Microsoft provides Power BI Report Builder to design paginated reports within the Power BI ecosystem. Paginated reports can create highly formatted, pixel-perfect reports suitable for printing or sharing as PDFs. With Power BI Report Builder, users can design these reports with precise control over layout, formatting, and data presentation, complementing the interactive and exploratory capabilities of Power BI Desktop.

Power BI Report Builder supports various data sources, allowing users to connect to different data types to create paginated reports. Some of the commonly used data sources include Microsoft SQL Server, Analysis Services, Power BI Datasets, Azure SQL Database, Oracle, Excel, XML, and CSV/Text Files.

In this blog post, our primary emphasis will be on integrating Power BI Datasets within Power BI paginated reports. We will consider one of the use case scenarios where I have a Power BI report that displays an invoice report specific to each user. This report includes numerous calculated columns and measures. To facilitate exporting the report as a PDF, we use paginated reports. Instead of recreating all the columns and measures manually in Power BI Report Builder, we can leverage the functionality of adding a Power BI semantic model.

Demonstration: Add a Power BI Semantic Model in the Power BI Report Builder.

Step 1: Opening Power BI Report Builder

When you open Power BI Report Builder for the first time, you will be greeted with a screen where you can choose to open an existing report or start a new one.

Above the design surface is the toolbar, where you have various tabs to change the formatting and setup of your report. To the left of the design surface is the Report Data pane, which displays all the built-in fields (automatically available in any paginated report), parameters, images, data sources, and datasets included in your report.

Step 2: Creating a New Report

You can also have the option to create a report from a wizard or a blank report.

Click on the data source and select the add power bi semantic model connection.

Step 3: Selecting the Semantic Model

Select your workspace and choose the appropriate semantic model.

Step 4: Adding a Dataset

After selecting the semantic model, add a dataset. A dataset comprises the query to be executed, a list of fields with their data types to be included in the report, and a connection to a data source.

Step 5: Designing the Query

Select your data source and click on Query Designer. The Query Designer is a visual representation of the families, fields, and criteria that the query is configured to return. While designing a query, it can be tailored to return particular records based on predetermined criteria and formatting.

In the screenshot below, you can see the measures developed in Power BI. You can also add tables to the query by simply dragging them into the design area.

Step 6: Select “OK”

Now you see your new dataset with a list of its fields in the Report Data pane, along with your calculated Columns and Measures.

By following these steps, you can effectively create and customize paginated reports in Power BI Report Builder, leveraging the Power BI semantic model to incorporate rich data visualizations and insights.

Note: To utilize a Power BI semantic model with DirectQuery in Power BI Report Builder, your dataset must include a measure, even if you don’t intend to display it in your report. Without the measure, the dataset won’t provide accurate data results.

Conclusion:

This way, you will be able to use the Power BI Semantic model incorporated within Power BI Paginated Reports.

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A standout feature of Power BI Desktop is its mobile layout view, which enables users to fine-tune their reports and dashboards specifically for mobile devices. This ensures that visualizations remain crisp, responsive, and user-friendly when accessed on smartphones or tablets.

Within the mobile layout view, users can leverage a suite of tools to customize their content for mobile consumption. This includes resizing visuals, optimizing spacing and alignment for smaller screens, and prioritizing key information for mobile users. By harnessing these tools effectively, users can create immersive and intuitive mobile experiences that effectively communicate insights and data to users on the move.

In this blog post, we will undertake a comprehensive exploration of this feature, delving into its intricacies through a meticulously structured step-by-step process.

Steps to open the Mobile view within Power BI Desktop:

Here are two ways to open the mobile view,

1. From the taskbar, as shown in the below screenshot
   2. From the ‘View’ option located on the Ribbon bar
   

Additionally, users can seamlessly transition back to the desktop view by simply clicking on the desktop icon located at the bottom of the interface.

Use case Scenario:

Let’s consider a scenario for a better understanding the mobile view.

Here is an example of the browser view, and we will convert it into the mobile view.

To switch the current browser view to a mobile-friendly layout, simply follow these steps:

Step 1: Click on the Mobile Icon in order to switch to the Mobile layout.

The screenshot below illustrates the same.

Step 2: It will be presented with two alternatives, as listed below:

1. Auto Create
2. Design Manually

Opting for “Auto Create” entails Power BI Desktop automatically generating a mobile-friendly version of your report, simplifying the process for you.

So, a single click on the Auto-Create Mobile Layout option will design the visuals on the mobile layout view, as shown in the below screenshot.

If you prefer to do it yourself as manual customization, simply drag and drop the tiles from the page visuals to craft your desired mobile layout.

Page Visuals

This feature lets us set up the mobile version of a report by adding visuals to it. It is visible in the page visuals on the right-hand side, as shown in the screenshot below:

Conclusion:

The enhancement improves the user experience by allowing Power BI to simplify the design process with its one-click auto creation of mobile views. This feature saves time and ensures a smooth user experience across various devices.

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On-object is an easy approach to constructing and setting up the visual. The on-object feature provides the following formatting options on visuals:

• Rename titles.
• Add data labels.
• Change colour of selected element/title.
• Change text format of titles.
• Easy to add data in the fields on Visual itself, etc.

Initially, Power BI desktop had a Formatting panel for each visual, and users had to navigate to that panel to find the required properties of the visual for formatting, as shown in the below screenshot.

Whereas On-Object feature allows user to simply find the formatting options beside the visual itself.

NOTES:

• This feature currently supports Table, Pie, Donut, Tree map, Card, Bar, Column, Line, Area, Combo and Scatter visuals.
• This feature is not supported in Power BI service or mobile layout.

Let’s consider a scenario where production supervisor wants to create a production report for manufacturing company. We can construct the visual using On-object feature for production report in Power BI Desktop by following below steps.

Step 1: Navigate to Power BI Desktop app.

Step 2: Navigate to below path to activate On-object feature.

In File -> click on Options and settings -> then click on Options -> then click on Preview Features -> then click on Features -> and put a tick mark in checkbox of “On-object interaction” -> then click OK to turn it ON. Then restart Power BI Desktop app to see the newly added On-object feature.

Step 3: Navigate to In Home -> click on Get Data -> then click on Dataverse.

Step 4: Log in with your user credentials to establish connection with Dataverse. Then select appropriate Environment and select the Table as per your requirement, and then either load the data directly or transform data.

In production report, all the Table columns are visible in Data pane, as shown in below screenshot.

Step 5: Add a Pie chart visual in Production report. In Visual, navigate to Add data and build a visual button, and from Build a visual popup menu, easily add data by selecting Product Name field in Legend and Revenue field in Values without drag and drop fields from the data as shown in below screenshot.

Step 6: In Build a Visual Popup Menu, select toggle Suggest a type to on for automatic selection of the best visual type based on selected data, or select toggle Suggest a type to off for all fields option menu.

When we select toggle Suggest a type to on, then Pie Chart Visual is changed to Clustered Bar Chart Visual, as shown in the below screenshot.

Step 7: In the clustered bar chart visual, right-click to get a popup menu and select the Format option, or double-click on the visual for formatting.

In the formatting of the clustered bar chart visual, the borders of the visual turn blue, and on hover, the region is displayed to format the Bars element, and on click, select the Bars element or Product-wise Revenue title.

In formatting, right click on selected Bar element or Axis value element to get a pop-up mini-toolbar and shortcut menu for formatting the selected Bar or Axis value element.

We can change the colour of Bar elements as shown in screenshot below.

Also, we can change the text format or change text colour of Axis value element, as shown in the below screenshot.

In formatting of Clustered bar chart visual, double click on Product-wise Revenue title itself to easily rename the title.

In the production report, navigate and click on the Plus button to open the customize pane switcher to easily add and switch between data, format, bookmarks, selection, performance analyzer, and sync slicers.

In production report, right click and select Format Canvas, and then navigate to Page Information for Tooltip and Drilltrough setting. These settings are moved to the format page setting in the visualization pane.

In the formatting of the clustered bar chart visual, navigate to the Reference line and select Constant Line from the Type dropdown for the Analytics feature. Analytics feature is moved to the format setting of visual from the visualization pane.

Conclusion

While creating reports using the On-object feature, we can easily construct and format the visuals. So, working with visuals becomes more convenient and simpler.

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There are various visuals available to design our Power BI report, such as Card, Slicer, and Matrix in Power BI. Microsoft has announced a new feature in Power BI, namely “Slicer (new)” and it is an advanced version of the existing “Slicer” Visual.

In this blog, we will go through the process of designing a Power BI report to implement the use of this Slicer (new) Visual. Let us consider a business scenario where a Salesperson wants to filter out the list of the Customers of the organization. This implies that the report will exclusively showcase Customers owned by the Salesperson we have selected.

In the preceding blog post, we accomplished this using the “Slicer” and now, in the current post, we will delve into the upgraded iteration of the established “Slicer (new)“.

Let us have a look at the steps to accomplish this requirement using Power BI:

Step 1: Navigate to Power BI Desktop to Microsoft Dataverse. Look for the ‘Get Data’ option. Click and Expand ‘Get Data’ and select ‘Dataverse’.

Please refer to the screenshot given below:

You shall be prompted to log in with the user credentials to establish the connection to Dataverse.

Step 2: After establishing the connection, select the necessary data from Dataverse. When you click the ‘Dataverse’, an environment selector window pops up. Select an environment from the options offered.

Please refer to the screenshot given below:

Step 3: Now, select the tables as indicated in the screenshot (You can select any table as per your requirements).

On selecting the tables from the appropriate environment, data can directly be loaded or transformed.

All the Table columns are visible in the sitemap. Select Slicer (New) from Visualization, and then select the columns Full Name from the System users table.

When you add the newest Slicer, it will automatically convert into the Button Format on the Power BI Report.

In the older version of the slicer, certain functionalities were limited. For instance, there was a need to manually create buttons in vertical and horizontal within the formatting options unlike in the newest version of the slicer. We have more functionalities as compared to the oldest slicer which we will see one by one below.

Add Images:

Images functionality allows us to take image URLs to display images on the Slicer options.

We will add the sample image URLs in the “Title” Field of User Entity.

After this, we have to click on Images->then click on Add data->then search Title Field.

Button Formatting:

In this property, we encounter a broader range of features such as Border, Fill, Shadow, Glow, and Accent Bar. Let us explore all, individually.

When we enable the “Shadow” option for the Slicer, it will be applied to the Slicer’s data. To achieve this, we need to define the position and offset parameters within the Shadow properties.

When we enable the “Glow” option for the Slicer, it will be applied to the Slicer’s data. To achieve this, we need to define the Color, position, and offset parameters within the Glow properties.

When we enable the “Accent Bar” option for the Slicer, it will be applied to the Slicer’s data. To achieve this, we need to define the Color, position, Transparency, and Width parameters within the Glow properties.

After that, we can filter the Customer by Salesperson name using the new “Button Slicer” feature as shown in the below screenshot.

Conclusion

By following these steps, you can explore the New Features “Button Slicer” report that displays Customers filtered based on selected Salespeople. Thus, is a valuable way to present data for various business scenarios within Dynamics 365 CRM.

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Recently, we came across one of its new features called Calculation Groups. This feature takes Power BI’s ability to understand and work with data to a whole new level, making it easier to do more complicated and personalized calculations.

In this blog, we’ll walk through to understand how we can use Calculation Groups to design improvised Power BI Reports.

Pre-requisites:

Before using the Power BI Calculation Group, we need to enable the Semantic Model from the preview features pane in Power BI.

1. Navigate to the settings,

2. Expand the Preview Features,

3. Enable the Modal Explorer and Calculation Group authoring

4. Click on “OK”

5. Restart the Power BI Desktop APP

6. After restarting the Power BI Desktop, Expand the Modal View in Power BI Desktop,

In the screenshot provided above, on the right side, there’s a “Model” tab that includes Semantic Models like Measures, Cultures, Roles, and more. The Calculation Group is a part of the Semantic Model.

Now, let’s demonstrate the use of the Calculation Group in one of our Power BI reports with a real-world use case scenario within the Power BI report. We will use calculation Groups to calculate the Lead Counts based on two aspects:

• Lead Status i.e. Open Leads, Qualified Leads
• Created On Date i.e. Monthly Created Leads, Quarterly Created Leads, and Yearly Created Leads

Previously we used to create separate measures for each of these Lead Count calculations in the Power BI report as shown below screenshot,

Now with a Calculation Group, we can combine these Measures and achieve the same results using a simple calculation Group Model.

In the report below, the highlighted columns represent measures that display the count of leads with various expressions. Our goal is to consolidate these measures into a Calculation Group.

Navigate to the Calculation group in the Semantic Modal,

7. Expand the Calculation Group,

8. Create a new Calculation Group, For now, we are creating it as “Lead Overview”

9. Create the Calculation Items, these items can be created with their own expressions. We have created three items since we had three measures used in the Lead report.

Created items are provided below with their DAX expressions

Leads = SELECTEDMEASURE()

Open Lead = CALCULATE(SELECTEDMEASURE(),FILTER(‘lead’,’lead'[statecodename]=”Open”))

Qualified = CALCULATE(SELECTEDMEASURE(),FILTER(‘lead’,’lead'[statecodename]=”Qualified”))

Please refer to the screenshot given below,

In the screenshot below, we have placed the “Lead Overview” Calculation Group in the column for the Matrix visual and included the Lead Measures in the Values section. These measures calculate the count of leads.

Here is the DAX expression for the Lead Measure:

Lead Count Measure = IF(COUNTROWS(‘lead’)=BLANK(), 0, COUNTROWS(‘lead’))

Furthermore, we can expand the Calculation Group by adding additional items. Let’s incorporate some Date KPIs. Please review the following expressions where we have introduced three new items to the existing Calculation Group:

YTD = CALCULATE(SELECTEDMEASURE(),DATESYTD(‘lead'[Created On]))

QTD = CALCULATE(SELECTEDMEASURE(),DATESQTD(‘lead'[Created On]))

MTD = CALCULATE(SELECTEDMEASURE(),DATESMTD(‘lead'[Created On]))

We previously discussed the dynamic switching benefits of the Calculation Group. After incorporating these new items into the Calculation Group without making any alterations, any updates or modifications to the Calculation Group will automatically be reflected in the Power BI Report.

Please refer to the screenshot given below,

Conclusion

In conclusion, the utilization of Calculation Groups in Power BI offers significant advantages for organizing and managing complex calculations within reports. By leveraging Semantic Models, we can efficiently structure and consolidate measures, such as Date KPIs and more, ensuring that updates and modifications seamlessly propagate throughout our Power BI Reports. This empowers users to create more dynamic and responsive reports, enhancing the overall data analysis experience. Calculation Groups provide a valuable tool for enhancing the clarity and flexibility of Power BI reports and are a key asset for data professionals and analysts.

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NOTES:

• This feature needs Power BI Desktop installed on your Windows.
• This feature is in private preview.

How to activate Copilot in Power BI Desktop?

To enable Copilot, you need to enable Quick Measure suggestions and Q&A for live connected Analysis Services Databases in Power BI Desktop or Power BI Service Admin Page. To enable both, the user must be a System Admin and follow the steps below:

1. Log into your Power BI account first.
2. Once you Log in to Power BI Desktop, Click on the File option > Select Options and Settings > Click on Options > then under Global Section, click on Preview Features > Turn on Quick Measure suggestions and Q&A for live connected Analysis Services Databases.

Let’s understand by considering the example:

Create a Dashboard to track and analyze sales across the country for Global Store.

1. After logging in, you will see the Power BI Desktop Interface, as shown in the screenshot below:

2. Referring to the above image, you can see the Quick Measure Suggestions button is disabled. To enable it, you need to load the data. There are multiple sources to load the data choose the one that suits your needs.

Note:  If you are importing data for 1^st time then Transform data. Data should be consistent.

Here we have imported data through CSV files, i.e., Details.csv and Orders.csv.

3. Now, from the Calculations section > click on Quick Measure suggestions. This will open a dialog window for Quick Measure Suggestions on the right side.

Let’s understand by considering some common DAX Measures Scenarios:

1. Mathematical Operations: Here, we calculated the total revenue from Details (table) by multiplying Amount(column) with Quantity(column).

After the description, click on Generate to get DAX suggestions.

 You can change the name of the measure just like we changed from measure 1 to Total Revenue. Similarly, we have to find the sum of profit.

However, to make it more visual, choose the donut chart and visualize the Total Revenue generated by each category.

2. Most/ least common value: Here we want to know the most preferred payment mode chosen by the customer.

3. Count of rows: To find how many orders have been placed.

Here, we visualize the Count of Orders placed by month using a stacked column chart.

4. Distinct Values: Furthermore, we can find distinct values for selected columns. As per the need for analysis, you can describe exactly what you need, and Copilot will generate DAX for you. DAX generated by Copilot can be customized later.

5. Filtered Values: Based on the condition, data gets filtered. Suppose the owner wants to find orders placed in New York.

Conclusion

Copilot helps you build faster and easier dashboard reports and insights. With Copilot measure suggestions, you can create interactive dashboards and analysis reports.

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In this blog post, we will explore how to create a Power BI report that filters activities based on selected users. This means that only activities owned by the chosen users will be displayed in the report.

To achieve this, we will need to handle some relationships between tables due to the complex structure of activity data in CRM.

Here are the steps to accomplish this requirement using Power BI:

Step 1: Begin by connecting Power BI Desktop to Microsoft Dataverse. To do this, navigate to Power BI Desktop and look for the ‘Get Data’ option. Expand ‘Get Data’ and click on ‘Dataverse’.

Please refer to the screenshot given below:

You will be prompted to log in with your user credentials to establish the connection to Dataverse.

Step 2: After the connection is established, select the necessary data from Dataverse. When you click on ‘Dataverse’, you will see an environment selector pop-up window. Choose your environment from the options provided.

Please refer to the screenshot given below:

Step 3: Now, select the required tables as indicated in the screenshot.

After selecting the tables from the from appropriate environment, you can either load the data directly or choose to transform it.

If you wish to include only specific columns from the table and avoid unnecessary data, use the ‘Transform Data’ option. This will open the Power BI Query Editor, where you can specify the columns needed for your Power BI report.

In this scenario, we require data from the ‘systemuser’ and ‘activitypointer’ entities.

As to have only required data in report and not to load the report with unnecessary data, we can use “Choose Columns” option to select only required columns from the table.

Please refer to the screenshot given below:

Step 4: Click the ‘Close & Apply’ button to update the changes in the tables. You will now see all the table columns in the sitemap.

As shown in the screenshot below:

You will be able to see all the Table columns in the sitemap. Select Table from Visualization, then select the columns Activity type, Subject from Activitypointer table.

As shown in screenshot here:

Step 5: To create a meaningful report, we need to add a slicer visual control to filter the data based on user selection. Select the ‘Full name’ column from the ‘User’ table.

Step 6: To reflect the slicer’s selection within the table, we must establish a relationship between the ‘Users’ and ‘Activity’ tables.

Navigate to the Modeling tab and look for ‘Manage Relationships’.

Click ‘New’ to create a relationship. Select ‘Ownerid’ from the ‘activitypointer’ table and ‘systemuserid’ from the ‘User’ table to establish the relationship.

Step 7: Finally, we will be able to filter Activity by Users as shown in the below screenshot.

Conclusion

By following these steps, you can create a Power BI report that displays activities filtered based on selected users. This is a valuable way to present data for various business scenarios within Dynamics 365 CRM.

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In a world where businesses generate vast amounts of data every day, extracting meaningful insights from this data has become crucial for making informed decisions and staying competitive. Microsoft has been at the forefront of innovation, consistently pushing boundaries to enhance user experiences. One such groundbreaking development is the introduction of the “Copilot” concept, brought to life through GitHub Copilot – an AI assistant designed to assist programmers in writing code. Expanding the scope beyond coding, Microsoft defines a Copilot as an application leveraging modern AI and large language models to aid users in complex cognitive tasks, from crafting sales pitches to planning themed dinner parties. Recognizing the potential of this concept, Microsoft has ingeniously integrated Copilot into its suite of products and services, unleashing its power to elevate user efficiency and productivity.

Microsoft 365 Copilot, GitHub Copilot X, Dynamics 365 Copilot, and more are just a few of the products where Microsoft has infused the Copilot idea, resulting in significant strides across multiple domains. However, one of the most recent and game-changing implementations of Copilot is seen in Power BI, where it empowers businesses with insightful data analysis and visualization capabilities.

The Power of Copilot in Power BI:

Power BI in Fabric already offers industry-leading visualization and AI-driven analytics, empowering business analysts and users to extract valuable insights from their data. The seamless integration of Power BI into Microsoft 365 further enhances the accessibility of these insights within the existing workflow. Now, with the introduction of Copilot in Power BI, Microsoft is taking the capabilities of data analysis and visualization to the next level.

Copilot in Power BI Key features:

This powerful feature streamlines the report creation process, making it possible to generate reports and gain insights using natural language descriptions.

• Automated Report Generation: AI-powered dashboards, narratives, and interactive elements save time and effort in report creation.
• Conversational Language Interface: Describe data requests using simple language for easy interaction and insights.
• Real-time Analytics: Stay ahead with swift visualization and data-driven decision-making.

How Copilot in Power BI Helps Business:

With its natural language interface, managers can easily create reports and gain insights without diving deep into technicalities. Copilot takes their descriptions and automatically generates the desired report, complete with interactive visualizations, simplifying the decision-making process. Two such use cases are

• Retail: Retailers can use Power BI to analyze sales data, track inventory levels, and understand customer behavior. It enables them to make data-driven decisions on pricing, inventory management, and marketing strategies.
• Finance: Financial institutions can leverage Power BI to analyze financial data, monitor key performance indicators (KPIs), and track revenue and expenses. It helps in identifying trends, managing risk, and improving financial planning.

Benefits of integrating Copilot in Power BI

The benefits of integrating Copilot in Power BI are multifaceted and cater to both business managers and data analysts alike:

• Simplified DAX Formula Creation: Power BI with Copilot empowers non-professional developers to create DAX formulas without requiring expertise in coding. This democratizes the data analysis process, making it accessible to a broader range of users.
• Efficient Data Model Changes: Copilot’s suggestions make it easier to modify the data model within Power BI. With reduced manual effort, developers can iterate on data models swiftly, leading to more agile and data-driven decision-making.
• Streamlined Visual Reporting: By leveraging Copilot’s capabilities, adding visuals to reports becomes more straightforward and intuitive. Users can create visually appealing and informative reports without extensive technical knowledge.
• Faster Report Generation: Power BI, powered by Copilot, can generate complete reports in a matter of seconds using natural language queries or comments. This capability empowers users to access crucial insights swiftly, enhancing data-driven decision-making.
• Advanced Natural Language Reporting: Copilot’s capabilities extend beyond simple natural language queries, allowing users to ask more complex questions and create detailed reports efficiently. This fosters deeper analysis and facilitates a better understanding of data insights.

Upcoming Features and Release Date:

Microsoft has already rolled out quick-measure suggestions for DAX capabilities, allowing analysts to create code quickly. The remaining Copilot in Power BI is currently in private preview, and Microsoft plans to reveal further updates and the public release date soon. Data enthusiasts and business professionals alike are eagerly anticipating the official launch, which promises to revolutionize the way we interact with data and make data-driven decisions.

Unlock the Power of Dynamics 365 CRM with Power BI!

In the meantime, if you’re interested in exploring Power BI for Dynamics 365 CRM, consider checking out the following blogs:

• Power BI Integration with Canvas App in Microsoft Dynamics 365 CRM – The blog demonstrates Microsoft’s Power BI report creation and integration into Dynamics 365 CRM via Canvas Apps, particularly for mobile service use to enhance on-the-go decision-making with data insights.
• Visualize data in a view with Power BI service – The blog introduces Microsoft’s new feature: using Power BI quick reports to visualize CRM data in model-driven apps, detailing activation steps and benefits for interactive data analysis within Dynamics 365 CRM.
• Add Power BI Reports On Model-Driven App Form with Power BI Report Control – The blog explains how Power BI reports can be integrated into CRM model-driven app forms, enabling users to access customized data insights within specific records and effectively meeting client requests.
• Card (new) Visual in Power BI Report within Microsoft Dynamics 365 CRM – Explore the new “Card (new)” visual in Power BI, allowing multiple fields within one visual, making report creation more user-friendly and efficient.

Conclusion

Copilot in Power BI represents a significant leap forward in the realm of data analytics. By harnessing the power of AI and large language models, Microsoft is empowering users with a tool that streamlines report creation, eases data analysis, and enhances productivity. With Copilot in Power BI, data analysts and business managers alike can look forward to a future where extracting valuable insights from data is more accessible and impactful than ever before. As we await the public release, the excitement for this next-generation AI assistant continues to grow. Stay tuned to the Power BI blog for updates and, prepare to witness the transformative power of Copilot in Power BI!

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In this blog, we will walk you through how to integrate the Power BI Report with Canvas App. Microsoft has recently provided an integration of the Power BI report within the Canvas app, as the report will be handy for users working on the Mobile apps at Service Location.

Let’s consider a scenario, a Field Service Technician will work on the Work Order and generate the Work Order Report, and this report needs to be integrated within Canvas app.

We will need to follow the steps below to achieve this requirement.

Step 1: Navigate to the Power BI Service at https://app.powerbi.com and make sure you have Power BI Dashboard added to the Power BI workspace.

Below is a screenshot of the same.

Step 2: Now develop a Canvas app to embed this Power BI Report. Navigate to https://make.powerapps.com and, within the appropriate environment, create a Canvas app.

Step 3: Insert Power BI Tile on the screen as shown in the below screenshot.

Step 4: Now we need to choose the below setting to enable Power BI Report.

• Workspace: Select Power BI Workspace you created, in this case, we selected Power BI Workspace.
• Dashboard: Select the Power BI Dashboard, in this case, we selected Work Order Inspection.
• Tile: Select the Report to be displayed on the Canvas app. For example, select Work Order Report.

Please refer to the below screenshot.

Step 5: Save the app and publish the changes. This will display the app with a report, as shown in the below screenshot.

Conclusion

We can use Power BI within Canvas app to have an analytical view of mobile applications along with other operations.

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Microsoft Dynamics 365 Business Central, also referred to as Business Central, is an enterprise resource planning (ERP) solution by Microsoft. Business Central helps small and medium-sized businesses manage various operational aspects, such as finance, purchasing, inventory, manufacturing, etc.

Power BI can be connected to data from the Business Central environment, allowing users to leverage reports within Business Central using its tables.

This blog will walk us through the steps to connect the Business Central data and develop a Power BI report.

Let’s consider a scenario where a user wishes to access the account report –

Please refer to the provided screenshots for visual guidance.

Step 1: Connecting Business Central to Power BI.

Navigate to the Power BI Desktop. Within the Menu Bar, you will have the option – Get Data, then in the search box, search for Business Central.

Step 2: Select the table you want to create a report for. Here we have considered an Account.

Step 3: Now, we can add some visuals to design the report.

Let’s create a report based on the following scenario:

• Accounts by Type,
• Top 10 Accounts by Revenue,
• Accounts by Post,
• Accounts by Category

You can also add a Pie Chart to the report, as shown in the screenshot below.

Step 4: If you wish to add more visuals to the report, add Line Chart and Clustered Column Chart.

Step 5: Lastly, publish the report.

Step 6: Once the report is published, it gets added to Power BI Service within the selected Workspace. All the workspaces, dashboards, and reports are then automatically available for use within Business Central.

Step 7: Navigate to the Business Central to integrate the Power BI Report. You can select the desired Power BI Report in the Business Central environment, as shown in the screenshot below.

Step 8: Click on the selected report and expand the Workspace.

Step 9: Click the Show More options and select Enable to view the report.

You can see the report after clicking on Enable and Tick as enabled.

The Account report is now enabled to view on the Business Central Environment.

Conclusion

In this way, Analytical Business Reports for Business Central can be designed using Power BI.

The post How to create a Power BI report using Business Central Data? first appeared on Microsoft Dynamics 365 CRM Tips and Tricks.

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The post How to create a Power BI report using Business Central Data? appeared first on Microsoft Dynamics 365 Blog.