Business intelligence with excel

Dashboard with data visualization for analyzing the correlation of IQ levels with the sales performance of managers. You can download a ready-made dashboard template for the presentation of a report on the analysis of the intelligence of sales personnel and sales performance in Excel at the end of the article. But first, let’s consider the interactive functionality and principles of building visualization using the example of the model of the relationship between smart coefficients and sales in practice.



Modern analysis of sales force efficiency in Excel

This dashboard in Excel allows you to perform visual analysis to assess the effectiveness of sales personnel management.

The model of the situation for the practical application of the dashboard is as follows. The sales department employs 10 managers. Each manager has his own sales performance indicators as each of them has its own advantages and disadvantages. Some of the managers are generally out of place or are selling the wrong types of products under ineffective pressure from management. Other salespeople need just a little nudge in the right direction to maximize new results.

From the situation described above, the question arises, how can all this be determined? Psychology comes to the rescue. Most large companies employ at least one psychologist among their employees. And this is a wise decision! It has long been proven that a person spends most of his energy on the psyche. Also, certain patterns of correlation between the relationship between business intelligence and successful human performance were noticed.

At first, the emphasis was placed on the IQ indicator. Many executives began hiring coaches to improve their IQ levels. Regular IQ tests were conducted to analyze the mental growth of employees and the effectiveness of coaching. But in practice, many HR managers have often argued about the IQ approach to sales growth. And not in vain! After all, Dr. Goleman later proved that a person’s success depends 4 times more on the level of the emotional intelligence quotient EQ than on IQ.

High emotional intelligence is determined by the ability to manage, create, and control emotions. After all, business is not only numbers and cold calculations, but also emotions that cannot be calculated with formulas. If business success was guaranteed by accurate calculations, then mathematicians would be the best businessmen. In fact, any business is based on the sale of goods or services. After all, any sale is primarily an emotional decision of the consumer’s choice.

Emotions are the main source of energy. All living things in this world are constantly fighting for energy, so there is no other world except the emotional one! Create, control and manage emotions = manage energy. The higher your EQ, the better your ability to work with your energy and your counterparties (customers, employees, business partners). Consequently, people with high EQ scores have a higher chance of success in sales and therefore in business.

Coefficients for determining the level of business intelligence of a manager

Modern methods for the effective management of sales personnel necessarily include several intellectual tests at once to analyze the indicators of the intellectual level of employees in various important areas. The most popular smart Q tests are coefficient determination:

1. IQ — mental intelligence (mind, logic, analytical forecast).
2. PhQ — physical Intelligence (fitness, health, comfort and discipline).
3. EQ — emotional intelligence (self-management, understanding oneself, understanding others, the ability to build relationships, the skills to create a suitable atmosphere).
4. SQ — spiritual intelligence (values, principles, beliefs, morality).

To track the dynamics of the correlation between improved sales results and the intellectual growth of managers, it is very effective to use tools for visual analysis. As an example, a dashboard will be presented with data visualization for all business intelligence ratios and performance indicators in sales. For convenient and efficient work, the dashboard is equipped with some interactive features. But first things first.



Preparing baseline data for comparing IQ and sales levels

To build a visualization of comparative multilevel analyzes, it is necessary to pre-prepare and well structure all different initial data into one integral system. In order not to create a complex large table with a large number of flags for the interconnection of different initial information, all incoming data was split into several small tables. This not only improves readability, but also makes it easy to master the capabilities of the dashboard template. All of these tables are on one sheet «Data», but with large amounts of data, they can be divided into separate sheets for ease of use. In this example, the initial data looks like this:

All initial information is divided into 6 tables:

1. Managers
2. Sales of pieces of Products in 2020
3. Sales Plans in 2020
4. Sales in 2019
5. Sales in 2020
6. Margin in 2020

All tables, before displaying data for dashboard visualization, form a general relationship, and all this happens on the «Processing» sheet:

With the help of complex formulas, the selection of the initial values from the “Data” sheet is made for further calculations and calculations. On the “Processing” sheet, preparation is being made to visualize the comparison of the indicators of managers’ IQs with their indicators of the dynamics of productivity growth.

Download dashboard of business intelligence and sales performance in Excel

The structure of the interactive dashboard for comparative visual analysis consists of 5 blocks.

The first block looks like a panel of diagrams with a visual display of 4 indicators of intellectual coefficients of managers:

The same block contains the first and main control for switching between managers (counter in the upper right corner). In fact, this is an element of control of the whole dashboard, since when using it, all information about the intellectual abilities and dynamics of sales is completely updated for each manager separately.

As a dashboard user, a business manager or sales manager has the ability to visually analyze the strengths and weaknesses of each sales manager. And after the analysis, make important decisions:

1. Which training or coaching course to send an employee to to improve his efficiency.
2. What group of products the manager should sell.
3. How to set sales plans for specific product groups.
4. How to motivate.
5. When to punish.
6. Where to set goals for promotion.
7. At what level is his dismissal deadline.

The second block «SALES 2019 & 2020 (in thousand)». Here is a chart for a comparative analysis of monthly transactions for the current and last year:

For the convenience of working with this block and effective presentation of the report, cursors are provided for the control of two interactive elements on the right. By managing them, you can focus on important points in the dynamics of the presentation of indicators.

Third block «MARGIN»:

The block is similar to the previous one, but displays the percentage of the share of the margin (net profit) received by the firm from the manager’s effective trading activity. A very mercantile schedule, but this is business and nothing personal.

The fourth block «SALES PLAN by PRODUCT»:

Here are presented the performance indicators of sales plans for 5 different groups of goods (A, B, C, D, E). If the plan is 100% fulfilled, then the top labels of the histogram columns are highlighted in white. If the plan is overfulfilled, the signature is colored red. In this case, it is worth paying attention to the setting of the plan level, perhaps it should be revised for the next accounting period for the current manager.

The fifth block «PRODUCT RANKING»:

All product groups are ranked here. Their rating is determined as a percentage. 100% has a headliner (the best selling product group). The rest of the products are assigned the share they occupy in comparison with the leading group.

For example, group B did not have enough 25% to make the same result as the flagship — group A. Group E needs to sell exactly half more to reach leader A.

Together, the blocks are harmoniously combined into a convenient interactive-driven intelligent business dashboard:

Download dashboard for analyzing business intelligence in Excel

The last sheet «Resources» contains graphic elements from figures made in MS PowerPoint, which is also included in the MS Office package. Unfortunately, you cannot create shapes of this complexity in Excel yet.

This dashboard does not contain macros, all interactive controls are implemented using standard Excel tools on the «DEVELOPER» — «Insert» tool tab.

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Introduction

We can derive business intelligence out of the Excel data by making use of its charting capability. In order to work with charting options, Excel provides the chart object.
The chart can either be an embedded chart (contained in a ChartObject object) or a separate chart sheet.

We have a lot of options to create business intelligence charts within SharePoint like SSRS, PerformancePoint, PowerPivot, Power BI, Client Side Rendering and so on. In this article, we will see how to get started with the charting capability of Excel using
VBA, upload it and view it from SharePoint.

Prerequisites

Make charts with sample data

On running the macro, we will get the below chart output in the sheet.

Create Chart from Excel Data

We can now run the script and see how the chart looks like by clicking on the «Run» button.

Create Pie Charts

Let’s go ahead and select the macro and run it to see the output chart.

Build Line Chart and Cylinder Charts

By changing the ChartType to ‘xlLine’, we can convert the previous Pie Chart to a Line Chart as shown below.

Upload to SharePoint

Available Chart Types

Name	Value	Description
xl3DArea	-4098	3D Area.
xl3DAreaStacked	78	3D Stacked Area.
xl3DAreaStacked100	79	100% Stacked Area.
xl3DBarClustered	60	3D Clustered Bar.
xl3DBarStacked	61	3D Stacked Bar.
xl3DBarStacked100	62	3D 100% Stacked Bar.
xl3DColumn	-4100	3D Column.
xl3DColumnClustered	54	3D Clustered Column.
xl3DColumnStacked	55	3D Stacked Column.
xl3DColumnStacked100	56	3D 100% Stacked Column.
xl3DLine	-4101	3D Line.
xl3DPie	-4102	3D Pie.
xl3DPieExploded	70	Exploded 3D Pie.
xlArea	1	Area
xlAreaStacked	76	Stacked Area.
xlAreaStacked100	77	100% Stacked Area.
xlBarClustered	57	Clustered Bar.
xlBarOfPie	71	Bar of Pie.
xlBarStacked	58	Stacked Bar.
xlBarStacked100	59	100% Stacked Bar.
xlBubble	15	Bubble.
xlBubble3DEffect	87	Bubble with 3D effects.
xlColumnClustered	51	Clustered Column.
xlColumnStacked	52	Stacked Column.
xlColumnStacked100	53	100% Stacked Column.
xlConeBarClustered	102	Clustered Cone Bar.
xlConeBarStacked	103	Stacked Cone Bar.
xlConeBarStacked100	104	100% Stacked Cone Bar.
xlConeCol	105	3D Cone Column.
xlConeColClustered	99	Clustered Cone Column.
xlConeColStacked	100	Stacked Cone Column.
xlConeColStacked100	101	100% Stacked Cone Column.
xlCylinderBarClustered	95	Clustered Cylinder Bar.
xlCylinderBarStacked	96	Stacked Cylinder Bar.
xlCylinderBarStacked100	97	100% Stacked Cylinder Bar.
xlCylinderCol	98	3D Cylinder Column.
xlCylinderColClustered	92	Clustered Cone Column.
xlCylinderColStacked	93	Stacked Cone Column.
xlCylinderColStacked100	94	100% Stacked Cylinder Column.
xlDoughnut	-4120	Doughnut.
xlDoughnutExploded	80	Exploded Doughnut.
xlLine	4	Line.
xlLineMarkers	65	Line with Markers.
xlLineMarkersStacked	66	Stacked Line with Markers.
xlLineMarkersStacked100	67	100% Stacked Line with Markers.
xlLineStacked	63	Stacked Line.
xlLineStacked100	64	100% Stacked Line.
xlPie	5	Pie.
xlPieExploded	69	Exploded Pie.
xlPieOfPie	68	Pie of Pie.
xlPyramidBarClustered	109	Clustered Pyramid Bar.
xlPyramidBarStacked	110	Stacked Pyramid Bar.
xlPyramidBarStacked100	111	100% Stacked Pyramid Bar.
xlPyramidCol	112	3D Pyramid Column.
xlPyramidColClustered	106	Clustered Pyramid Column.
xlPyramidColStacked	107	Stacked Pyramid Column.
xlPyramidColStacked100	108	100% Stacked Pyramid Column.
xlRadar	-4151	Radar.
xlRadarFilled	82	Filled Radar.
xlRadarMarkers	81	Radar with Data Markers.
xlStockHLC	88	High-Low-Close.
xlStockOHLC	89	Open-High-Low-Close.
xlStockVHLC	90	Volume-High-Low-Close.
xlStockVOHLC	91	Volume-Open-High-Low-Close.
xlSurface	83	3D Surface.
xlSurfaceTopView	85	Surface (Top View).
xlSurfaceTopViewWireframe	86	Surface (Top View wireframe).
xlSurfaceWireframe	84	3D Surface (wireframe).
xlXYScatter	-4169	Scatter.
xlXYScatterLines	74	Scatter with Lines.
xlXYScatterLinesNoMarkers	75	Scatter with Lines and No Data Markers.
xlXYScatterSmooth	72	Scatter with Smoothed Lines.
xlXYScatterSmoothNoMarkers	73	Scatter with Smoothed Lines and No Data Markers.

Source: TechNet

Summary

Thus, we saw how we can create Business Intelligence Charts from Excel Data and upload it to SharePoint.

One of the most common ways to collect and maintain data in organizations is through Excel sheets. But getting deeper insights from Excel may not always be possible, especially when you are dealing with massive volumes of data. To remedy this, you can use data visualization tools such as Power BI.

You can easily set up the Power BI Excel connection and start making attractive reports and dashboards. Using the simple UI, you can import data from your excel files and begin designing your reports. Power BI has a huge collection of charts, graphs, etc that can be customized according to your business needs.

In this article, you will learn how to effectively set up the Power BI Excel connection in 5 easy steps. 

Table of Contents

• What is Power BI?
  • Key Features of Power BI
• What is Excel?
  • Key Features of Excel
• What are the benefits of setting up Power BI Excel Integration?
• What are the Steps to Export data from Power BI to Excel?
  • Power BI Excel Connection Step 1: Extract Data
  • Power BI Excel Connection Step 2: Prepare Your Data
  • Power BI Excel Connection Step 3: Generate Your Report
  • Power BI Excel Connection Step 4: Format Your Report
  • Power BI Excel Connection Step 5: Save Your Report and Publish to Power BI Service
• How to Connect to Power BI Datasets with Analyze in Excel?
  • Steps to Establish Power BI Excel Connection
  • Limitations of Analyze in Excel 
• What are the Limitations to Importing an Excel Workbook in Power BI?
• Conclusion

What is Power BI?

Power BI is a data visualization and business intelligence tool that transforms data from a variety of data sources into interactive dashboards and BI reports. The Power BI suite offers multiple software, connectors, and services Power BI Desktop, Power BI services based on SaaS, and  Power BI mobile apps available on a variety of platforms. This set of services is used by business users to consume data and create BI reports.

Key Features of Power BI

• DAX Functions: The DAX function is a Data analysis expression included in PowerBI. These analytic functions are predefined codes for performing analytics-related operations on your data. Currently, there are about 200 functions in the PowerBI function library.
• Data Security: Power BI Protects your data with industry-leading data security features such as sensitivity labeling, end-to-end encryption, and real-time access monitoring.
• Flexibility: Power BI allows you to extract data from a variety of sources. For instance, you can easily set up the Power BI Excel Connection and visualize excel data in Power BI. From On-premise to Cloud-based databases, structured to unstructured data Power BI allows you to work with a broader range of datasets. 
• Data Filteration: In Power BI, you can create data subsets from several databases and work only on the filtered data that has contextual relevance.

What is Excel?

Microsoft Excel is a spreadsheet application developed by Microsoft to organize and record data in a tabular format. Launched in 1985, Microsoft Excel is a widely used Spreadsheet software in businesses worldwide allowing you to organize and manipulate data through formulas in columns and rows. MS Excel is loaded with functionalities to perform several operations such as calculations, pivot tables, graph tools, etc.

Compatible with Microsoft Windows, macOS, Android, and iOS, MS Excel is included with the MS Office Suite. It is typically used by firms to record, organize and analyze financial data. MS Excel also offers VBA programming that can assist you in automating repetitive tasks.

Key Features of Excel

• Conditional Formatting: MS Excel allows you to apply formats to a cell or range of cells, and have that formatting change depending on the value of the cell or the value of a formula.
• Built-in Formulae: MS Excel provides you with basic and advanced built-in formulae for sum, average, minimum, etc. You can use formula auditing to graph or trace the relationship between cells and formulas with blue arrows. You can track precedents (cells that provide data for a particular cell) or the cells that depend on the value of a particular cell. 
• Data Protection: Excel spreadsheets can be password protected on your laptop or PC. MS Excel also provides a robust system to recover data.
• Data Sorting & Filtering: You can easily perform the basic data sorting and filtering operation on your data in excel. MS Excel also provides Advanced filtering options for complex criteria.

What are the benefits of setting up Power BI Excel Integration?

Setting up the Power BI Excel Integration can help assist you in the following aspects:

• Deal with large volumes of data: Power BI has great compression capabilities for Microsoft Excel and text / .csv files that allow you to view, analyze, and visualize large amounts of data that cannot be opened in Excel. Most computers have a hard time opening a 300MB .csv file, which makes it difficult to analyze and report in Excel.
• Analyze Trends Quickly: Analyzing trends with Power BI is very easy. With built-in time intelligence analysis features, it only takes a few seconds to view massive amounts of data. You can see data by various dimensions and attributes, including date and time dimensions.
• Share your Reports: You can now publish to a secure Microsoft cloud service called Power BI Service and automate basic data updates. Just click Publish in the upper-right corner of the Power BI home feed. You can then easily share these reports with your colleagues and collaborate with them.
• Visualization Made-Easy: The great thing about Power BI is that with basic design ideas, it allows you to easily create something visually appealing and neat. Drag-and-drop functionality, easy resizing, and copy and paste make it feel like you’re at home for those familiar with the Microsoft Office suite.

What are the Steps to Export data from Power BI to Excel?

Power BI provides a beginner-friendly interface to quickly load data from Excel and start visualizing it. To begin setting up the Power BI Excel Integration, ensure that you have Power BI installed on your system. If not done already, you can download Power BI Desktop. You can start building the Power BI Excel Integration by following the simple steps given below:

• Power BI Excel Connection Step 1: Extract Data
• Power BI Excel Connection Step 2: Prepare Your Data
• Power BI Excel Connection Step 3: Generate Your Report
• Power BI Excel Connection Step 4: Format Your Report
• Power BI Excel Connection Step 5: Save Your Report and Publish to Power BI Service

Power BI Excel Connection Step 1: Extract Data

• Step 1: For this Power BI Excel Connection article, you download a sample Financial Excel Workbook. You can also work with any of your Excel workbooks.
• Step 2: Open Power BI Desktop. Navigate to the Home ribbon and click on the Excel option present in the Data section.
• Step 3: Go to the folder where you have saved your workbook and click on the Open button after selecting the file.

Power BI Excel Connection Step 2: Prepare Your Data

Now, a Navigator window will pop up on your screen. It displays an overview of the data so you can be sure that the range of the data is correct. For instance, all the numeric data types are shown in italics. Navigator allows you to transform your data before loading it. Transforming the data can often assist you in creating visualizations that are easier to understand. Follow the steps given below to perform various transformations:

• Step 1: Check the box next to Financials and click on the Transform Data button.

• Step 2: In the given sample data, values of units sold in decimal don’t make sense. Hence, you can transform it into whole numbers. Select the Units sold column and navigate to Transform Tab > Data Type > Whole Number. Click on the Replace current option to change the data type. 

• Step 3: To make the segments easier to observe in the visualizations, later on, you can change its format to uppercase. To do that, select the Segments column and navigate to Transform tab > Format > UPPERCASE.

• Step 4: You can shorten the Month Name Column header to Month by just double-clicking the Month Name column, and renaming it to just Month.

• Step 5: For this sample data, it is assumed that the Montana product was discontinued last month, so you can filter this data from your report to avoid confusion. To do that, go to the Product column. Click on the dropdown and clear the box next to Montana.

You can now observe that each transformation has been added to the list under Query Settings in Applied Steps.

• Step 6: Since your data is now prepared, you can go to the Home tab and save the modification by clicking on the Close & Apply option.

You can also notice that Power BI has recognized various filed such as Sales, Discounts, etc of numeric data types by placing a Sigma symbol. It has also denoted the Date field as a Date time entity by placing a Calendar icon.

Power BI Excel Connection Step 3: Generate Your Report

After the data preparation step of the Power BI Excel Connection, you can now move toward creating your reports. To do that, follow these simple steps:

• Step 1: Go to the Insert ribbon on the top, and click on the Text Box option. You can now type the title for this report as “Executive Summary – Finance Report”.
• Step 2: Select the text you typed and set the font size to 20 and bold. You can also resize the box for the text to be in one line.

• Step 3: To create a line chart to see which month and year had the maximum profit, go to the Fields pane. Drag the Profit field to a blank area on the report canvas. You will notice that Power BI displays a column chart with one column, Profit.
• Step 4: Similarly, drag the Date field. You now will see the profit columns for 2 years.

• Step 5: To view profits for each month, go to the Fields section of the Visualizations pane. Click on the drop-down in the Axis value and change Date from Date Hierarchy to Date.

Now, Power BI will display profits month-wise.

• Step 6: You can change the bar chart to a line chart from the Visualization pane.

• Step 7: To see which country had the highest profits, drag the Country field from the Fields pane to a blank area on your report canvas to create a map. Then, drag the Profit field to the map.

• Step 8: You can also find out which companies and segments to invest in. To do that, first, you can create some space by dragging the two charts you’ve built to be aligned side by side in the top half of the canvas.
• Step 9: Click on the blank area in the lower half of your report canvas and select the Sales, Product, and Segment fields from the Fields pane. After you observe a chart, you can drag it to fill the space under the two upper charts.

• Step 10: A slicer is an effective tool for filtering report page visual elements for certain selections. In this case, you can build two different slicers to narrow down the performance for each month and each year. The slicer uses the date field of the original table. You can drag the Date option from the Fields pane to the blank area on the left of the canvas.
• Step 11: Now, select Slicer from the visualization pane. You can also drag the ends to filter, or select the arrow in the upper-right corner and change it to a different type of slicer.

Power BI Excel Connection Step 4: Format Your Report

After preparing the basic report in the 3rd step of Power BI Excel Connection, you can start modifying its format for better visualization:

• Step 1: You can change the theme to Executive from the View pane.

• Step 2: You can also make specific changes to your graphs and charts individually in the Format tab of the Visualizations pane. Select Visual 2 (profits by month & year graph) and change the title text in the title section to “Profit by Month and Year” and Text size to 16 pt with the Toggle Shadow set to On. 

• Step 3: Similarly for Visual 3, change the Theme to Grayscale in the Maps section. Like Visual 2, change the title Text size to 16 pt with the. Toggle Shadow set to On for both Visual 3 & 4.
• Step 4: For Visual 5, go to the Selection controls section & toggle the “Select all” option to On. In the Slicer header section, set the Text size to 16 pt.
• Step 5: You can also add a background for the title. For that, go to the Insert ribbon on the top and navigate to Shapes > Rectangle. You can place the rectangle at the top of the page, and stretch it according to the width of the page and the height of the title.
• Step 6: Go to the Format shape pane, in the Outline section and set the Transparency to 100%. You can also set the Fill color to Theme color 5 #6B91C9 (blue).

• Step 7: Now navigate to the Format tab and select Send backward > Send to back. For the title to appear clearly, select the text in Visual 1, the title, and change the font color to White.
• Step 8: Similarly, create and place the rectangle shape for Visuals 2 & 3. Here also, change the Transparency to 100%. & set the color to White 10% darker in the fill section. Finally, go to the Format tab & select Send backward > Send to back.

Power BI Excel Connection Step 5: Save Your Report and Publish to Power BI Service

Coming to the last Power BI Excel Connection Step, you can now save this report by going to the File menu and clicking on the Save option.

Power BI allows you to share your reports with your colleagues via its Power BI service. This allows Power BI account holders to interact with your report but they can’t save changes. To publish your report, follow these steps:

• Step 1: Go to the Home ribbon and click on the Publish option. If you don’t have a Power BI service account, you can opt for a free trial also.
• Step 2: You need to choose a destination such as My workspace in the Power BI service > Select.
• Step 3: Click on the Open ‘your-file-name’ in the Power BI option.

This will open your report in the browser.

• Step 4: Click on the share icon at the top of your report to share it with your colleagues. This completes setting up your Power BI Excel Connection.

How to Connect to Power BI Datasets with Analyze in Excel?

Another aspect of Power BI Excel Integration is bringing Power BI Datasets to Excel using the Analyse in Excel feature. You can then view and interact with them using PivotTables, charts, slicers, and other Excel features.

Steps to Establish Power BI Excel Connection

Follow these simple steps to easily set up the Power BI Excel Connection and analyze your data in Excel:

• Step 1:  In the Power BI Service, go to the dataset or report you want to analyze in Excel. Click on the More options (…) next to the dataset or report name and select Analyze in Excel.

• Step 2: Another way for the Power BI Excel Connection is by opening the report and selecting Export > Analyze in Excel.

• Step 3: You can also select a dataset and then click on the Analyze in Excel in the menu bar of the Dataset details pane.

• Step 4: Using any of the above Power BI Excel Connection steps, the Analyze in Excel feature should install automatically. Finally, click on the Download button.

A new Excel workbook will be downloaded to your system that contains an OLAP connection to a Power BI dataset.

After opening the file, you may have to Enable Editing & Enable Content depending on your systems settings.

Limitations of Analyze in Excel 

Though Analyze in Excel is an excellent feature for utilizing Power BI Excel Integration, there are some challenges that you might encounter:

• Some firms may have Group Policy rules that prohibit the installation of required updates for Excel. If you are unable to install the update, please contact your administrator. 
• Row-level security (RLS) is supported for Analyse in Excel. RLS is applied at the data model level and to all users who access the data in the report. 
• When using Analyze in Excel, you may get unexpected results or the function may not work as expected. 
• Only PowerBI datasets that use import mode maintain hierarchies in Excel workbook analysis. When using Analyze in Excel, the hierarchy of PowerBI datasets created with DirectQuery or composite models is not preserved. 
• While using Analyse In Excel, you cannot change the connection string to specify the locale after the workbook is generated. 
• When data exceeds 2GB, an error message may be displayed. In this case,  you can reduce the amount of data by applying a filter or using an XMLA endpoint. 
• For guest users,  Power BI data can’t be analyzed in Excel for datasets sent (from) by another tenant.  
• Analyzing PowerBI data in Excel is a PowerBI service feature. It is not possible to analyze Power BI data in Excel using Power BI Report Server or Power BI Embedded.

What are the Limitations to Importing an Excel Workbook in Power BI?

While trying to set up the Power BI Excel connection, there are some challenges that you may face when you import an Excel Workbook in Power BI:

• External Connections to SQL Server Analysis Services Tabular Models: Excel 2013 allows you to connect to SQL Server Analysis Services tabular models and create PowerView reports based on those models without having to import the data. This connection type is not currently supported when importing an Excel workbook into Power BI Desktop. Alternatively, you need to recreate these external connections in Power BI Desktop.
• Hierarchy: Power BI Desktop doesn’t support this type of data model object. Therefore, when you import an Excel workbook into Power BI Desktop, the hierarchy is skipped.
• Binary Data Columns: This data model column type is not currently supported by Power BI Desktop. The binary column of data is removed from the Power BI Desktop result table. 
• Unsupported PowerView Elements: PowerView has some features that are not available in Power BI Desktop like Themes or specific types of visualizations (scatter plots using playback axes, drill-down behavior, etc.). These unsupported visualizations display unsupported visualization messages in the appropriate places in Power BI Desktop reports that you can edit or omit as needed. 
• Named range using PowerQuery’s FromTable or M’s Excel CurrentWorkbook: Importing this named range data into Power BI Desktop is not currently supported, but is a planned update. These named ranges are now loaded into Power BI Desktop as a connection to an external Excel workbook.  
• PowerPivot to SSRS: External PowerPivot connections to SQL Server Reporting Services (SSRS) are not currently supported because this data source is not currently available in Power BI Desktop.

Conclusion

In this article, you have learned how to effectively set up the Power BI Excel integration. Power BI Excel connection enables you to easily import data from Excel and gets you started with your report generation in minutes. With a user-friendly interface and a vast collection of visualization features, you can create visually stunning and informative dashboards and reports.  

As you collect and manage your data across several applications and databases in your business, it is important to consolidate it for complete performance analysis of your business. To achieve this you need to assign a portion of your engineering bandwidth to Integrate data from all sources, Clean & Transform it, and finally, Load it to a Cloud Data Warehouse, BI Tool like Power BI, or a destination of your choice for further Business Analytics. All of these challenges can be comfortably solved by a Cloud-based ETL tool such as Hevo Data.   

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Tell us about your experience of setting up the Power BI Excel Connection! Share your thoughts with us in the comments section below.