Free Tableau Tutorial

Tableau is a business intelligence and data visualization software used by organizations to visualize and analyze data. It’s a powerful tool for data analysis and exploration. Tableau provides a range of options for data exploration, including interactive dashboards, reports, and visualizations.

Audience

This tutorial is intended for people who are new to Tableau and want to learn how to use the software. It is suitable for a wide range of users, including data analysts, business intelligence professionals, data scientists, and business users who want to gain insights from their data. It is also suitable for students and educators who are looking to learn the basics of Tableau.

Prerequisites 

1. Basic understanding of data and databases

2. Good understanding of basic computer operations

3. Familiarity with SQL and other query languages 

4. Previous experience with other data visualization tools (e.g. Microsoft Excel, Power BI, etc.) 

5. Knowledge of business intelligence concepts 

6. Basic knowledge of data wrangling and analytics 

7. Working knowledge of the Tableau interface and features

Tableau – Overview

Tableau is a powerful data visualization and analysis platform that helps people explore and analyze data quickly and easily. It provides interactive visualizations and dashboards that bring data to life. Tableau supports a wide range of data sources and allows users to quickly connect to their data, build visualizations and explore data in an intuitive way. It provides powerful features such as drag-and-drop functionality, interactive filtering, and ad-hoc data exploration. Tableau also offers advanced features such as predictive analytics and machine learning, enabling users to uncover hidden patterns and gain insights into their data. Tableau is used by data analysts, data scientists, and business professionals to quickly analyze and share insights on their data.

Tableau Features

Tableau offers a wide range of features to help users explore, visualize, and analyze data. These features include:

1. Drag-and-drop functionality: Tableau makes it easy to quickly build visualizations and charts with drag-and-drop functionality.

2. Data blending: Tableau enables users to merge data from multiple sources to create one comprehensive view.

3. Table calculation functions: Tableau has a range of functions for manipulating data and creating custom calculations.

4. Customization options: Users can customize their visualizations and charts with a variety of options, such as color, font, and size.

5. Dashboards and Storytelling: Tableau makes it easy to create interactive dashboards and share stories and insights through visuals.

6. Mobile app: Tableau Mobile allows users to access their data and analytics anytime, anywhere.

7. Cloud integration: Tableau integrates with cloud services such as Amazon Web Services and Google Cloud Platform.

Tableau – Environment Setup

Tableau is a popular data visualization tool that can help to quickly create visuals and analysis of large datasets. To set up a Tableau environment, you will need to follow the steps below:

1. Install Tableau Desktop: Download and install the Tableau Desktop application from the Tableau website.

2. Connect to data sources: Connect to the data sources you plan to use in your Tableau environment. This can include both local and external sources such as databases, spreadsheets, and cloud-based sources.

3. Create worksheets and dashboards: Create worksheets and dashboards in Tableau using the data sources you set up.

4. Publish to server: Publish your worksheets and dashboards to Tableau Server for easy access and sharing.

5. Set up Tableau Reader: Set up Tableau Reader to allow others to view and interact with your worksheets and dashboards without requiring them to install Tableau Desktop.

Tableau – Get Started

Tableau is a powerful data visualization tool used by businesses and organizations to quickly and easily create interactive visualizations of their data. It can be used to create basic charts, interactive dashboards, and advanced visualizations with just a few clicks.

To get started with Tableau, the first step is to download and install the software. Once installed, users can connect to data sources such as databases, spreadsheets, and text files. Then, users can use Tableau’s drag-and-drop interface to create visualizations.

Once a visualization is created, users can interact with it to gain deeper insights into their data. For example, they can filter and drill down into the data, add custom calculations, and create interactive dashboards.

Tableau also has a range of features designed to help users share their visualizations with others, such as embedding them into websites, creating reports, and sharing them on social media.

To get the most out of Tableau, users can take advantage of its powerful features, such as its scripting language, data blending, and advanced analytics. Additionally, users can also take advantage of Tableau’s extensive library of tutorials and resources.

Tableau – Navigation

Tableau allows users to quickly and easily navigate through data sets and explore different visualizations. It gives users the ability to drill down into data sets to gain insights and analyze trends.

Users can also use filters to narrow down the data to focus on specific aspects. They can also use parameters to dynamically adjust the data and create custom charts and visualizations. Additionally, Tableau provides a wide range of chart and graph types to choose from, allowing users to quickly explore data and gain insight.

Menu Commands 

1. File: Allows users to open, save, publish, export, import, and manage workbooks.

2. Data: Allows users to connect to data, edit connections, combine and edit data, join data, filter data, and create parameters.

3. Worksheet: Allows users to create and format worksheets, add calculations, and set up data hierarchies.

4. Dashboard: Allows users to create and format dashboards, add calculations, and set up data hierarchies.

5. Story: Allows users to create and format stories, add calculations, and set up data hierarchies.

6. Analyze: Allows users to add reference lines, create trend lines and forecasts, perform calculations, and edit data.

7. Map: Allows users to create and format maps, add calculations, and set up data hierarchies.

8. Format: Allows users to format worksheets, dashboards, and stories.

9. Window: Allows users to manage the window view, open and close windows, and tile windows.

10. Help: Allows users to access help topics and online resources.

File Menu 

Tableau’s File menu allows users to open, save, and share their data. This menu also provides access to a variety of options, such as creating new worksheets, data sources, and workbooks.

1. Open – Allows the user to open a file in Tableau.

2. Save – Allows the user to save their workbook or worksheet.

3. Save As – Allows the user to save their workbook or worksheet as a different file with a different name.

4. Close – Closes the current workbook or worksheet.

5. Revert – Reverts the current workbook or worksheet to its last saved state.

6. Data Source – Opens the Data Source window, which allows the user to view and edit the data source connections used in their workbook.

7. Extract Data – Allows the user to create a Tableau Extract from their data source.

8. Publish Data Source – Allows the user to publish their data source to Tableau Online or Tableau Server.

9. Append Data – Allows the user to append data from a different data source to the current data source.

10. Export Data – Allows the user to export data from the current data source.

11. Refresh Data – Refreshes the data in the current data source.

12. Recent Workbooks – This option allows the user to quickly access their recently opened workbooks.

13. New Worksheet – Creates a new worksheet in the current workbook.

14. New Workbook – Creates a new workbook.

15. New Data Source – Creates a new data source connection.

16. New Folder – Allows the user to create a new folder in the Tableau Repository.

17. Share – Allows the user to share their workbook with other Tableau users.

18. Export Image – Allows the user to export their worksheet as an image.

19. Export Crosstab – Allows the user to export their worksheet as a crosstab.

20. Export Packaged Workbook – Allows the user to export the current workbook as a packaged workbook.

21. Export Story – Allows the user to export their worksheet as a story.

22. Print – Allows the user to print their worksheet.

23. Page Setup – Allows the user to configure the page setup for their worksheet.

24. Exit – Closes Tableau.

Data Menu 

The Tableau Data Menu is a feature that allows users to quickly and easily access and explore their data. It provides a comprehensive view of all the data tables, fields, and measures in a workbook, and provides easy access to the data sources, calculations, and visualizations.

The Tableau Data Menu is located in the main toolbar. It contains a list of data sources and worksheets, along with their respective fields and measures. When the Data Menu is opened, users can easily select data tables, fields, and measures to add to their visualizations. The Data Menu also provides quick access to the Tableau calculation editor, allowing users to quickly create calculated fields and measures.

In addition to the Data Menu, Tableau also provides several other navigation options, including the Tableau Worksheet Navigator and the Tableau Field List. The Worksheet Navigator allows users to quickly move between worksheets in their workbook, while the Field List provides an overview of all the fields and measures in a workbook. By combining the Data Menu with the Worksheet Navigator and Field List, Tableau users can quickly and easily explore their data and create powerful visualizations.

Worksheet Menu 

1. Data: This menu item allows you to connect to data sources, import and export data, set data options, and create calculations.

2. Marks: This menu item allows you to select the type of visualization you want to use, apply color, size, and shape to the marks, and adjust the mark’s appearance.

3. Analytics: This menu item provides access to analytic tools such as reference lines, trend lines, and forecasting.

4. Reference: This menu item provides access to reference lines, forecasts, and trend lines.

5. Dashboard: This menu item allows you to create worksheets and combine them into a dashboard.

6. Story: This menu item allows you to organize related worksheets and dashboards into a storyboard.

7. Worksheet: This menu item allows you to create, edit, and manage worksheets.

8. View: This menu item allows you to change the view of your worksheet and dashboard.

9. File: This menu item allows you to save, open, print, and publish your workbook.

10. Server: This menu item allows you to publish your workbook to Tableau Server.

Dashboard Menu

The Tableau dashboard menu typically includes the following items:

1. File: This menu contains commands related to opening and saving Tableau workbooks, connecting to data sources, and other document-related tasks.

2. Data: This menu contains commands related to connecting to, managing, and preparing data for analysis.

3. Worksheet: This menu contains commands related to manipulating and exploring data in Tableau worksheets.

4. Dashboard: This menu contains commands related to creating, arranging, and formatting dashboards in Tableau.

5. Story: This menu contains commands related to creating and sharing interactive stories in Tableau.

6. Analysis: This menu contains commands related to exploring data, using calculations, and creating visualizations.

7. Map: This menu contains commands related to creating and formatting maps with Tableau.

8. Format: This menu contains commands related to formatting and styling Tableau worksheets, dashboards, and stories.

9. Help: This menu contains commands related to getting help with Tableau and learning more about the software.

Story Menu 

A Tableau story menu could be used to create a visual representation of a story. The menu would include a selection of visualizations that allow the user to explore the story in depth. The visualizations could include bar charts, line graphs, maps, scatter plots, and other types of data visualizations. The user would be able to select the type of visualization they would like to explore the story with and then be able to view the data in a meaningful way. The story menu could also be used to provide additional context to the story, such as providing an overview of the data or providing additional information about the characters or events. Overall, the story menu could be a powerful tool for conveying stories in a visual way.

Analysis Menu 

The Analysis menu in Tableau is a powerful tool that allows users to quickly and easily analyze their data in meaningful ways. The menu provides a wide range of options, including sorting, filtering, grouping, hierarchies, and calculated fields. The menu also allows users to create charts, maps, and other visualizations that can be used to better understand the data. Additionally, the menu provides access to powerful tools such as Tableau Prep and Tableau Desktop for more advanced data analysis.

Map Menu 

Tableau’s Map menu is located in the toolbar at the top of the screen. It is the fifth icon from the left and looks like a globe. Clicking on the Map menu will open a drop-down menu with options to create, format, and analyze maps. Options include Map Layers, Map Options, and Spatial File. Additionally, you can access further map-related tools and options by right-clicking on the map itself.

Format Menu 

The Format menu in Tableau can be found under the Home tab in the ribbon menu. It allows users to customize the look and feel of their worksheets and dashboards. This includes options to format text, adjust fonts, and change colors. It also features options to add borders, adjust spacing, and apply formatting to specific sections of the worksheet. The Format menu also includes options to format dates and times, and edit the worksheet’s background.

Server Menu 

Tableau can be used to create a server menu. The server menu can be created in Tableau by using text boxes and drop-down menus to enter the different menu items. Once the items have been entered, they can be formatted to create a visually appealing menu. The server menu can also be made interactive by adding interactive elements such as sliders and buttons. This allows the user to quickly find the items they are looking for and make selections. Additionally, the menu can be filtered to show only certain items based on the user’s preferences.

Tableau – Design Flow

Tableau is a data visualization software that allows users to quickly and easily create visualizations from their data. It is designed to be user-friendly, so users can quickly and easily understand their data.

Tableau’s design flow is an iterative process that begins with understanding the user’s data. This involves exploring the data, understanding relationships within the data, and determining which visualizations will be most effective. Once the user has an understanding of their data, they can begin creating visualizations. Tableau provides a wide range of visualization options, including graphs, maps, and charts.

Once the user has created their visualizations, they can refine them by editing the visuals and the data behind them. This allows them to create the best possible visualizations that accurately represent their data.

Finally, users can share their visualizations with others. Tableau provides a range of sharing options, including direct sharing, embedding, or exporting. This allows users to easily share their visualizations with colleagues, customers, or the public.

Connect to Data Source 

Tableau offers multiple ways to connect to data sources. It can connect to a wide variety of data sources such as relational databases, cloud-based data sources, multidimensional databases, and Excel spreadsheets. It also supports connectivity to many web-based data sources like Google Analytics and Salesforce. Tableau also supports direct connection to Hadoop and web data connectors for custom web data sources. To connect to a data source, open Tableau and select the “Data” tab in the toolbar. From there, choose the type of data source you want to connect to. Tableau will then prompt you to enter the connection information for the data source. Once you have successfully connected to your data source, you can start exploring and visualizing your data with the help of Tableau’s powerful analytics and visualization tools.

Build Data Views 

Tableau is an interactive data visualization tool that can be used to create a variety of data views. Tableau allows users to create visualizations such as bar charts, line graphs, maps, and more. Tableau also offers a variety of features that enable users to filter, group, and sort data in order to gain insights from their data.

1. Bar Charts: Bar charts are a great way to compare data points. They are especially useful for comparing categorical data such as gender, product types, and job titles. 

2. Line Graphs: Line graphs are useful for tracking trends over time. They can be used to show the changes in a particular data point over a period of time or to compare multiple data points over time. 

3. Maps: Maps are a great way to visualize geographic data. They can be used to show the distribution of data points across a geographic area or to compare different geographic regions. 

4. Scatter Plots: Scatter plots are useful for comparing two data points to show the correlation or relationship between them. 

5. Heat Maps: Heat maps are useful for visualizing data that has a high degree of variability. They are especially useful for showing patterns and trends in data that is too complex or too large to be displayed in other types of charts. 

6. Pie Charts: Pie charts are great for displaying the proportions of a particular data point. They are especially useful for comparing the relative sizes of different categories. 

7. Tree Maps: Tree maps are useful for showing the hierarchical structure of data. They are especially useful for displaying the relationships between different data points. 

8. Bullet Graphs: Bullet graphs are useful for comparing data points over time. They are especially useful for comparing the performance of different data points over a period of time. 

9. Box Plots: Box plots are useful for displaying the distribution of data points. They are especially useful for showing the range, median, and quartiles of a data set.

Enhance the Views 

Tableau is a powerful data visualization tool that can help you quickly create and share compelling visualizations of your data. Here are some tips for enhancing your visualizations in Tableau:

1. Use color strategically. Color can be used to emphasize certain features, draw attention to certain parts of your data, and even help communicate a message.

2. Utilize charts and graphs. Different charts, such as bar charts, line graphs, and scatter plots, are all great ways to visualize your data in Tableau.

3. Use labels and annotations. Adding labels and annotations to your visualizations can help make it easier to understand your data.

4. Add calculations and parameters. Calculations and parameters can be used to create dynamic visualizations that can be adjusted based on the user’s preference.

5. Make use of interactive features. Tableau comes with a range of interactive features, such as filters, that can help you create dynamic visualizations.

6. Take advantage of formatting options. Tableau has a wide range of formatting options that can help you customize the look and feel of your visualizations.

Create Worksheets 

Tableau is a powerful business intelligence software that enables users to quickly create and publish interactive worksheets. To create a worksheet in Tableau, you need to first connect to your data source, then set up the visualization, and finally publish it to the web. 

1. Connect to Data Source: To connect to a data source in Tableau, you first need to open Tableau Desktop. Once it is open, select the “Connect” option from the top left corner. From here, you can select the type of data source you want to connect to. You can connect to Excel, CSV, and text files, as well as databases such as Oracle, MySQL, and PostgreSQL.

2. Create Visualization: After connecting to your data source, you can begin creating your visualization. Tableau provides a wide range of charts, graphs, and maps to choose from. Simply drag and drop your data fields onto the worksheet to create your visualization. 

3. Publish Worksheet: Once you have created your visualization, you can publish it to the web. In Tableau Desktop, click the “Share” icon in the top right corner. Enter the address you want to publish to, then click “Publish.” Your worksheet will now be accessible to anyone with the link.

Create and Organize Dashboards

1. Create a Dashboard:

a. Launch Tableau and connect to the data source.

b. Drag and drop the necessary fields from the data set onto the canvas.

c. Select the chart type for each field and customize it with additional formatting options.

d. Add additional objects such as webpages, images, and text to the dashboard.

e. Arrange the objects on the dashboard to create a visually appealing layout.

f. Add interactive filters, parameters, and actions as needed.

g. Preview the dashboard and make any necessary adjustments.

h. Save the dashboard.

2. Organize a Dashboard:

a. Start by grouping related fields.

b. Organize the dashboard into sections that each focus on a specific topic.

c. Use color, fonts, and shapes to create visual hierarchy.

d. Make use of whitespace to create a clean and organized look.

e. Utilize the dashboard sidebar to provide easy access to filters and parameters.

f. Add titles, captions, and other text elements to clearly explain the dashboard’s purpose.

g. Preview the dashboard and make any necessary adjustments.

h. Save the dashboard.

Create a Story  

Once upon a time, there was a small town nestled in the hills of a beautiful valley. The town, named Happiness Valley, was known for its vibrant culture and its idyllic scenery. 

The people of Happiness Valley had a deep connection with the land and the natural beauty around them. Every morning, the townspeople would climb to the top of the highest hill and take in the breathtaking view of the valley. 

One day, a group of travelers arrived in Happiness Valley, seeking to explore the town and its surrounding area. The travelers were enchanted by the beauty of the valley and decided to stay for a while. 

The travelers quickly became part of the community and were welcomed into the homes of the townspeople. They quickly discovered that the people of Happiness Valley were not only kind and generous, but also incredibly talented. 

The townspeople shared their culture and traditions with the travelers, teaching them how to make traditional dishes, craft beautiful artwork, and play traditional music. The travelers were captivated by the culture and decided to stay even longer.

After a few months, the travelers had grown to love Happiness Valley and its people. They decided to create a Tableau to capture the beauty of the valley and to share the stories of the people who lived there. The Tableau was a stunning work of art that showcased the beauty of the valley and the rich culture of the townspeople. 

To this day, the Tableau is still displayed in Happiness Valley, reminding all who visit of the beauty and culture of the town.

Tableau – File Types

Tableau supports many different file types, including:

• Excel (.xls and .xlsx)

• Text/CSV (.csv)

• JSON (.json)

• Statistical Files (SAS, SPSS, and RData)

• Statistical file types such as Stata (.dta)

• Spatial Files (KML, MapInfo, GeoJSON, and TopoJSON)

• Hyper files (.hyper)

• Database connections (Oracle, SQL Server, MySQL, etc.)

• Web Data Connectors (WDC)

• Tableau Data Extracts (.tde)

• Tableau Packaged Files (.twbx)

Tableau – Data Types

Tableau supports the following data types:

– String (text): A sequence of characters, such as words or numbers, that can be used as labels.

– Numeric: Numbers stored as integers, decimals, or currency values.

– Date & Time: Dates and times stored as either a timestamp or a string.

– Boolean: True/False values stored as either 0 or 1.

– Geographical: Data such as country, region, and city names.

– Binary: Binary data stored as a series of 1s and 0s.

Tableau – Show Me

Tableau is a powerful data visualization tool that enables users to easily create interactive visualizations. Using Tableau, users can easily create bar charts, scatter plots, line graphs, maps, and many other types of visualizations to quickly identify trends and insights from their data. Tableau also provides a wide range of features and options that allow users to further customize and refine their visualizations. Tableau is a great tool for quickly exploring and analyzing data, and its interactive features make it a great choice for data exploration and storytelling.

Show Me with Two Fields 

1.   Create a new workbook in Tableau.

2.   Connect to your data source.

3.   Drag and drop two fields from the data pane into the Columns and Rows shelves.

4.   Select a chart type from the Show Me menu.

5.   Adjust the chart and the axes to customize the visualization.

Show Me with Multiple Fields 

Tableau can show multiple fields in different ways. For example, you can simply drag and drop multiple fields into the view to display them side by side. You can also use the Show Me feature to quickly create charts that visualize multiple fields at once. To use Show Me, simply select the fields you want to visualize in the Data pane and then click the Show Me button in the bottom right corner. Tableau will then present a list of chart options that you can use to visualize the selected fields.

Tableau – Data Terminology

1. Worksheet: A worksheet is a single page in a workbook, which is a collection of multiple worksheets.

2. Dashboard: A dashboard is an interactive visual display of key performance indicators (KPIs) that allows users to quickly analyze and compare data points.

3. Pivot Table: A pivot table is a data summarization tool that allows users to quickly summarize data from multiple related sources.

4. Calculated Field: A calculated field is a formula or expression used to generate values within a pivot table.

5. Filter: A filter is a set of rules used to limit the data displayed in a view.

6. Dimension: A dimension is a data category that is used to organize and classify data.

7. Measure: A measure is a numerical value that is calculated from the data in a view.

Tableau – Data Sources

Tableau supports a variety of data sources, including relational databases, spreadsheets, cloud-based sources and big data. Some of the most popular data sources for Tableau include Microsoft Excel, Microsoft Access, Microsoft SQL Server, Oracle, PostgreSQL, MySQL, Google BigQuery, Salesforce, Amazon Redshift, and Teradata. Tableau also has built-in connectors for Amazon Web Services, Microsoft Azure, and Google Analytics.

Connect Live 

Tableau Connect Live is an online data source that enables users to connect to their data stored in an online database, such as Amazon Redshift, Google BigQuery, Snowflake, Microsoft Azure SQL Database, and many others. It enables users to create powerful visualizations and data insights without the need to manually move data or write complex queries. Through Connect Live, users can also access data stored in cloud systems such as Salesforce, Microsoft Dynamics, and other platforms. Connect Live also supports data blending, which allows users to join data from multiple sources into a single visualization.

In-Memory 

Tableau offers the ability to work with in-memory data sources, which allows users to quickly and easily analyze data without having to create a physical connection to an external data source. This is especially useful when dealing with large datasets that could take a long time to query from an external source. To use an in-memory data source, simply select “Create In-Memory” from the Data Source page in Tableau. You can then drag and drop data from your computer into the data source, or import data from a spreadsheet or text file. Once the data is in-memory, you can analyze it in Tableau just like any other data source.

Combine Data Sources 

Tableau allows users to combine multiple data sources into a single view or dashboard. This can be accomplished by creating a Union, blending, or joining the data sources. 

A Union is the most basic way to combine data sources in Tableau, and it is used when two or more data sources have the same data structure. A Union combines the data from each source into a single table.

Blending is used when the data sources have different data structures. Blending allows you to combine the data from each source into a single table using a common field.

Joining is used when the data sources have the same data structure and you want to combine the data from each source into a single table using a common field. Joins in Tableau can be inner, left, right, left outer, right outer, or full outer. 

Tableau also allows you to combine data sources using parameters, calculations, and custom SQL. Parameters allow you to interactively control a data source in a view. Calculations allow you to create calculated fields that use data from multiple data sources. And custom SQL allows you to write your own queries to combine data sources.

Tableau – Custom Data View

Tableau is a data visualization tool that can be used to create custom data views. It allows users to combine data from multiple sources, create interactive visualizations, and explore data in an intuitive way. Tableau is a powerful tool for creating visualizations that can help to uncover insights and trends in data. It can be used to uncover patterns, correlations, and trends in data that may not be obvious. Tableau also allows users to customize the data view by adding filters and custom calculations. This makes it possible to create deeper insights from data. By combining data from multiple sources and creating interactive visualizations, Tableau makes it easier to analyze and understand complex data sets.

Drill Down View

A drill down view in a custom data view is a way to view a large amount of data in an organized and detailed way. The user can start with a top-level overview of the data, and then “drill down” into more detailed levels of information. This is often accomplished by allowing the user to click on specific elements within the data view to reveal more detailed information. For example, a drill down view might allow a user to select a specific region, and then show detailed information about that region such as population, income, and other key metrics. This can be a powerful way to quickly analyze and understand large datasets.

Swapping Dimensions  

Swapping dimensions in a custom data view can be done by first selecting the dimensions you would like to swap. Once the dimensions have been selected, you can drag and drop them into the desired position. Alternatively, you can also right-click on the desired dimension and select the “Swap Dimension” option. This will then switch the two dimensions in the custom data view.

Tableau – Extracting Data

Tableau provides a range of features for extracting data from a variety of sources. The Tableau Extract API allows users to access data from their databases, web services, and file systems directly from within Tableau. Additionally, Tableau provides built-in functions for connecting to and extracting data from a variety of sources, including relational databases, text files, Hadoop, Google BigQuery, and Salesforce. Tableau also provides an Extract Builder which makes it easy to extract data from a variety of sources. With the Extract Builder, users can select the data they need and specify how often it should be refreshed.

Creating an Extract 

To create an extract in Tableau, select the Data menu and then select Extract Data. You will then be prompted to connect to a data source. Once you have connected to the data source, choose the data you would like to extract. You can also choose to filter the data, as well as specify the type of extract you would like to create. Finally, click the Extract button to create the extract.

Applying Extract Filters 

In Tableau, extract filters can be applied to data in a few different ways. Firstly, they can be applied directly to an extract (if one has already been created). This can be done by right-clicking on the extract and selecting “Edit Extract Filters”. Secondly, they can be applied to the data source itself by clicking the “Data” tab, selecting “Edit Data Source Filters”, and then adding the required filters. Finally, they can be applied to individual worksheets by clicking “View”, selecting “Worksheet”, and then clicking “Filters”. From here, the required filters can be added.

Adding New Data to Extract 

When adding new data to an extract in Tableau, the first step is to identify the source of the data. This can include a database, an online service, or a file. Once the source of the data is identified, the user should determine the connection type that will be used to connect the source to Tableau. This can be an ODBC connection, a live connection, or a direct connection. After selecting the connection type, the user will need to configure the connection settings to extract the desired data. This may include authentication, specifying the fields to be included in the extract or making sure that the extract includes the latest data. Finally, the user can build the extract and configure the extract refresh settings.

Extract History 

Tableau is a powerful data visualization and business intelligence tool that can be used to extract data from a variety of sources. With Tableau, users can quickly and easily connect to a data source, extract the necessary data, and then create visualizations to gain insight into the data. Tableau also provides a range of options for users to extract historical data.

One of the most popular methods of extracting historical data with Tableau is to use the built-in Tableau Extracts feature. Tableau Extracts are a way of storing data in a Tableau-optimized format, which can then be used to create visualizations. To create a Tableau Extract, users can connect to their data source, select the fields they want to extract, and then select the “Create Extract” option. Once the extract is created, Tableau will store the data in its own optimized format, which will make it easier and faster to create visualizations.

Another method of extracting historical data with Tableau is to use the Tableau Data Extract API. This API allows users to create their own custom extract files in Tableau, which can then be used to create visualizations. To create an extract using the Tableau Data Extract API, users can use the Tableau Server Client (TSC) library to connect to their data source, create an extract file, and then use the extract in Tableau.

Finally, users can also extract historical data from other sources, such as databases, text files, and web services, using Tableau’s Web Data Connector. The Web Data Connector allows users to connect to a variety of data sources, extract the necessary data, and then use it in Tableau.

No matter which method is used, Tableau provides a range of options for users to extract historical data and create visualizations. With the right tools and techniques, users can quickly and easily gain insight into their data.

Tableau – Fields Operations

Tableau – Fields Operations is an online tool designed to help businesses manage their data fields. It can be used to automate the creation, modification, and deletion of data fields. The tool allows users to control which fields are visible and which are not, and to customize field names and data types. Additionally, it provides a visual representation of the data fields, allowing users to quickly identify and make changes. With Tableau – Fields Operations, organizations can ensure their data is organized and up to date, providing the foundation for data-driven decision making.

Adding Fields to Worksheet 

In Tableau, adding fields to a worksheet can be done by simply dragging and dropping the desired fields from the Data pane onto the view. The fields can be dropped onto the Rows and Columns shelves, as well as the Filters and Marks cards. Additionally, fields can be added from the Data pane to the view by right-clicking the field name and selecting “Add to” from the context menu. This will open the Add to Contextual Menu, where the user can select where they would like to add the field.

Combining Two Fields 

To combine two fields in Tableau, one can use the “Combine Fields” feature within the Dimensions pane. This feature allows for two or more fields to be combined into a single field. To combine two fields, right-click on one of the fields and select “Combine Fields”. Then select the other fields you want to combine and choose an appropriate delimiter. Finally, click “OK” to combine the fields.

Searching Fields 

Tableau allows users to search for fields in various ways. The quickest way is to use the search bar at the top of the Data window. This search bar allows users to search for fields by name, data type, and other variables. Additionally, users can also filter fields in the Data window by selecting the “Show Me” option. This option allows users to filter fields by data type, such as numerical or string data. Finally, users can also navigate to the Dimensions or Measures shelves to search for relevant fields.

Reordering Fields

1. Right-click on the field you want to move in the Data pane.

2. Select “Move Dimension”

3. Select where you want to move the field (up or down).

4. The field will be reordered.

Tableau – Editing Metadata

Tableau allows users to edit metadata by right-clicking on the field or column in the data pane and then selecting “Edit Metadata”. This will open a dialog box where users can change field name, type, default aggregation, and other properties. They can also add descriptions, comments, aliases, and other custom properties. Additionally, users can set the data type for each field, which can be used to ensure that calculations are performed correctly in Tableau.

Checking the Metadata 

Metadata in Tableau can be accessed by clicking on the Data Menu. From there, the user can view the data source, the fields in the data source, and the data types for each field. Additionally, a user can also view the relationships between different fields in the data source.

Changing the Data Type

Tableau allows users to change the data type of a field by right-clicking on the field in the Data window, selecting “Change Data Type” and then selecting the desired data type from the drop-down menu. Alternatively, users can select “Edit Data Type” from the drop-down menu in the Data window. This will open a dialog box in which users can select the desired data type. Additionally, users can also change the data type of a field in the Data pane of a Tableau worksheet by selecting the field, clicking on “Edit Data Type” from the drop-down menu and selecting the desired data type from the list.

Renaming and Hiding 

Tableau allows users to rename and hide certain elements of their data. To rename an element, users can select the element from the Data pane and then select the “Rename” option from the context menu. To hide an element, users can select the element from the Data pane and then select the “Hide” option from the context menu. Tableau also allows users to change the data type for elements, which can be done by selecting the element from the Data pane and then selecting the “Change Data Type” option from the context menu.

Column Alias  Tableau – Data Joining

Tableau is a data visualization software used to create interactive and attractive visualizations. It is most commonly used to join data from multiple sources, allowing users to explore relationships between different data sets. Joining data in Tableau is a process that involves connecting multiple data sources together to create a single, unified view. This can be done by linking tables, appending data, or using a custom join. Tableau also makes it easy to create custom calculations and visualizations based on the joined data.

In Tableau, column aliases are used to assign an alternative name to a column in a data source. They help make the data easier to understand by replacing long column names with short, meaningful ones. For example, a column with the long name “Total Sales for the Previous Year” can be replaced with the alias “Previous Year Sales”.

Creating a Join 

1. Open Tableau and connect to the data source.

2. Drag the two tables you want to join onto the Data pane.

3. Click on the join type icon (three dots) for the secondary table and select the join type.

4. Select the common field(s) to be used as the join key.

5. Click on the join type icon (three dots) for the primary table and select the join type.

6. Select the common field(s) to be used as the join key.

7. Select the join type (Inner, Left, Right, Full Outer, etc.)

8. Click the “Apply” button.

Your join should now be created.

Editing a Join Type 

1. Open the Tableau Desktop application.

2. Select the data source that you want to edit.

3. Click on the “Data” tab at the top of the screen.

4. Select the “Joins” option on the left side of the Data window.

5. Select the Join Type that you want to edit.

6. Make the appropriate changes to the Join Type options.

7. Click “Ok” to save your changes.

Editing Join Fields 

To edit join fields in Tableau, first select the data source on the left side of the Tableau workspace. Then, click on the Join icon in the toolbar and select the two data sources you would like to join. Next, click on the join type dropdown and choose the type of join you would like to perform (e.g. inner join, left join, etc). Finally, select the fields you would like to join and click the “OK” button. This will join the two data sources and the fields you specified will be used as the join fields.

Tableau – Data Blending

Tableau data blending is a process by which data from different sources can be combined in a single Tableau visualization. The process involves creating a connection to each data source, creating a relationship between the data sources, and then blending the data together. The data blending process can be used to create powerful visualizations that allow users to quickly analyze and understand data from multiple sources. Data blending can also be used to combine disparate data sources and create a single, unified view of the data.

Preparing Data for Blending 

Blending data in Tableau is the process of merging multiple data sets into one visualization. Before blending data in Tableau, the data sets must first be prepared and organized.

1. Identify Data Sources: The first step is to identify all of the data sources that you want to use in your visualization. Make sure that all of the data sources have the same structure and contain compatible data types.

2. Clean Data: Once the data sources are identified, clean the data by removing any unnecessary or irrelevant columns. You should also make sure to standardize data types and formats across all data sets.

3. Join Data: Before blending the data, you must decide how the data will be joined together. If the data sets have common columns or fields, you can use those to join the data together. Otherwise, the data sets will need to be linked using a unique identifier, such as a customer ID.

4. Organize Data: Once the data sets have been joined, organize the data in a logical and consistent manner. This will make it easier to create visualizations in Tableau.

5. Create Visualizations: Once the data has been prepared and organized, you can begin to create visualizations in Tableau using the blended data sets.

Adding Secondary Data Source

1. Open Tableau Desktop and connect to your base data source.

2. On the left side of the window, select the Data Source tab.

3. In the Data Source tab, select the Data Sources pane.

4. Click the New Data Source icon in the lower-left corner.

5. Select the type of data source you want to add.

6. Connect to the data source using the authentication credentials provided.

7. Once the data source is connected, add the dimensions and measures you wish to analyze.

8. Drag the dimensions and measures to the appropriate areas on the worksheet.

9. Click the Sheet tab in the lower-left corner to go back to the worksheet.

10. Select the Data pane in the left sidebar.

11. From the Data pane, select the Relationships tab.

12. Select the relationship type that you wish to establish between the two data sources.

13. Click the Apply button to save your changes.

14. You are now ready to analyze data from both data sources in Tableau.

Blending the Data  

Blending data in Tableau is a process of combining two or more data sources into a single view. This process is useful for analyzing data from different sources and creating more complex visualizations. To blend data in Tableau, select the Data menu and then select the “Blend Data Sources” option. Select the two or more data sources to be blended, and then click on the “Blend” button. Tableau will then create a blended view of the data sources.

Tableau – Add Worksheets

You can add worksheets to a Tableau workbook in a few simple steps.

1. Select the Worksheets tab from the left side of the Tableau Desktop.

2. Click the “+” sign to add a new worksheet.

3. Select the type of data source you want to use and click OK.

4. Select the fields you want to include in the worksheet and click OK.

5. Select the visualizations you want to use and click OK.

6. Enter the title of the worksheet and click OK.

7. Tableau will create the worksheet in the workbook.

Adding a Worksheet 

1. Open Tableau Desktop and select the “New Worksheet” option from the File menu.

2. Select a data source from the list of available connections. You can also use the “More” option to connect to a variety of different data sources.

3. Once you have selected a data source, drag and drop fields from the data pane into the view.

4. To start creating visualizations, use the “Marks” card and select either a “Shape”, “Color”, “Size”, or “Label” option to apply to the field.

5. You can also add additional fields to the view by dragging them from the data pane and adding them to the Marks card.

6. Once the visualization is created, use the “Analytics” pane to add additional insights and calculations to the view.

7. To save the worksheet, select the “Save Worksheet” option from the File menu.

8. Name the worksheet and save it to the desired location.

Tableau – Rename Worksheet 

To rename a worksheet in Tableau, right-click the tab of the worksheet you want to rename and select “Rename Sheet”. Type in the new name and press Enter.

Quick Preview of a Worksheet 

The worksheet preview can be seen on the left of the Tableau interface. It will display a preview of the data that is currently loaded in the worksheet, as well as any visualizations that have been created. The worksheet preview will also show any dimensions, measures, or fields that have been added to the worksheet view. Additionally, any filters, parameters, and sets that have been added to the worksheet will be visible in the worksheet preview.

Tableau – Save & Delete Worksheet

Tableau worksheets can be saved by clicking the File menu and then selecting the Save option. The worksheet can also be deleted by clicking the File menu and then selecting the Delete Worksheet option.

Tableau – Reorder Worksheet

Tableau allows users to easily reorganize worksheets within a dashboard. To do this, click and drag the worksheet tab to the desired position. Once you have the worksheets in the desired order, click the ‘Update’ button in the bottom right corner of the dashboard window to save your changes.

Tableau – Paged Workbook

Tableau Paged Workbooks are interactive web pages that can be used to create a variety of data visualizations. A Tableau Paged Workbook is an ideal tool for data analysis, as it allows the user to view the data in a variety of ways, and quickly create charts, graphs, and other visualizations. Tableau Paged Workbooks are interactive, allowing the user to interact with the data by filtering and sorting, as well as creating custom visualizations. They are also highly customizable, allowing the user to control the size, layout, and design of the visualizations, as well as the type of data that is being displayed. Tableau Paged Workbooks are easy to use, and can be shared with other users, allowing for collaboration and data sharing.

Tableau – Operators

Tableau provides a range of operators for performing calculations and filtering data. 

Types of Operator

Tableau – Functions

String Functions: These are functions used to manipulate strings such as concatenating, trimming, substituting, converting to upper or lower case, and extracting a part of a string.

Date Functions: These are functions used to manipulate dates such as adding, subtracting, formatting, and comparing dates.

Logical Functions: These are functions used to evaluate logical statements and return true or false values.

Aggregate Functions: These are functions used to calculate aggregate values from a set of values such as sum, average, minimum, and maximum.

Tableau – Numeric Calculations

Tabular calculations are numerical calculations that are performed using tables. Tabular calculations are used to calculate a variety of data, including financial data, statistical data, and mathematical data. Tabular calculations are typically used in data analysis and decision-making. Tabular calculations are also used in a variety of other applications, including risk management and forecasting. Tabular calculations can involve simple arithmetic operations such as addition, subtraction, multiplication, and division, as well as more complex operations such as exponentiation, logarithms, and trigonometric functions. Tabular calculations can also be used to calculate the average, median, and mode of a set of data.

Create Calculated Field 

Calculated fields are custom fields that allow you to perform calculations and modify existing fields in Tableau. To create a calculated field, click the “Analysis” tab at the top of the Tableau window, then select “Create Calculated Field” from the drop-down menu. A window will open where you can enter the expression you want to use to calculate the field. You can use basic math operators and functions, as well as a variety of other options. Once you are finished, click “OK” to save the calculated field.

Calculation Editor 

Tableau’s calculation editor is a powerful tool that allows users to create custom calculations to use in their visualizations. The calculation editor is a text-based interface that can be accessed by clicking the down arrow next to the measure or dimension fields in the data pane. This opens a window where users can enter their calculations using the Tableau expression language. The expression language allows users to create complex calculations that can be used to generate new measures and dimensions, or perform calculations on existing fields. The calculations can be used to calculate averages, sums, counts, and more. The calculation editor also allows users to use advanced functions such as logical operators, case statements, and custom functions. The calculations can be saved for future use and can be applied to other workbooks as well. With the calculation editor, users can quickly and easily create custom calculations to use in their visualizations.

Using the Calculated Field 

Once the calculated field has been created, it can be used in Tableau to display the data. To do this, the calculated field can be added to the view. In the view, the calculated field can be used to create a measure or visualization. For example, a bar chart can be created with the calculated field as the measure, and the other field as the dimension. This will give a visualization of the difference in values between the two fields.

Applying Aggregate Calculations 

Aggregate calculations can be applied in Tableau through the use of aggregate functions such as SUM, AVERAGE, MIN, MAX, COUNT, and more. These can be used to perform calculations on data such as sums, averages, counts, and more. For example, to calculate the average sales for a particular region, a user can use the AVG function on the Sales field. Additionally, Tableau also allows users to create custom calculations that use multiple fields and functions. For example, a user can create a custom calculation that calculates the sum of Sales and Returns for a particular region.

Tableau – String Calculations

String calculations in Tableau can be done using the CALCULATE and CALCULATETABLE functions. The CALCULATE function is used to perform basic calculations such as addition, subtraction, multiplication, and division. The CALCULATETABLE function is used to perform more complex calculations such as string concatenation and extraction of substrings. Both functions can also be used to compare values in strings and return logical values (true/false).

Tableau – Date Calculations

Tableau is a powerful data visualization and business intelligence tool that can be used to calculate dates and time periods. With Tableau, you can calculate the difference between two dates, add or subtract days, weeks, months, and years from a given date, calculate the age from a given date, calculate the number of days in a month, and much more. Tableau also supports various date formats, including the Gregorian calendar, ISO 8601, and Unix Epoch. Additionally, Tableau can be used to generate dynamic date ranges and to use date parameters for filtering and grouping.

Tableau – Table Calculations

Table calculations are used to analyze data in Tableau. They allow you to perform calculations on your data, such as running totals, ranking, percentiles, and more. Table calculations are used to calculate values on a row or column level. They can be used to compare data points or help to visualize trends in your data. Table calculations can also be used to create custom calculations, such as calculating the difference between two data points. Table calculations can be used in combination with other features, such as filters, parameters, and sets.

Tableau – LOD Expressions

LOD Expressions are a powerful tool used in Tableau to allow users to perform calculations on specific data points. These calculations are defined by the user and can be used to create measures, create dynamic views, and even generate custom insights. LOD Expressions are made up of three distinct parts: the dimension, the measure, and the aggregation. 

The dimension is the data point that the user wants to analyze. It may be a customer, a product, or any other type of data point. The measure is the calculation that the user wants to perform on the dimension. It could be a simple sum or an average, or a more complex calculation such as a median or percentile. Finally, the aggregation defines how the measure will be calculated across the dimension. It could be an average, a sum, or a count. 

LOD Expressions are a great tool for data analysis and allow users to get specific, granular insights into their data. They are an invaluable tool for Tableau users and can be used to create powerful visualizations.

FIXED LOD (Level of Detail) expressions are used to calculate aggregations at a level that is not the same as the level of the view. These expressions are used to compute values that are independent of the level of detail in the view.

INCLUDE LOD expressions are used to force Tableau to include data from a lower level of detail than what is in the view. This is useful when you have data from multiple levels of detail that you want to include in your calculations.

EXCLUDE LOD expressions are used to force Tableau to ignore data from a higher level of detail than what is in the view. This is useful when you have data from multiple levels of detail that you want to exclude from your calculations.

Tableau – Basic Sorting

Tableau offers a variety of sorting options. To sort a data field, first select the field you want to sort. Then, right-click on the field and select either “Sort Ascending” or “Sort Descending”. You can also sort by multiple fields by selecting the fields you want to sort, then right clicking and selecting “Sort.” You can also select “Sort by Field” to sort by multiple fields at once. Additionally, you can create custom sorting options by using the “Sort by Formula” option.

Computed Sorting

Computed sorting is a sorting algorithm that uses mathematical calculations to sort data. It can be used to sort data of any type, including numbers, text, dates, and other objects. This type of sorting is often used when sorting large datasets, as it is more efficient than other sorting methods. It is also often used when sorting data that is not easily sorted using traditional sorting algorithms, such as natural language text.

Manual Sorting

Manual sorting is a process of organizing items into specific categories or classes by hand. This could be done with items such as books, documents, toys, or any other item that can be classified. Manual sorting is most often done using sorting cards, which have labels or other indicators of the category. This method is used when a large number of items need to be sorted quickly, easily, and accurately.

Tableau – Basic Filters

Tableau offers a variety of basic filters that can be used to refine data. The most common basic filters include:

• Dimension Filters: Filters that are based on the columns in your dataset (e.g. year, country, product category).

• Measure Filters: Filters that are based on the values in your dataset (e.g. sales, profit, cost).

• Date Filters: Filters that are based on date values (e.g. last week, last month, year-to-date).

• Top N Filters: Filters that allow you to select the top or bottom N values in a given measure.

• Range Filters: Filters that allow you to select a range of values (e.g. sales between $100 and $200).

• Wildcard Filters: Filters that allow you to search for specific text values (e.g. product names that contain “widget”).

Filter Dimensions: Filter Dimensions allows users to filter the data according to the dimension of the data set. For example, if a dataset contains columns for Country, State, and City, a user can use Filter Dimensions to narrow down the data to only include those from a certain country, state, or city.

Filter Measures: Filter Measures allows users to filter the data according to the measure of the data set. For example, if a dataset contains columns for Sales and Profit, a user can use Filter Measures to narrow down the data to only include those with a certain level of sales and profit.

Filter Dates: Filter Dates allows users to filter the data according to a certain time period or range. For example, if a dataset contains columns for Date Sold and Date Returned, a user can use Filter Dates to narrow down the data to only include those within a certain time period.

Tableau – Quick Filters

Tableau Quick Filters are designed to give users the ability to quickly filter a view or dashboard. These filters can be applied to any measure or dimension within the data. Quick Filters are dynamic, meaning they can be changed without having to go through the entire process of creating a new filter. They can also be used to filter across multiple data sources. Quick Filters are a great way to quickly explore and analyze data without having to create multiple filters.

Tableau – Context Filters

Tableau context filters are a type of filter that can be used to limit the amount of data that is returned when a query is executed. They are different from traditional filters because they allow the user to create a context around the data that is being queried. This context can be used to limit the data that is returned to only the most relevant information. For example, a context filter can be used to limit the data returned to only those records that match a certain date range or geographic region. Context filters can be used to quickly narrow down large datasets to the most relevant information.

Creating Context Filter 

1. Open your Tableau workbook.

2. Select the sheet or dashboard where you want to create the Context Filter.

3. Select Analysis > Create > Context Filter.

4. Select the field that you want to use as a filter.

5. Select the type of filter you want to apply: Include, Exclude, or Top.

6. Choose the type of aggregation you want to use: Sum, Average, Minimum, Maximum, Count, or Percentile.

7. Select the range of values that you want to include or exclude.

8. Click OK.

Tableau – Condition Filters

Condition filters in Tableau allow the user to filter viewable data based on specific conditions. For example, users can filter the data to show only records with a certain value in a certain field, or records that fall within a certain date range. Condition filters can also be used to filter out certain records, such as those with null values or those that don’t meet certain criteria.

Creating Condition Filter 

1. Navigate to the data source tab in Tableau 

2. Select the data set

3. Drag and drop the dimension or measure field to the filter shelf

4. Select the condition from the list of options, such as ‘equal to’, ‘less than’, ‘greater than’

5. Enter the value for the condition in the text box

6. Click ‘Apply’ to confirm the selection

Tableau – Top Filters

Tableau Top Filters are fast, easy-to-use filters that allow users to quickly and easily filter data by predefined criteria without having to manually search through the entire dataset. These filters can be used to quickly identify outliers, trends, and patterns in data, and can be used to quickly answer questions such as “What is the most popular product?” or “Which region is seeing the highest sales?” Top Filters are also highly customizable, allowing users to apply multiple filters at one time and to adjust the criteria used to create the filters.

Creating a Top Filter

1. Open Tableau and connect to a data source.

2. Drag a dimension field to the Filters shelf.

3. Select the “Top” option from the menu.

4. Enter the number of values to be included in the filter.

5. Click “OK”.

6. The filter will now display the top values according to the specified criteria.

Creating Filters  

Tableau allows users to quickly and easily create filters. To do this, right-click on any field in the data source view and select “Create Filter.” This will open the filter window, where you can select the desired values to filter on. You can also create a custom filter by entering a specific value or range in the “Custom Filter” box at the bottom of the window. Once you have set up the filter, click “Apply” to apply the filter to your worksheet.

Creating Filters for Measures 

Tableau filters are used to limit the data that is displayed in a visualization. They can be used to focus on specific measures or to filter out irrelevant data. Examples of filters include date range, geographic region, product category, or customer segment.

When creating filters for measures in Tableau, it is important to consider the context of the data and what needs to be shown. For example, if you are looking at sales data, you may want to filter by time period, region, product category, or customer segment.

Once you have identified the appropriate filters, you can set up the filters in the “Filters” tab in Tableau. Here, you can choose the type of filter (numeric, date, string, etc.), the condition (equals, contains, greater than, etc.), and the value (number, text, date, etc.).

Tableau also has the ability to create calculated fields, which can be used to create more sophisticated filters. For example, a calculated field can be used to filter sales data by product category and customer segment.

By using filters, you can ensure that only the relevant data is displayed in the visualization, enabling you to create more meaningful insights.

Clearing Filters 

In Tableau, filters can be cleared by selecting the ‘Clear’ option from the dropdown menu on the right side of the filter. Alternatively, the ‘Clear All’ option can be used to clear all filters at once. Additionally, filters can be cleared by right-clicking the filter and selecting ‘Clear Filter’ from the context menu.

Tableau – Bar Chart 

A bar chart is a type of graph that can be used to visualize data. It is a rectangular chart that is used to compare different categories of data. The data is plotted on a vertical or horizontal axis, typically with bars representing the relative size of each category.

Bar charts are an effective way to compare different values across multiple categories. They are simple to create and can be used to quickly visualize data. They are often used to compare the relative sizes of different categories, such as sales figures for different products, or the number of people in different age groups.

Bar charts can also be used to compare data points across different time periods. This is especially useful when looking at the growth or decline of a particular metric over time.

Bar charts can be used to identify trends and patterns in data. They are also useful for identifying outliers, or data points that are outside of the general range of the data.

In general, bar charts are an effective way to visualize data and compare different values. They are simple to create and can be used to quickly identify patterns and trends in data.

Tableau – Line Chart 

A Line Chart is a graph type used to display the changes in a variable over a period of time. It is a powerful visualization tool used to represent the trends in data and compare different datasets. Line charts are generally used to show changes in values over a set of time intervals. It can be used to compare different categories or to compare the same category over a period of time.

Line charts are usually composed of two axes. The x-axis is used to represent the time periods, while the y-axis displays the values of the variable being studied. The values can be represented using a single line or multiple lines. A single line is used when comparing two datasets, while multiple lines are used to compare multiple datasets.

Line charts are often used in business to analyze the performance of a company over a period of time. They can also be used to visualize the percentage change in a variable or the trend in the data over a certain period. Line charts are also used in scientific research to compare different datasets or to measure the progress of a certain experiment.

Line charts can be created in Tableau, a data visualization software. Tableau provides a wide range of options to customize the chart, such as color, style and labels. It also allows users to easily create interactive charts with annotations, filters, and more. Line charts in Tableau can be used to quickly and effectively visualize data.

Tableau – Pie Chart 

A pie chart is a type of graph used to visually represent the relative proportions of different data points in a set. It is a circular chart divided into sections or “slices” that each represent a proportion of the whole. Pie charts are commonly used to show the percentages of a whole, such as a population broken down by gender or age group.

Pie charts are simple to create and interpret in Tableau. To create a pie chart, drag the desired dimension (e.g. gender or age group) to the “Rows” shelf and the measure (e.g. population size) to the “Columns” shelf. Then, click on the “Show Me” tab and select the pie chart icon. This will generate a pie chart with the proportions of the population size represented by each section.

To interpret the data, simply look at the labels and the relative size of each slice. The larger the slice, the greater the proportion of the population it represents. The labels indicate what the slices represent. For example, if the chart shows population by gender, then the labels will be “Male” and “Female”.

Overall, pie charts are an effective and easy way to represent proportions of data points in a set. They are simple to create and interpret in Tableau, making them a great choice for data visualization.

Tableau – Crosstab 

Tableau is a powerful data visualization and business intelligence tool used to analyze, visualize, and explore data. It is used to create dashboards and crosstabs. A crosstab is a table that summarizes data from multiple sources. It is often used to compare different categories of data.

Crosstabs in Tableau are used to display data in a tabular format. It allows users to compare and analyze data across multiple dimensions. It is an effective way to visualize the relationship between two or more data sets. For example, a crosstab could be used to compare sales figures by product and region. 

Crosstabs are created in Tableau by selecting the dimensions and measures to be included in the table. The dimensions are used to define the rows and columns of the table, and the measures are used to populate the table with data. Once the dimensions and measures have been selected, Tableau can automatically generate a crosstab.

Tableau crosstabs can be further customized with filters, parameters, and sorting options. Tableau also provides options for customizing the appearance of the table, such as font size, color, and formatting. The crosstab can then be saved as an image or a PDF for sharing and further analysis.

Tableau crosstabs are a great way to quickly summarize data and analyze relationships between multiple data sets. They are easy to create and customize, and they can be used to create compelling visuals that help users better understand their data.

Tableau – Scatter Plot

A scatter plot is a type of data visualization used to represent the relationship between two or more variables. Scatter plots are useful for understanding the distribution of data points and for identifying trends or patterns in the data. They are also useful for finding correlations between variables. Scatter plots can be created with various software packages, including Tableau, which is a business intelligence software used to create interactive data visualizations.

In Tableau, a scatter plot is created by adding two or more measures (numeric values) to the visualization pane. These measures are represented by circles on the plot, with each circle representing a single data point. The position of the points on the plot is determined by the values of the two measures. The x-axis represents the first measure, while the y-axis represents the second measure. Points on the plot can be colored or sized to represent additional data points or to add emphasis to particular points.

Tableau also allows users to add labels to the scatter plot, which can be used to identify particular points or to add additional context to the plot. Additionally, Tableau allows users to add a line to the scatter plot which can be used to represent a trend in the data or to highlight a particular relationship between the variables.

Scatter plots are a powerful data visualization tool that can be used to quickly identify trends and relationships in the data. Tableau makes it easy to create and customize scatter plots, making it a great tool for exploring and understanding data.

Tableau – Bubble Chart

Tableau is a popular data visualization software that allows users to explore and analyze data in a visual format. One of the most popular types of charts used in Tableau is the bubble chart. 

A bubble chart is a type of scatter plot that can be used to compare three variables at once. Each data point is represented by a “bubble”, which is a circle that has a size and color that represent different values. The size of the bubble is determined by the third variable, while the color is determined by the second variable.

Bubble charts are useful for comparisons between different categories of data. For example, you could use a bubble chart to compare the sales of different products or the performance of different teams. You can also use a bubble chart to view changes over time.

Bubble charts are also useful for spotting outliers in data. The size and color of the bubbles can help you identify unusual data points that may not be immediately obvious in traditional charts.

Tableau makes it easy to create bubble charts. All you need to do is select your data, choose the bubble chart from the visualization menu, and customize the size, color, and labels. You can also add filters and drill-down options to further refine your data analysis.

Tableau – Bullet Graph 

A bullet graph is a data visualization tool used to compare a given metric to a target value. It is a variation of a bar graph that displays one or more values against a single measure. Bullet graphs are used to quickly compare data points to predetermined goals or targets, and can be used to track progress over time. 

The bullet graph typically includes three components: a measure, a target, and a range. The measure is the main value of interest, and is typically represented by a bar, circle, or other shape. The target is the desired value or goal, and is usually represented by a line or marker. The range is the range of values that the measure can take on and is usually represented by a band or area.

Bullet graphs are helpful for quickly identifying if a value is more or less than the target. They are also useful for quickly comparing multiple values to a single target. They can be used in any situation where it is important to quickly assess the performance of a metric relative to a target. 

Bullet graphs are a great way to make data easier to understand, as they are visually appealing and can quickly showcase a value’s performance relative to its target. They are also an effective tool for communicating data to a wide range of audiences.

 Tableau – Box Plot

A box plot, also known as a box-and-whisker plot, is a type of graph used to display and compare set of numerical data. It is used to show the distribution of a data set, providing a visual representation of the five-number summary, which consists of the minimum, maximum, median, first quartile and third quartile. 

Box plots are useful for understanding the range of values in a data set. They are also used to compare multiple sets of data and to spot potential outliers. They are especially useful for comparing distributions of data with different spreads, such as when comparing data sets with different numbers of observations.

Box plots can be created in Tableau using the Show Me menu. To create a box plot, select the field to be plotted, and then select the Box Plot option. Tableau will then generate the box plot with the five-number summary and any outliers. Tableau also allows for the customization of the plot, such as changing the colors and the size of the boxes. 

Overall, box plots are a useful and easy-to-understand tool for visualizing data and comparing distributions of data. They are easy to create and customize in Tableau, making them a powerful tool for data exploration and analysis.

Tableau – Tree Map 

A Tree Map is a type of visualization tool that uses a hierarchical structure to represent data. It is typically used to visualize large amounts of data in a way that is easy to comprehend. Tree maps are often used to display hierarchical data, showing the relationship between parent and child nodes, as well as how values are distributed within the data set. Tree maps are also effective tools to identify patterns and trends that would be difficult to detect in other types of visualizations.

Tree maps are composed of a series of rectangles, each of which represents a data element. Each rectangle is scaled according to its relative value, so that larger values are represented by larger rectangles. This allows the viewer to quickly identify the largest elements in the data set. The rectangles can be color-coded to represent other aspects of the data, such as categories or groupings.

Tree maps are useful for summarizing large amounts of data and for uncovering relationships between data elements. They are also a helpful tool for identifying outliers in the data. Tree maps can be used in a variety of applications, including business intelligence, data mining, and visualization. Tableau is a popular software for creating tree maps. It provides a range of features for creating interactive tree maps, including the ability to add custom colors and shapes, as well as filtering and sorting options.

Tableau – Bump Chart 

A bump chart is a data visualization tool used to create a graphical comparison of entities over a period of time. It is a type of line chart that plots the relative position of entities. Instead of plotting the exact values of each entity, the chart plots the relative positions of each entity with respect to each other.

Bump charts are useful for analyzing changes in rankings over time. It is a great way to visualize a large amount of data and compare multiple entities at the same time. By plotting the positions of the entities, you can quickly identify trends in the data.

Bump charts can be used to analyze a variety of data types. Common use cases include analyzing changes in rankings of products or services, analyzing changes in stock prices, or analyzing changes in rankings of countries or cities. Bump charts can be used to identify patterns or anomalies in the data.

Bump charts are created using a Tableau software. Tableau is a popular data visualization tool that allows users to quickly create interactive and visually appealing data visualizations. Tableau offers a wide range of features, including a drag and drop interface, which makes it easy to create bump charts.

Bump charts can be used to quickly identify trends and outliers in the data. It is a great way to compare multiple entities over time and identify correlations between them. Bump charts can also be used to compare entities over different time periods. Tableau makes it easy to create bump charts, allowing users to quickly and easily access and analyze large amounts of data.

Tableau – Gantt Chart 

A Gantt chart, named after its creator Henry Gantt, is a type of bar chart used in project management to visualize tasks and activities over time. It is a type of bar chart that shows the start and finish dates of each task within a project, as well as the dependencies between tasks. The chart is divided into a number of horizontal bars, each one representing a task or activity, with a length that corresponds to its estimated duration. A Gantt chart can also be used to show progress, resources, and other information related to the project.

Gantt charts offer a straightforward way of visualizing the project plan, and can help project managers to identify tasks that are behind schedule, as well as to recognize potential overlaps or conflicts. It is also helpful for team members to understand their roles and responsibilities within the project, as well as to identify any potential resource constraints. Gantt charts can also be used to track budgets and resources, as well as estimate the total project cost.

Gantt charts are simple to create and use, and can be used to quickly and easily communicate project plans to stakeholders. They can be created in a number of different software programs, such as Microsoft Project and Tableau, and can be shared with others in the form of PDFs or other digital formats.

Gantt charts are an essential tool for anyone involved in project management, as they provide a simple way of visualizing project plans, tracking progress, and identifying potential issues or conflicts. They are a powerful tool for communication and collaboration, and can be used to ensure that projects are completed on time and within budget.

Tableau – Histogram 

Tableau is a powerful data visualization tool that allows users to easily create visualizations such as histograms. Histograms are a type of bar graph that show the frequency of data points within a range of values. Histograms are useful for quickly displaying how often values within a dataset occur.

Tableau makes it easy to create a histogram. When creating a histogram in Tableau, the first step is to select the data that will be used. Tableau allows users to select data from multiple data sources, including text files, databases, and spreadsheets. After selecting the data, users can then select the measures and dimensions they want to use for the histogram.

Once the data is selected, Tableau will automatically create a histogram with the data points. The x-axis of the histogram will display the range of values, and the y-axis will display the frequency of the values. Users can customize the histogram by changing the label names, color scheme, and other settings.

Tableau also provides several options for analyzing the histogram. For example, users can calculate the mean, median, and mode of the data points within the histogram. This makes it easy to quickly determine the central tendency of the data points.

Overall, Tableau provides an easy-to-use platform for creating and analyzing histograms. It makes it easy to quickly visualize data and identify patterns within the data.

Tableau – Motion Charts 

Tableau Motion Charts are interactive data visualizations which allow users to explore their data over time. The charts are designed to be intuitive and easy to use, allowing users to quickly identify trends in their data. A motion chart is created by selecting a measure and two dimensions. The measure is plotted on the x-axis and the two dimensions are plotted on the y-axis and color-coded. The motion chart then shows the evolution of the measure over time, with each point representing a different time interval. The motion chart can be further customized by adding filters, such as different time periods or specific categories.

Motion charts are a great way to explore trends in data over time. They can help users identify outliers, correlations and other patterns which can be used to make decisions or identify areas for improvement. Motion charts can also be used to compare different data points over time and identify relationships between them. Additionally, motion charts can be used to forecast future trends, allowing users to make predictions about the future.

Overall, Tableau Motion Charts are an effective data visualization tool which helps users to quickly identify trends in their data and make decisions based on those trends. They are easy to use and offer a great way to explore data over time.

Tableau – Waterfall Charts 

Tableau Waterfall Charts are used to visualize the cumulative effect of sequentially introduced positive or negative values. It is commonly used to explain the intricacies of financial operations such as investments, expenditures, and profits.

Tableau Waterfall Charts are also known as bridge charts or flying bricks charts. The chart starts with a base value and then each subsequent bar is color-coded to represent the positive (green) or negative (red) value added to the overall sum. A cumulative total line is also included to show the total amount at each step.

Tableau Waterfall Charts are useful for understanding the individual contributions of different factors to an overall result. They can be used to identify the sources of growth for a business or to identify areas in need of improvement. They are also an effective way to visualize the cumulative contributions of different departments or employees in a team or organization.

Tableau Waterfall Charts are easily customizable and can be used to emphasize particular points or trends. For example, a chart can be filtered to display positive and negative values separately, or to show changes over time. Additionally, the chart can be formatted to display the data as individual bars or as a continuous line.

Tableau Waterfall Charts are a powerful tool for businesses, and they can be used to make informed decisions and to help stakeholders understand complex data.

Tableau – Dashboard

Tableau is a powerful business intelligence (BI) and analytics platform that enables organizations to create interactive, visual dashboards. Tableau dashboards provide real-time access to data, helping decision-makers quickly spot trends and make informed decisions. Tableau dashboards are designed to be intuitive and easy to use, allowing users to quickly explore data, identify insights, and share results with others. Tableau dashboards are an invaluable tool for businesses of all sizes, giving them the ability to quickly analyze and interpret data to inform decisions.

Tableau – Formatting

Tableau provides several formatting options for visualizing data. Formatting can be used to adjust the appearance of a chart or graph, such as changing the color, size, or shape of the visual elements. Additionally, formatting can be used to alter the way data is displayed, such as changing the number of decimal places shown in a chart. Tableau also offers an array of formatting options related to labels, tooltips, and annotations. All of these formatting options can be used to help create compelling visuals that aid in data analysis and storytelling.

Tableau – Forecasting

Tableau is a data visualization and analytics platform that can be used to create powerful data visualizations and reports. It is also a powerful forecasting tool that can be used to create projections of future performance. Tableau combines data from multiple data sources, including databases, spreadsheets, and text files, to create interactive visualizations and reports. Tableau’s forecasting capabilities include trend analysis, time series forecasting, and predictive analytics. With Tableau, users can create interactive visualizations and reports to more accurately forecast future performance. Additionally, Tableau’s forecasting tools allow users to quickly identify trends and outliers in their data and make more informed decisions about the future.

Creating a Forecasting 

1. Start Tableau and connect to the data source.

2. In the Data window, select the measures and dimensions you want to use in your forecast.

3. Drag the measures and dimensions to the Columns and Rows shelves of the view.

4. Right-click on a measure and select Forecast.

5. Choose the desired settings for the forecast, including the forecast period, confidence interval, and seasonality.

6. Select the desired forecasting options, such as a smoothing factor or auto-regressive parameters.

7. Click OK to generate the forecast.

8. Visualize the forecast by adding additional measures or dimensions to the view, or by changing the chart type.

9. Save the view for future reference.

Tableau – Trend Lines

Tableau is a powerful data visualization tool that allows users to easily create and analyze complex data sets. One of its most powerful features is its ability to create trend lines. Trend lines help to identify the direction of a data set and can be used to identify trends, correlations, and outliers. Trend lines can be created in Tableau by selecting the data points on a chart, then clicking the “Trend Line” button. The user can then adjust the trend line as desired, such as by changing the type of trend line or adding a label. Trend lines can also be used to detect anomalies in the data. For example, if the trend line is significantly different from the data points, then this could indicate that something unusual is taking place. Trend lines can also be used to analyze the relationship between two variables. For example, if the trend line indicates that one variable is increasing while the other is decreasing, then this could indicate a negative correlation between the two variables.

Creating a Trend Line 

Tableau is a data visualization platform that allows users to create a wide variety of visuals, including trend lines. To create a trend line in Tableau, follow these steps:

1. Open Tableau and connect to your data.

2. Drag the relevant measure or dimension onto the Rows shelf.

3. Drag the same measure or dimension onto the Columns shelf, and select ‘Line’ as the mark type.

4. Right-click on the measure or dimension in the Rows shelf and select ‘Trend Lines’.

5. Select the type of trend line you want to generate.

6. Customize the trend line (if needed) by selecting the ‘Trend Line’ tab in the ‘Marks’ card.

7. Preview the trend line in the view.

8. Publish the view to share it with others.