Excel Power Pivot is an add-in that allows you to analyze large amounts of data quickly and easily. It is an advanced form of data analysis and modeling in Excel that allows you to combine data from multiple sources and create powerful calculations and reports. With Power Pivot, you can create relationships between multiple tables of data, perform advanced calculations and create reports.
To get started with Power Pivot, open up the Power Pivot window. This window can be found under the Data tab in Excel. When the Power Pivot window appears, you will see two tabs: Data and Model. The Data tab is where you will load your data and create relationships between tables. The Model tab is where you will create calculations and reports.
Once you have your data loaded in the Data tab, you can start creating relationships between the tables. To do this, click on the table you want to create the relationship with and select “Create Relationship” from the ribbon. Once you have created the relationship, you can now start setting up the calculations.
To do this, select the columns you want to use in the calculation and then click the “Calculations” button. Here you can create formulas to calculate various values, such as averages, sums, products, and more. Once you have created your calculations, you can then create reports by dragging and dropping the fields you want to display in the report.
Power Pivot is a powerful tool for analyzing large amounts of data quickly and easily. With its powerful features and easy-to-use interface, you can create complex calculations and reports in no time.
Audience
The audience for an Excel Power Pivot tutorial would include anyone who wants to learn how to use the Power Pivot feature in Excel. This includes data analysts, business analysts, financial analysts, accountants, project managers, and other professionals who work with data and use Excel for their work. The tutorial would also be useful to students who are studying data science or analytics.
Prerequisites
To get the most out of this Excel Power Pivot tutorial, it is recommended that you have a basic understanding of the following topics:
• Microsoft Excel
• Pivot tables
• Data Analysis
• Database Concepts
Excel Power Pivot – Overview
Excel Power Pivot is a feature of Microsoft Excel that allows users to ingest, manipulate, and analyze large amounts of data from multiple sources. Power Pivot is an add-in for Excel that enables users to import large amounts of data from multiple sources and then create data models and perform powerful data analysis. It allows users to create dashboards, automate data manipulation, and use complex calculations. Power Pivot also offers features such as data modeling, data exploration, and interactive reporting. Power Pivot allows users to create sophisticated data models with relationships, hierarchies, and calculations, enabling users to gain even greater insights into their data. Power Pivot can be used to build business intelligence (BI) solutions, including dashboards, scorecards, and predictive models. Power Pivot can also be used to to integrate data from multiple sources, allowing users to build comprehensive data models and reports.
Power Pivot Features
Power Pivot is an Excel add-in that enables users to import, manipulate, and analyze large amounts of data from multiple sources. It is capable of performing powerful data analysis on millions of rows of data, and can be used to build complex data models. Power Pivot also provides advanced analytics such as data mining and forecasting. Some of the key features of Power Pivot include:
– Ability to connect to multiple data sources, such as SQL Server, Access, Oracle, and text files.
– Automatically creates relationships between data sources.
– Ability to create calculated columns and measures.
– Automatically generates powerful, dynamic PivotTables.
– Ability to create interactive dashboards using Power View.
– Enables users to build sophisticated analytical models.
– Ability to create forecasts and data mining models.
– Supports real-time data analysis.
– Compatible with Windows and Office 365.
Power Pivot Data from Various Sources
Power Pivot is a powerful data analysis tool that can be used to combine and analyze data from multiple sources. With Power Pivot, you can quickly and easily combine data from multiple sources, such as Excel spreadsheets, Access databases, SQL Server databases, text files, and even web-based data sources. Once the data is combined, you can use Power Pivot to create reports, charts, and graphs from the data. Additionally, you can use advanced data modeling techniques to analyze the data and uncover valuable insights. Power Pivot is an invaluable tool for anyone looking to gain deeper insights from their data and make better decisions.
Power Pivot Data Model
Power Pivot data models are a type of data model that enables users to create and manipulate large amounts of data in a powerful, interactive way. Power Pivot models enable users to quickly analyse large amounts of data and create analytical reports, dashboards, and other forms of visualisations. They are typically used in business intelligence applications, but can also be used for other analytical tasks. Power Pivot models are built with the Microsoft Excel Power Pivot add-in, which allows users to connect to various data sources and create relationships between them. Power Pivot also enables users to easily manipulate and aggregate data, and to create calculated columns and measures. In addition, Power Pivot models enable users to create hierarchies and drill-down capabilities, allowing for better exploration and understanding of the data.
Managing Data Model and Relationships
Data models are used to define and analyze the data needed for an organization, and the relationships between the different data elements. Data models are used to represent the data elements and the relationships between them in a logical way. Relationships between data elements can be defined by their attributes, such as the type of data, the size of the data, and the relationships between the data elements. Relationships can also be defined by the data model itself, such as the relationship between a customer and a product.
The data model also defines the rules for how data is stored and accessed. Data models help to ensure that the data is stored in a consistent way, so that it can be accessed and used easily and correctly. Data models also ensure that data is organized correctly, so that it can be easily searched and analyzed.
Data models are important for managing data and relationships in an organization. They help to ensure that data is stored in a consistent format, and that the data can be easily accessed and used. They also help to ensure that data is organized in a way that is easy to understand and analyze. Data models help to ensure that data is organized in a way that is consistent and efficient, so that it can be used to make better decisions and improve business operations.
Creating Power Pivot Tables and Power Pivot Charts
Power Pivot tables and charts are a powerful tool for data analysis in Microsoft Excel. They allow users to quickly and easily analyze large amounts of data and create interactive and dynamic reports. Power Pivot tables and charts can be used to visualize trends, compare data sets, and identify correlations between different pieces of data.
To create a Power Pivot table, you first need to create a data model. This is done by selecting the data from the worksheet and adding it to the data model. Once this is done, the data will appear in the Power Pivot window. You can then add any calculations, measures, or relationships that you want to include in the model.
Once the data model is created, you can create a Power Pivot table or chart by dragging and dropping fields from the Power Pivot window onto the worksheet. The Power Pivot table or chart can then be modified by changing the data fields, sorting, filtering, and adding conditional formatting.
To create a Power Pivot chart, you will need to select the fields from the Power Pivot window that you want to include in the chart. You can then customize the chart by changing the chart type, adding labels, and changing the chart color.
Power Pivot tables and charts are a great way to explore data and create dynamic and interactive reports. They are also a great tool for quickly and easily analyzing large amounts of data.
DAX Basics
DAX stands for Data Analysis Expressions, and it is a formula language used in Microsoft Excel and Power BI to perform data analysis. DAX is used to calculate and manipulate data, create calculated columns and measures, and build dynamic hierarchies and relationships within the data. DAX formulas can be used to query data from a variety of data sources, such as Power BI, SQL databases, and Excel sources. DAX is also used to create relationships between data sources and to create calculated columns and measures. It is important to understand the basics of DAX in order to effectively utilize the language for data analysis tasks.
Exploring and Reporting Power Pivot Data
Power Pivot is a data analysis tool from Microsoft that allows users to quickly and easily analyze large amounts of data from multiple sources. It provides powerful features such as the ability to combine data from multiple sources, create complex calculations and relationships between data, and generate sophisticated reports. Power Pivot is an ideal tool for business intelligence and data analysis projects.
The first step in exploring and reporting Power Pivot data is to create a data model. This is done by connecting to data sources and importing the data into the Power Pivot window. This can be done by using the Get Data feature or by using the Power Query Builder. Once the data is imported, it can be organized into tables, columns, and relationships. This helps to create a logical structure to the data that makes it easier to analyze and report on.
Once the data model is created, the next step is to create meaningful calculations and relationships between the data. This can be done using the DAX (Data Analysis Expressions) language. DAX is a powerful language for creating calculations and relationships between data. It is also used to create measures, which are calculations that can be used to aggregate data across multiple tables.
Once the data model is complete, it can be used to generate reports. Power Pivot has built-in reporting tools that allow users to create simple tables and charts. These tools are easy to use and can be customized to display the data in the way that best suits the user’s needs. Additionally, Power Pivot has the ability to connect to external data sources such as Microsoft Excel, SQL Server, and other databases. This allows users to combine data from multiple sources and create powerful reports that can be used to gain insights into the data.
Overall, Power Pivot is a powerful and versatile tool for exploring and reporting data. It provides powerful features and allows users to quickly and easily analyze large amounts of data from multiple sources. It can be used to create meaningful calculations and relationships between data and generate sophisticated reports. Power Pivot is an ideal tool for business intelligence and data analysis projects.
Excel Power Pivot – Installing
Excel Power Pivot is a Microsoft Excel add-in that enables users to easily manipulate, analyze and visualize large amounts of data. It can be installed quickly and easily through Microsoft Office’s add-ins feature.
To install Excel Power Pivot in Excel, open a new workbook and select the “File” tab. Then, select “Options” and “Add-Ins”. At the bottom of the Add-Ins window, select “Manage: COM Add-ins” and click “Go…”. Check the box next to “Microsoft Power Pivot for Excel” and click “OK”. Once the installation is complete, you will be able to access Power Pivot and begin manipulating large amounts of data.
Power Pivot on the Ribbon
Power Pivot can be found on the ribbon in Microsoft Excel, located in the Data tab. It is an add-in that can be used to analyze and manipulate large datasets with powerful calculation and reporting capabilities. It can be used to analyze data from multiple sources, create dynamic relationships between tables, and perform advanced calculations and analysis.
Power Pivot Add-in
The Power Pivot add-in is an Excel add-in that enables users to create powerful data models from a variety of sources. It is used to analyze and report on massive amounts of data in a single spreadsheet. It can help users to quickly analyze large amounts of data, provide insights and make better decisions. Power Pivot is a powerful tool for data analysis and reporting, and can be used to quickly and easily create data models.
What is Power Pivot?
Power Pivot is an Excel add-in that enables users to import and manipulate large amounts of data from multiple sources. It allows users to create relationships between different data sets and create powerful data models for analysis. Power Pivot works with all versions of Excel, and can be used to create complex data analysis and reporting projects.
Why is Power Pivot a Strong Tool?
Power Pivot is a strong tool because it allows users to import and work with large amounts of data quickly and easily. It is a powerful tool that can be used to analyze data from multiple sources, create advanced calculations, and build visually appealing models. It also allows for the creation of complex relationships between data sets, as well as the ability to drill down into the data to extract insights. Finally, Power Pivot is an efficient tool that can be used to save time by automating certain tasks.
Power Features to Excel with Power Pivot
1. Data Modeling: Power Pivot allows users to create complex data models and relationships between tables. This allows for more efficient analysis, as it allows users to easily link related data together.
2. Automated Calculations: Power Pivot can automatically calculate sums, averages, and other statistical functions on data. This saves users from having to manually type out the formulas and makes it easier to get quick results.
3. Data Visualization: Power Pivot allows users to quickly create visuals such as charts, graphs, and maps. This makes it easy to quickly analyze data and gain insights.
4. User-Friendly Interface: Power Pivot has an intuitive user-interface that allows users to quickly and easily create data models, calculate functions, and visualize data.
5. Security: Power Pivot has built-in security features that allow users to restrict access to specific data based on user roles. This ensures that only authorized users can access sensitive data.
Uses of Power Pivot
1. Data Analysis: Power Pivot enables users to quickly analyze large amounts of data from multiple sources. It can be used to generate insights and make data-driven decisions.
2. Data Visualization: Power Pivot can be used to create visually appealing charts, graphs, and other visuals to help simplify complex data.
3. Data Modeling: Power Pivot can be used to create complex data models, which can then be used to better understand data relationships and patterns.
4. Reporting: Power Pivot can be used to create reports to help organizations stay informed about their data.
5. Dashboards: Power Pivot can be used to create interactive dashboards to help users better understand their data.
Data Modelling with Power Pivot
Power Pivot is a Microsoft Excel add-in that enables users to create data models with large amounts of data, enabling them to create sophisticated data analysis and reporting. It allows users to quickly and efficiently model the data in their workbooks and then use the data to create powerful visualizations and reports. Power Pivot also allows users to create interactive dashboards and perform data analysis using advanced functions like Power Query, Power Pivot, and DAX. It can be used to create data models from multiple sources, including relational databases, flat files, web services, and other sources. Power Pivot allows users to save time and effort by creating data models from multiple sources and then combining them into a single, unified model. The result is an easy-to-use, intuitive, and powerful tool for data analysis.
Business Intelligence with Power Pivot
Power Pivot is Microsoft Excel’s data modeling and analysis tool. It enables users to analyze large amounts of data from multiple sources quickly, build powerful data models and create interactive reports. With Power Pivot, users can create powerful data models that allow them to explore and analyze data in ways that weren’t possible before. It can also be used to create dashboards and visualizations that make data easier to understand. Power Pivot is an excellent tool for Business Intelligence, allowing users to quickly analyze large datasets and draw meaningful insights.
Excel Power Pivot – Features
1. Data Modeling
Excel Power Pivot enables users to create custom data models from various data sources. It provides features such as automatic data refresh, data relationships, and data filtering and grouping.
2. Advanced Calculations
Power Pivot enables users to create powerful calculations using DAX (Data Analysis Expressions), a powerful expression language.
3. Data Visualization
Power Pivot supports data visualization as it allows users to create interactive charts, reports, and dashboards.
4. Data Security
With Power Pivot, users can manage and control access to data sources and data models, ensuring that only authorized users can access sensitive data.
5. Scalability
Power Pivot allows users to create and manage large data sets, allowing for better scalability and performance.
Excel Power Pivot – Loading Data
Excel Power Pivot makes loading data into the Power Pivot Data Model easier than ever. Users can load data from multiple sources, including Excel workbooks, external databases, and online data sources. Data can be loaded into the data model directly from the source, or it can be imported into an Excel worksheet and then loaded into the data model from there.
Data can be loaded into the Power Pivot Data Model from the Power Pivot Window, which can be opened by going to the Data tab in Excel and clicking on the Power Pivot button. From the Power Pivot window, users can select the data source, choose which tables to add, and then click on the load button to import the data.
In addition to loading data, users can also use Power Pivot to add calculations, such as sums, averages, and count values, to the data model. This can be done using DAX (Data Analysis Expressions) formulas, which are similar to Excel formulas. Once the data is loaded and the calculations are added, users can then explore and analyze the data using Excel’s pivot tables, charts, and slicers.
Data Sources Supported by Power Pivot
Power Pivot supports data from the following sources:
• Excel workbooks
• Text files (CSV, TSV, etc.)
• Relational databases (SQL Server, Oracle, Access, etc.)
• Online services such as Azure, Salesforce, Facebook, Zendesk, etc.
• Power Query (M language)
• Hadoop (Hive, HDFS, etc.)
• OData feeds
• Analysis Services cubes
• Reports from other tools such as Tableau, QlikView, etc.
Loading Data Directly into PowerPivot
PowerPivot is a Microsoft Excel add-in that allows users to analyze large amounts of data. It can be used to analyze data from a variety of sources, including relational databases, text files, Excel spreadsheets, and other data sources. PowerPivot allows users to quickly and easily load data into the program and analyze it in a variety of ways. For example, users can create pivot tables, charts, and other visuals to uncover trends and insights in the data.
To load data directly into PowerPivot, users can connect to the data source and import the data into the program. This can be done by selecting the “Get Data” option from the PowerPivot ribbon and selecting the appropriate data source. The data can then be imported into the PowerPivot workbook, which is stored within the Excel file. Once the data is imported, users can begin to analyze and manipulate the data.
Table Import Wizard
The Table Import Wizard is a feature of Microsoft Excel that allows users to quickly and easily import data from other sources into an Excel spreadsheet. The wizard can be accessed by clicking the “Data” tab in the ribbon, then selecting “From Other Sources” and then “Table Import Wizard”. The wizard walks the user through a series of steps to specify the source and format of the data, and then to adjust any column settings or mapping. Once all the settings are chosen, the user can preview the data and then click the “Finish” button to import the data. The imported data will appear in the specified worksheet, ready to be manipulated and analyzed.
Opening Existing Connections in excel
1. Open Microsoft Excel.
2. Click the “Data” tab.
3. Click “Existing Connections” from the “Get External Data” group.
4. Select the connection you want to open.
5. Click “Open.”
6. Click “Properties” to edit the connection or click “Open” to view the data.
Creating Linked Tables
1. Select the data to be linked and create a Table by selecting the Insert tab.
2. Right-click in the Table and select Table Name to give the Table a meaningful name.
3. Copy the Table by selecting the Copy button on the Home tab of the Ribbon or by right-clicking the Table and selecting Copy.
4. Open the other workbook and Paste the Table using the Paste button on the Home tab of the Ribbon or by right-clicking the Table and selecting Paste.
5. Select the Paste Options button and select the Linked Table option.
6. Click OK in the Paste Link dialog box to create the linked Table.
Loading from Excel Files
Excel files can be loaded into Python using the pandas library. Pandas makes it easy to read in data from Excel sheets and also to write data frames back to Excel. This makes it an ideal choice for loading data from Excel files into Python.
Loading from Text Files
Text files are one of the most common ways to load data into a computer. They usually contain plain text and can be opened with any text editor. They can also be easily read and processed by programming languages such as Python.
To load data from a text file, you must first open the file and read the contents. Depending on the format of the text file, you may have to parse the data in order to make sense of it. Once the data is parsed, it can be stored in a data structure such as a list, dictionary, or array. From there, the data can be manipulated and used as needed.
Loading from the Clipboard in excel
1. Open a blank Excel worksheet.
2. Click on the “Home” tab.
3. Click the small arrow on the bottom right corner of the “Clipboard” group.
4. Select “Paste” from the menu.
5. Select the “From Clipboard” option.
6. Your data from the Clipboard will be pasted into the Excel worksheet.
Refreshing Data in Power Pivot
Data can be refreshed in Power Pivot by clicking the ‘Refresh All’ button in the ‘Home’ tab of the ribbon. This will refresh all the data in the model. Alternatively, data can be refreshed for a specific table by selecting the table, clicking the ‘Refresh’ button in the ‘Design’ tab of the ribbon and then selecting the ‘Table’ option from the drop down menu.
Excel Power Pivot – Data Modeling
Excel Power Pivot is an add-in to Microsoft Excel that is used to create data models. It allows users to create sophisticated data models and run complex calculations on their data. With Power Pivot, users can link together tables of data and then use that data in calculations and visualizations. Power Pivot can be used to create a data model which can be used to answer complex questions about the data. It can also be used to analyze and visualize data in a variety of ways. Power Pivot also has features for creating relationships between tables and for creating calculated columns.
Excel and Data Modeling
Excel and data modeling are closely related to one another because they both involve the use of data to analyze and interpret information. Excel is a spreadsheet program that is used to store, organize, and analyze data. Data modeling is the process of developing a model of a system or process to better understand its behavior and identify potential areas of improvement. Data models can be used to create visualizations that can help identify patterns and trends in data, as well as to optimize processes. By combining Excel and data modeling, users can leverage the power of both tools to gain insight into their data and make informed decisions.
Power Pivot and Data Modeling
Power Pivot is an Excel add-in that helps users create data models and analyze data. It offers a powerful and easy-to-use interface for creating data models. It is ideal for creating more complex data models and for working with large amounts of data. Power Pivot allows users to create relationships between different tables of data, create calculations, and use powerful analytical functions to analyze data. This can help identify patterns, trends, and valuable insights from data. Data modeling helps to structure data so that it can be easily understood. It is used to create a logical representation of the data, making it easier to understand and analyze. Power Pivot can be used to build data models more quickly, and also allows for more complex models and data analysis.
Creating a Data Model
1. Identify the entities in the data model:
– Customers
– Products
– Orders
– Order Details
2. Identify the relationships between the entities:
– Customers have many Orders
– Orders have many Order Details
– Products have many Order Details
– Order Details belong to one Order and one Product
Tables in Data Model
The tables in the data model depend on the type of data model. Common types of data models include relational, dimensional, and object-oriented. Examples of tables in a relational data model include customers, orders, products, and order items. Examples of tables in a dimensional data model include facts and dimensions. Examples of tables in an object-oriented data model include classes, objects, and methods.
Excel Tables and Data Tables
Excel tables and data tables are both types of tables that can be used to store and organize data. Excel tables are used in Microsoft Excel and are typically used to store and manipulate numerical data. Data tables are used to store and organize information that may include text, images, and numerical data. Data tables may be used in software applications and web pages.
Data View of Data Model
The data view of a data model in Excel is a visual representation of the data in the model. Typically, the data view will include columns for the various fields in the data model, rows for each record, and values corresponding to each record’s field. For example, a data model of customer orders will have columns for the customer name, order date, product type, and order quantity, and each row will contain the corresponding values for a particular customer order. The data view will provide an overview of the data in the model, allowing users to quickly identify patterns and anomalies in the data.
Relationships in Data Model
Relationships in a data model are the logical connections between different entities. These relationships can be one-to-one, one-to-many, or many-to-many. Relationships are important in data models because they help to organize data and provide an efficient way to access and manipulate data. They also allow for better data integrity, as each entity is related to another.
Excel Power Pivot – Managing Data Model
Excel Power Pivot is a powerful tool for managing data models in Microsoft Excel. It allows you to quickly and easily analyze large amounts of data and create sophisticated data models. Power Pivot allows you to create relationships between your data, add calculations and reports, and create interactive dashboards. Power Pivot also provides a way to integrate data from multiple sources, such as databases and external services. With Power Pivot, you can quickly transform and blend data from multiple sources, calculate advanced metrics, and create sophisticated reports and dashboards. Power Pivot can be used to create data models with millions of rows of data and can substantially improve performance and scalability.
Adding Excel Tables to Data Model with PivotTable
To add an Excel table to the data model with a PivotTable, first select the data in the table. Then, click Insert > PivotTable. In the Create PivotTable window, make sure the checkbox for Add This Data to the Data Model is checked. Click OK to create the PivotTable. The data from the Excel table will now be included in the data model.
Adding Excel Tables from a Different Workbook to Data Model
1. Open the source workbook containing the Excel table you want to add to the data model.
2. Select the table you want to add to the data model.
3. Click on the “Data” tab from the ribbon and select the “From Table/Range” option.
4. Click on the “Power Pivot” tab from the ribbon, then select the “Add to Data Model” option.
5. Your table will be added to the data model in the same workbook.
Adding Excel Tables to Data Model from the PowerPivot Ribbon
1. Open the Excel workbook that contains the Data Model.
2. Click the PowerPivot tab.
3. In the PowerPivot window, click the Design tab.
4. Click the Table Import Wizard icon on the ribbon.
5. Select the table or tables you want to import, then click Next.
6. Select the columns you want to include in the table, then click Finish.
7. The imported table will be added to the Data Model.
Creating Relationships from Data View
Relationships from data can be created by using data analytics such as data mining, machine learning and natural language processing. These tools allow us to uncover meaningful relationships between different data points. For example, data mining can be used to analyze customer purchase history to identify purchasing patterns and correlations between different products. Machine learning can be used to uncover relationships between different types of data, such as weather patterns and crop yields. Natural language processing can be used to understand the sentiment of customer reviews, to uncover relationships between customer sentiment and product sales. By leveraging these different data analytic techniques, businesses can create meaningful relationships from data and use them to inform decision making.
Creating Relationships from Diagram View
1. One-to-One Relationship: Teacher and Student.
2. One-to-Many Relationship: Teacher and Classes.
3. Many-to-Many Relationship: Students and Classes.
Managing Relationships
Managing relationships in a data model is critical to ensure the data is organized, accurate and secure. Relational databases are often used to store data, and the relationships between the tables and fields are managed through normalization. This involves breaking down the data into smaller, more manageable chunks and organizing it in a logical, hierarchical way. This allows for greater flexibility in querying and reporting, as well as ensuring data integrity.
Relationships can be managed using foreign keys, primary keys, and indexing. Foreign keys are used to link two tables together, while primary keys are used to uniquely identify a row in a table. Indexing is used to speed up searches, and ensure data is consistent. Additionally, data models can be maintained through the use of triggers, which are automated processes that are triggered when certain conditions are met.
Data models can also be enhanced through the use of data modeling tools. These tools allow users to visualize the relationships between the data, as well as help with the design and development of the model. Additionally, data modeling tools can help users create and manage complex data models with ease.
Refreshing Power Pivot Data
Refreshing Power Pivot data is a relatively straightforward process.
1. Select the Power Pivot tab in Excel, then click the “Manage” button in the ribbon.
2. On the Power Pivot window, select the “Design” tab, then click “Refresh All”. This will refresh all the data within the Power Pivot.
3. If you need to refresh only specific data, select the specific table and click “Refresh” in the ribbon.
4. You can also select the “Refresh All Connections” option to refresh all external data sources connected to the workbook.
Excel Power PivotTable – Creation
1. Open Microsoft Excel.
2. Go to the Insert tab and select “PivotTable” from the ribbon.
3. Choose where to create the PivotTable. Select either a new worksheet or an existing worksheet.
4. Select the data source. You can choose from the list of data sources or select the range of cells where your data is stored.
5. Select the columns you want to include in the PivotTable.
6. Select the type of calculation you want Excel to use to create the PivotTable.
7. Click “OK”.
8. The PivotTable Field List will appear on the left side of the worksheet. Drag and drop the fields from the list to the PivotTable.
9. To analyze your data, you can add filters, sort data, and create calculated fields.
10. Click “Refresh” to update the PivotTable when the data is changed.
Creating a Power PivotTable
1. Open the Excel file containing the data you wish to analyze in a Power PivotTable.
2. Click the Power Pivot tab on the ribbon.
3. Click Manage.
4. Click the Home tab.
5. Click the From Table button on the ribbon.
6. Select the data you want to analyze from the table and click OK.
7. Go to the Home tab again.
8. Click the PivotTable button on the ribbon.
9. Select the Power PivotTable option from the drop-down menu.
10. Select the data you want to include in your Power PivotTable and click OK.
11. Customize the layout and design of your Power PivotTable as desired.
12. Once you are finished, click the Close button to save your Power PivotTable.
Power PivotTable Fields
Power PivotTable Fields are dynamic fields that allow users to quickly analyze data by dragging and dropping fields into the table. These fields allow users to quickly identify trends, calculate sums and averages, and compare data across different categories. Power PivotTable Fields also allow users to quickly modify the data by adding or removing fields, as well as filtering and sorting the data.
Excel Power Pivot – Basics of DAX
Excel Power Pivot is a powerful tool that allows you to manipulate, analyze and report on large datasets. With the help of Power Pivot, you can create data models and use DAX (Data Analysis Expressions) to create calculations and analyze data.
DAX is a formula language used to work with Power Pivot. It is similar to the formula language used in Excel, but it has more powerful functions and capabilities. DAX is used to create calculated columns and measures.
Calculated columns are like calculated fields in Excel. They are used to add new data to your data model. Measures are used to perform operations on data that is already in your data model.
DAX includes functions for basic calculations, such as SUM, AVERAGE and COUNT, as well as more complex calculations, such as RANK, TOPN and DISTINCTCOUNT. There are also functions for filtering data, such as FILTER, CALCULATETABLE and RELATEDTABLE.
DAX also includes many time intelligence functions that you can use to perform calculations over different time periods. For example, you can use the DATESINPERIOD function to calculate the sum of sales for the last 12 months.
In addition, DAX includes statistical functions, such as CORREL and LINEST, as well as many other functions. With the help of DAX, you can create complex calculations and analyze data in ways that are not possible with Excel alone.
Extending the Data Model using Calculated Columns
Extending the data model with calculated columns allows users to quickly access information that would otherwise require more complex calculations. For example, a calculated column could be used to calculate the difference between two other columns, such as the difference between the opening and closing stock prices of a company. This could be useful to quickly identify how much the stock has moved over a certain period of time. Other calculated columns could be used to calculate the average of another set of columns, or to calculate the total of a set of columns. Calculated columns can make it easier for users to quickly identify important data points and to quickly access insights from a data set.
Excel Power Pivot – Exploring Data
Excel Power Pivot is a powerful data analysis tool that allows users to create and manage powerful data models and perform complex calculations. With Power Pivot, users can explore data from multiple sources, analyze data more quickly and accurately, and create powerful insights. Power Pivot can be used to analyze data from multiple sources, including databases, spreadsheets, and text files. It can also be used to create powerful data models that can be used for data analysis and visualization. Power Pivot allows users to create and manage powerful data models, perform complex calculations, and analyze data from multiple sources. Power Pivot also provides users with powerful data analysis tools such as pivot tables, charts, and graphs. Power Pivot can also be used to create powerful dashboards that allow users to quickly and easily visualize their data.
Loading Data from Access Database
The data can be loaded from an Access Database using a library called pyodbc. pyodbc is an open source Python module that provides access to ODBC databases. It is typically used to connect to Microsoft Access databases.
First, the pyodbc library must be installed. This can be done using the pip installer:
pip install pyodbc
Once pyodbc is installed, the data can be loaded by creating a connection to the database and then using the execute() function to run a SQL query to retrieve the desired data.
For example, the following code snippet creates a connection to an Access database and then retrieves all the records from a table called “Customers”:
import pyodbc
# Create connection to Access database
conn = pyodbc.connect(‘Driver={Microsoft Access Driver (*.mdb, *.accdb)};DBQ=C:\\myDatabase.accdb;’)
# Create a cursor
cursor = conn.cursor()
# Execute a SQL query
cursor.execute(‘SELECT * FROM Customers’)
# Fetch all the records
results = cursor.fetchall()
# Close the connection
conn.close()
Creating a PivotTable from the Data Model
In order to create a PivotTable from the Data Model, the user will first need to select the desired data set. This can be done by selecting the desired tables or fields from the Power Pivot window. Once the desired data is selected, the user can then click the “PivotTable” button in the ribbon bar. This will open the “Create PivotTable” window. Here, the user can select the desired fields to be included in the PivotTable and choose the desired layout. Once the fields are selected, the user can click the “OK” button to create the PivotTable.
Exploring Data with PivotTable
A PivotTable is a powerful tool for exploring and analyzing data in a spreadsheet. It allows you to quickly summarize and reorganize large amounts of data in a visually appealing and easy to understand format. With a PivotTable, you can quickly identify patterns in your data, as well as easily compare and contrast different values. You can also use a PivotTable to create reports and charts that are easy to share with others. PivotTables are a great way to explore data and gain insights that can be used to inform decisions and take action.
Summarizing Data from Different Sources in Power Pivot
Power Pivot can be used to summarize data from different sources. This can be done by importing the data from different sources into Power Pivot, creating relationships between the tables, and using PivotTables and/or DAX formulas to analyze the data. Power Pivot can also be used to create calculated columns and measures, which can be used to analyze and summarize the data further. Additionally, Power Pivot can be used to create visualizations, such as charts and graphs, to better understand the data.
Extending the Data Model using Calculated Columns
Calculated columns are columns that are not stored in the database but are calculated by a formula based on existing data. They are useful for deriving values from existing data to display in a view or to use in a query. For example, a calculated column could be used to calculate the total cost of a product based on its unit cost and quantity. This can be useful for quickly calculating values at a glance, or for quickly filtering or sorting data. Calculated columns can also be used to derive values from other calculated columns, such as averages, or to combine values from different columns into one column.
Creating a Relationship Using Calculated Columns
A calculated column can be used to create a relationship between two tables. For example, a calculated column can be used to calculate the total cost of an item based on its price and quantity. This total cost can then be used to create a relationship between the two tables, linking the item’s price and quantity to its total cost. The calculated column can also be used to calculate other values, such as discounts and taxes, that can be used to create relationships between tables.
Excel Power Pivot – Flattened data
Excel Power Pivot can be used to take data from multiple sources and flatten it into a single table. This is done by creating relationships between tables and then combining the data into a single table. This can be very useful for analysis, as it allows you to quickly and easily access information from multiple data sources. Additionally, it can help reduce the amount of manual manipulation needed to analyze data from multiple sources, as the data has already been combined into a single table.
Creating a PivotTable
1. Open the spreadsheet containing the data you want to analyze.
2. Select the data you want to include in the PivotTable.
3. Go to the Insert tab and click on the “PivotTable” button.
4. On the Create PivotTable dialog box, select where you want to place the PivotTable.
5. Select the data you want to include in the PivotTable.
6. Click “OK” to create the PivotTable.
7. On the PivotTable Field List, drag and drop the fields you want to use in the PivotTable.
8. In the “Values” area, select the mathematical operation you want to perform on the data.
9. Use the PivotTable to analyze the data.
Creating a Flattened PivotTable
1. Open the data set you want to analyze in Excel.
2. Select the entire range of cells that contains the data.
3. Go to the Insert tab, click on PivotTable, and select the Flattened PivotTable option.
4. Select the columns you want to use in your PivotTable.
5. Click OK and the flattened PivotTable will appear on your worksheet.
6. Drag and drop the columns you selected into the Row Labels and Values areas to customize the PivotTable.
7. Click on the Sum of Values field and select Value Field Settings.
8. Select the type of calculation you would like to use (e.g. Average, Sum, Count, etc.).
9. Click OK and your flattened PivotTable will be ready to analyze.
Exploring Data in Flattened PivotTable
When exploring data in a flattened PivotTable, it is important to analyze the data in terms of trends and patterns. To do this, one can look for relationships between different data points, such as the correlation between sales and customer ratings, or the relationship between profit margin and expenses. Additionally, one can look for outliers in the data, as well as any unexpected changes or trends. Additionally, one can look for any seasonality or cyclicality in the data and use this to aid in decision making. Finally, one can use the data to identify any areas of improvement, such as areas where customer satisfaction is low or areas where expenses are high.
Excel Power Pivot Charts – Creation
Excel Power Pivot charts are created through the use of the Power Pivot add-in. This add-in allows the user to create pivot tables and charts from multiple sources of data. To create a chart, the user must first select the data to be used in the chart, then choose the type of chart he or she wishes to create. Once the data has been selected, the user can manipulate it to create a custom chart. The Power Pivot add-in also enables the user to add calculated fields and custom columns to the data set. This allows the user to further customize their chart.
Creating a PivotChart
1. Select the data you would like to include in the PivotChart.
2. Click the Insert tab and select PivotChart from the Charts group.
3. In the Insert Chart dialogue box, select the desired chart type, such as column, line, area, or pie.
4. Click OK to open the PivotChart Fields pane.
5. Drag and drop the desired fields from the list on the left side of the pane to the Axis, Values, or Legend fields on the right side.
6. Click the Analyze tab and select any desired options to further customize the chart.
7. Click the Design tab to select a different chart style or to add a chart title, legend, or other elements to the chart.
8. Click the Layout tab to adjust the size and positioning of the chart and its elements.
9. Click the Filter tab to add a filter to the chart.
10. When finished, click the View tab to view the final chart.
PivotChart Fields List
1. Data: This field allows users to select the data to be used in the chart.
2. Axis (Categories): This field allows users to set up the categories that appear along the x-axis of the chart.
3. Legend (Series): This field allows users to set up the series that appear along the y-axis of the chart.
4. Values: This field allows users to select the values that will be used to populate the chart.
5. Filter: This field allows users to filter the data used in the chart.
6. Report Filter: This field allows users to further filter the data used in the chart.
7. Columns: This field allows users to set up the columns that appear on the chart.
8. Rows: This field allows users to set up the rows that appear on the chart.
9. Chart Type: This field allows users to choose the type of chart to be used.
10. Chart Options: This field allows users to customize the chart by changing the chart type, legend position, labels, and more.
Slicers in PivotChart
Slicers are an interactive tool used to filter data in a PivotChart. They allow users to quickly and easily filter the data in a PivotChart by selecting a specific value or range of values. Slicers can be used to filter data based on any of the fields in the PivotChart, such as product category, region, or date range. Slicers can also be used to quickly compare different data sets within the same chart, such as sales from different regions or products over a specific time period.
PivotChart Tools Design
PivotChart Tools Design is a set of tools that allow users to create interactive and visual presentations using data from multiple sources. The tools allow users to quickly build data-driven presentations that can be shared with colleagues, clients, or other stakeholders. The tools are designed to help users create visually appealing presentations with a minimum amount of effort and time. The tools include a variety of features, including the ability to customize chart types, add labels and annotations, and create custom filters. Additionally, users can save and share their presentations with others.
Table and Chart Combinations
Table and chart combinations are used to present data in an organized and visual way. Tables can provide a detailed overview of the data, while charts can provide a graphical representation of the same data. This combination can help to convey information quickly and effectively. For example, a table may provide detailed information about a specific variable, such as sales figures for a given period, while a chart can provide a visual representation of the same data in order to quickly compare and contrast different variables. By combining tables and charts, information can be effectively presented in a way that is easy to understand and interpret.
Excel Power Pivot – Hierarchies
Excel Power Pivot is a powerful tool available in Microsoft Excel which enables users to transform large amounts of data into meaningful and actionable insights. Hierarchies are an important feature of Power Pivot, which allows users to structure data into logical, hierarchical groups. These hierarchies can be used to drill down into specific data points, as well as to organize data into meaningful categories. For example, an organization may create a hierarchy of products and categories to better understand how various products fit within its overall product lineup. Hierarchies can also be used to group related data points, such as customers and sales figures, making it easier to analyze and interpret the data. Hierarchies are an important feature of Power Pivot and can be used to gain deeper insights into data.
Creating a Hierarchy
1.Open Microsoft Excel.
2.Create a new worksheet.
3.Label the first column “Hierarchy”.
4.Label the first row “Levels”.
5.In the first cell, type “1”.
6.In the second cell, type “2”.
7.In the third cell, type “3”.
8.Continue numbering the cells in the first row until you have the desired number of levels in the hierarchy.
9.In the second column, list the items in the hierarchy in order from top to bottom.
10.In the third column, enter the number of the level that each item belongs to.
11.To add additional levels, create a new row and repeat steps 5-10.
12.To add additional items, add new entries to the second column and assign the appropriate level number in the third column.
Renaming a Hierarchy
1. Select the entire hierarchy by clicking and dragging the mouse over the range.
2. Right-click anywhere within the selection and select Rename from the menu.
3. Enter the new name for the hierarchy in the Rename dialog box.
4. Click OK to apply the changes.
Creating a PivotTable with a Hierarchy in Data Model
1. Select the data range for your PivotTable.
2. Go to the “Insert” tab in the ribbon and select “PivotTable”.
3. In the Create PivotTable dialog box, select the option to “Use an external data source”, and then click “Choose Connection”.
4. In the Existing Connections dialog box, select the connection to the data source, and then click “Open”.
5. In the Create PivotTable dialog box, check the box to “Add this data to the Data Model” and then click “OK”.
6. In the PivotTable Fields list, select the fields you want to include in your hierarchy and drag them to the Rows area.
7. Right-click on the field name in the Rows area and select “Group”.
8. In the Grouping dialog box, select the “By each value” option and then click “OK”.
9. Repeat steps 6 through 8 for each field you want to add to the hierarchy.
10. When you have finished setting up the hierarchy, select the fields you want to include in the Values area, and then click “OK”.
Creating a Hierarchy based on Multiple Tables
Table 1: Employees
Employee_ID | Employee_Name | Position
————————————
101 | John Smith | Manager
102 | David Jones | Supervisor
103 | Sarah Brown | Clerk
Table 2: Departments
Department_ID | Department_Name
—————————–
10 | Accounting
11 | Human Resources
12 | Sales
Table 3: Employee_Department
Employee_ID | Department_ID
————————–
101 | 10
102 | 11
103 | 12
Hierarchy:
John Smith (Manager)
– Accounting (Department)
– Sarah Brown (Clerk)
– Human Resources (Department)
– David Jones (Supervisor)
– Sales (Department)
Removing a Child Level from a Hierarchy
1. Select the child level in the hierarchy that you wish to remove.
2. Right-click the selection and select “Delete” from the drop-down menu.
3. Click “OK” when prompted to confirm the deletion.
4. Excel will automatically rearrange the hierarchy to exclude the deleted level.
Adding a Child Level to a Hierarchy in excel
1. Open the Excel worksheet with the existing hierarchy.
2. Select the cell where you want to add the new child level.
3. Click the “Insert” tab at the top of the screen and then click “Rows” in the Cells group. A new row will be added above the selected cell.
4. Enter the new child level in the new row.
5. Indent the new row by clicking the “Home” tab and then clicking the “Increase Indent” button in the Alignment group. This will create the parent-child relationship between the new row and the row above it.
6. If necessary, adjust the width of the columns to accommodate the new child level.
7. Repeat steps 2-6 for each additional child level you wish to add.
Changing the Order of a Child Level in a Hierarchy in excel
1. Select the cell that contains the child level that you want to move in the hierarchy.
2. Access the Home tab on the ribbon at the top of the Excel window.
3. Click the small triangle at the bottom right corner of the Sort & Filter group on the ribbon.
4. Select Move Up or Move Down from the menu that appears.
5. Select the parent level of the cell you want to move.
6. Click the Move Up or Move Down button again to move the cell to the desired location in the hierarchy.
PivotTable with Changes in Hierarchy
Yes, you can create a PivotTable with changes in hierarchy in Excel. To do this, simply drag the field that you want to change the hierarchy of into the Row Labels or Column Labels area of the PivotTable. You can then arrange the fields in the hierarchy you want. For example, if you want to display data by year and then by month, you can drag the year field into the Row Labels area, and then drag the month field into the Row Labels area below it. The PivotTable will then show the data grouped by year and then by month.
Hiding and Showing Hierarchies
Hiding and Showing hierarchies in Excel can be done by using the Group and Outline tools. To hide a hierarchy, select the rows or columns that you want to hide and then go to the Data tab and select the Group tool. This will create a group of the rows or columns that you have selected. To make the hierarchy visible again, select the rows or columns and then go to the Data tab and select the Outline tool. This will expand the group to show the hidden hierarchy.
Deleting a Hierarchy from the Data Model
To delete a hierarchy from the data model, you can remove it from the database and delete the associated tables and fields from the data model. When removing the hierarchy from the database, be sure to also delete any associated data, such as relationships, selections, and filters. Once everything is removed, you can save and publish the changes to the data model.
Calculations Using Hierarchy
Hierarchy in a data model can be used to create calculations that analyze the relationships between the different levels of data. For example, a hierarchy can be used to calculate the total sales for a product across all its associated categories, or to compare the sales of a store across different geographic regions. Hierarchies can also be used to calculate the average sale price for a particular product, or to calculate the number of customers at each level of the hierarchy. Additionally, hierarchies can be used to identify the top-selling products at each level of the hierarchy, or to compare the performance of different stores within a given geographic region.
Drilling Up and Drilling Down a Hierarchy
Drilling up is the process of aggregating data in a data model by moving up a level in the hierarchy. For example, drilling up from individual sales data to regional sales data.
Drilling down is the process of digging deeper into data in a data model by moving down a level in the hierarchy. For example, drilling down from regional sales data to individual sales data.
Excel Power Pivot – Aesthetic Reports
Excel Power Pivot is a data analysis tool that helps you create aesthetically pleasing reports quickly and easily. It allows you to analyze data from multiple sources, create relationships between data sets, and use powerful calculations to generate reports that are visually appealing. With Power Pivot, you can also quickly create reports that are tailored to specific audiences, since you can easily customize the appearance and layout of the report. Additionally, Power Pivot can be used to create interactive reports with drill-down and filtering capabilities.
Reports based on Power PivotChart
Power PivotChart reports can be used to analyze data and identify trends. They can be used to compare different types of data, such as sales figures, customer demographics, or product performance. Power PivotCharts can also be used to identify correlations between different types of data, such as customer purchase behavior and product sales. Finally, Power PivotCharts can be used to forecast future trends and make predictions about the future of a company or its products.
Using a Common Slicer
A common slicer in Excel is a visual filter that allows you to quickly filter and analyze data in pivot tables and charts. Slicers make it easy to filter data to display only the information you need. To use a slicer, you first need to create a pivot table or chart. Then you can add the slicer to the pivot table or chart. Once the slicer is added, you can select the data points you want to display in your pivot table or chart.
Selecting Objects for Display in the Report
When selecting objects for display in a report, it is important to consider the purpose of the report and the information that needs to be included. Depending on the scope and complexity of the report, it may be necessary to include graphs, tables, diagrams, and/or other visual aids to make the report easier to understand. It is important to select objects that are relevant to the report and that will provide the reader with the necessary information to draw conclusions. When selecting objects for display, it is important to consider the size and format of the objects, as well as their placement within the report. Additionally, it is important to consider the audience and their level of understanding, as different objects may be better suited for different audiences.