Trending February 2024 # Power Bi Copilot: Enhancing Data Analysis With Ai Integration # Suggested March 2024 # Top 9 Popular

You are reading the article Power Bi Copilot: Enhancing Data Analysis With Ai Integration updated in February 2024 on the website Bellydancehcm.com. We hope that the information we have shared is helpful to you. If you find the content interesting and meaningful, please share it with your friends and continue to follow and support us for the latest updates. Suggested March 2024 Power Bi Copilot: Enhancing Data Analysis With Ai Integration

Are you ready to elevate your data analysis capabilities? Then let’s delve into the realm of Power BI Copilot and its AI integration. This tool isn’t just another addition to your data analysis toolkit; it’s akin to having an intelligent assistant, always ready to help you navigate through your data.

In this article, we’ll explain how Power BI Copilot works and how you can leverage it to empower you and your organization.

Let’s get started!

Copilot is an AI tool that provides suggestions for code completion. The tool is powered by Codex, an AI system developed by OpenAI that can generate code from a user’s natural language prompts.

Copilot already has Git integration in GitHub Codespaces, where it can be used as a tool for writing tests, fixing bugs, and autocompleting snippets from plain English prompts like “Create a function that checks the time” or “Sort the following information into an alphabetical list.”

The addition of Copilot in Power BI has infused the power of large language models into Power BI. Generative AI can help users get more out of their data. All you have to do is describe the visuals or the insights you want, and Copilot will do the rest.

With Copilot, you can:

Create and tailor Power BI reports and gain insights in minutes

Generate and refine DAX calculations

Ask questions about your data

Create narrative summaries

All of the above can be done using conversational language. Power BI already had some AI features, such as the quick measure suggestions that help you come up with DAX measures using natural language, but Copilot takes it to the next level.

With Copilot, you can say goodbye to the tedious and time-consuming task of sifting through data and hello to instant, actionable insights. It’s the ultimate assistant for uncovering and sharing insights faster than ever before.

Some of its key features include:

Automated report generation: Copilot can automatically generate well-designed dashboards, data narratives, and interactive elements, reducing manual report creation time and effort.

Conversational language interface: You can describe your data requests and queries using simple, conversational language, making it easier to interact with your data and obtain insights.

Real-time analytics: Power BI users can harness Copilot’s real-time analytics capabilities to visualize data and respond quickly to changes and trends.

Alright, now that we’ve gone over some of the key features of Power BI Copilot, let’s go over how it can benefit your workflow in the next section.

Looking at Power BI Copilot’s key features, it’s easy to see how the tool has the potential to enhance your data analysis experience and business decision-making process.

Some benefits include:

Faster insights: With the help of generative AI, Copilot allows you to quickly uncover valuable insights from your data, saving time and resources.

Ease of use: The conversational language interface makes it easy for business users with varying levels of technical expertise to interact effectively with the data.

Reduced time to market: Using Copilot in Power Automate can reduce the time to develop workflows and increase your organization’s efficiency.

Using Power BI Copilot’s features in your production environments will enable you to uncover meaningful insights from your data more efficiently and make well-informed decisions for your organization. However, the product is not without its limitations, as you’ll see in the next section.

Copilot for Microsoft Power BI is a new product that was announced together with Microsoft Fabric in May 2023. However, it’s still in private preview mode and hasn’t yet been released to the public. There is no official public release date, but it’ll likely be launched before 2024.

Some other limitations of Copilot include:

Quality of suggestions: Copilot is trained in all programming languages available on public repositories. However, the quality of the suggestions may depend on the volume of the available training dataset for that language. Suggestions for niche programming languages (APL, Erlang, Haskell, etc.) won’t be as good as those of popular languages like Python, Java, C++, etc.

Doesn’t understand context like a human: While the AI has been trained to understand context, it is still not as capable as a human developer in fully understanding the high-level objectives of a complex project. It may fail to provide appropriate suggestions in some complicated scenarios.

Lack of creative problem solving: Unlike a human developer, the tool cannot come up with innovative solutions or creatively solve problems. It can only suggest code based on what it has been trained on.

Possible legal and licensing issues: As Copilot uses code snippets from open-source projects, there are questions about the legal implications of using these snippets in commercial projects, especially if the original code was under a license that required derivative works to be open source as well.

Inefficient for large codebases: The tool is not optimized for navigating and understanding large codebases. It’s most effective at suggesting code for small tasks.

While Power BI Copilot offers a compelling platform for data analytics and visualization, its limitations shouldn’t be overlooked. You have to balance the undeniable benefits of Copilot with its constraints and align the tool with your unique operational needs.

As we mentioned in the previous section, Copilot for Power BI was announced at the same time as Microsoft Fabric, so naturally, there’s a lot of confusion about whether Fabric is replacing Power BI or whether Power BI is now a Microsoft Fabric product.

Microsoft Fabric is a unified data foundation that’s bringing together several data analysis tools under one umbrella. It’s not replacing Power BI; instead, it’s meant to enhance your Power BI experience.

Power BI is now one of the main products available under the Microsoft Fabric tenant setting. Some other components that fall under the Fabric umbrella include:

Data Factory: This component brings together the best of Power Query and Azure Data Factory. With Data Factory, you can integrate your data pipelines right inside Fabric and access a variety of data estates.

Synapse Data Engineering: Synapse-powered data engineering gives data professionals an easy way to collaborate on projects that involve data science, business intelligence, data integration, and data warehousing.

Synapse Data Science: Synapse Data Science is designed for data scientists and other data professionals who work with large data models and want industry-leading SQL performance. It brings machine-learning tools, collaborative code authoring, and low-code tools to Fabric.

Synapse Data Warehousing: For data warehousing professionals, Synapse Data Warehouse brings the next-gen of data warehousing capabilities to Fabric with open data formats, cross-querying, and automatic scaling.

Synapse Real-Time Analytics: This component simplifies data integration for large organizations and enables business users to gain quick access to data insights through auto-generated visualizations and automatic data streaming, partitioning, and indexing.

OneLake: The “OneDrive for data,” OneLake is a multi-cloud data lake where you can store all an organization’s data. It’s a lake-centric SaaS solution with universal compute capacities to enable multiple developer collaboration.

Through Fabric, Microsoft is bringing the capabilities of machine learning models to its most popular data science tools. There are other components, like Data Activator, which are still in private preview and are not yet available in Fabric.

Microsoft Fabric is available to all Power BI Premium users with a free 60-day trial. To get started, go to the Power BI admin portal and opt-in to start the free trial.

In a world brimming with data, Copilot might just be the ‘wingman’ you need to make your data speak volumes. It’s turning Power BI into a human-centered analytics product that enables both data engineers and non-technical users to explore data using AI models.

Whether you’re a small business trying to make sense of customer data or a multinational figuring out global trends, give Copilot a whirl and let it take your data analysis to the next level. Happy analyzing!

To learn more about how to use Power BI with ChatGPT to supercharge your organization’s reports, check out the playlist below:

Copilot in Power BI is still in private preview, but it will become available to Power BI customers soon. With this tool, users can use natural language queries to write DAX formulas, auto-generate complete reports using Power BI data, and add visualizations to existing reports.

To use Copilot in Power BI, all you have to do is write a question or request describing what you want, such as “Help me build a report summarizing the profile of customers who have visited our homepage.” If you want Copilot to give you suggestions, type “/” in the query box.

Once Copilot for Power BI comes out of private preview, it’ll be available at no extra cost to all Power BI license holders (pro or premium).

You're reading Power Bi Copilot: Enhancing Data Analysis With Ai Integration

Distance And Bearing Calculation: Power Bi Geospatial Analysis

This tutorial aims to discuss how to calculate distance and bearing in Power BI and how to efficiently use them for geospatial analysis.

You can find a lot of distance calculations on the web. For this demonstration, I’ll use a simplified example of a solution I needed to build for one of my supply chain network projects.

I’ll also show the calculation of the straight line distance from a delivery depot to service locations.

Here, I have a slicer to select a distance using a DAX measure. This allows dynamic analysis of the customers, flows, weight, revenue, and any other value within the selected distance.

The great-circle distance calculation also known as the Haversine formula is the core measure for this tutorial. If you master this technique, you can tackle any required distance and bearing calculation.  

Although I prefer to do most calculations in Power Query, it’s required to use a DAX measure when you need to analyze the data dynamically based on the selectable distance.

If available, the actual distance could be the preferred option. However, you won’t need this in many cases as the straight line distance will be sufficient. 

Google or Bing API can be used to add the distance in Power Query for both the actual and straight-line distance. It’s a good practice to have more tools in your geospatial toolbox. However, applying API to Power BI will not be discussed in this tutorial. 

I was asked to help with the allocation of the nearest business to business parcel lockers to service engineers’ home addresses.

The service engineers worked in predefined working areas that could change over time and started that job from home.

Overnight, the replenishment of urgent spare parts took place to the parcel lockers. The following morning, the engineer would collect the spare parts from the parcel locker on his way to his working area. 

Normally, I use GIS (Geographic Information System) software to do this kind of analysis. But now, I’ll try to do it with Power BI to obtain a dynamic allocation model. I also used both the straight line distance and bearing calculations. 

In GIS, bearing angle is used for navigation or direction. In this example, I added the bearing that’s converted into a direction (Orientation) because the Distance itself doesn’t offer the full solution. 

The nearest parcel locker might be positioned in the opposite direction from the working area. So, I wanted to display the direction as well.

This allows restricting the selection for the locker allocation to be based on corresponding geographical headings with the working area. 

As an example, the working area is North of his home. So, the preferred parcel locker location should be in the same direction. 

In this simplified example, the dataset comprises addresses in the Netherlands and the free parcel locker locations.

This contains columns for the Latitude and Longitude (to and from), Depot, Name, Parts value, and Demand.

Adjacent to the initial table are the calculated columns and the distance calculations in Excel. First, I calculated the radians.

Then, I created the actual distance calculations for both miles and kilometers using the radians and Haversine formula. 

The calculations for the bearing initially result in a decimal number in degrees. So, I need to convert this into something more practical.

I created a table column with the degrees from 1-360. I also added a column for the directions as per the compass.

Moreover, I added a SORT column for sorting the directions clockwise in Power BI.

After that, I loaded the sourceNL dataset and the Orientation table in Power Query.

Let’s take a look at the sourceNL table.

First, I added an Index column. Whenever I do transformations in the editor, I add an Index column either for reference or for sorting.

Then, I rounded the latitude and longitude to 4 digits, which is important in bigger datasets. By doing this, it will return an accuracy of 11 meters which is still enough.

For the sake of this example, I have added each step in a separate calculated column to show the map. I calculated the radians of the latitude and longitude values, just like what I did in Excel.

Then, I applied the Haversine formula to calculate the distances both in miles and kilometers.

For the bearing, the calculation is another formula that I took from the web. I just tweaked it a bit to fit my purposes for this scenario. 

Initially, this calculation is in radian. It’s completely useless. So, I need to convert it.

This is the Bearing pre-step. This is for converting the radians into the next step of my calculation.  

For the next step, I changed the negative numbers and corrected them by applying this calculation.

After that, I rounded the Bearing to get a whole number.

I deleted the Bearing (rad), Bearing pre, and Bearing columns. Then, I renamed the Naar boven afronden column as Bearing Roundup.

I can now merge the Bearing Roundup column in this table with the BEARING column from the Orientation table.

By doing this, I would be able to obtain the direction.

Now, I have the bearing (Bearing Roundup) and the direction (Orientation_Direction) columns that I’ll be using for the next model.

Here’s the result in Power Query.

For this one, I’ll be using a solution with an R script. This is a dataset with the calculated distances in miles and kilometers.

I’m running this R script which is much shorter and cleaner than the formulas.

After running the R script, I now have 3 tables.

Here’s the output. I also rounded it off.

As you can see, the results for the R script calculation and the Excel calculation are similar. 

Lastly, I’ll add a visual display to the end result.

To do that, I repeated the steps in a Power BI report. I loaded the table with the 3 locations. I also loaded the Orientation table and the dataset (selectionNL) with the Sort column. Then I merged columns for the Orientation.

This completes the final model.

In this report, I have chosen to show the direction seen by the customer. You can reverse this or show both in your report, depending on your preferences. All it takes is to exchange the from and to latitude and longitude in the calculation.

Hopefully, this tutorial contributed to a better understanding of the distance and bearing calculations in general.

Check out the links below for more examples and related content.

Cheers!

Paul

Export Underlying And Extract Data Records Using Power Bi

I’m going to show you how to extract records from merged delimited data within multiple columns. This turns your data into a format that’s more suitable for analysis.

There are a number of ways to do this. But for this tutorial, I’m going to focus on a solution suggested by Ankit, who’s part of our Enterprise DNA community. You may watch the full video of this tutorial at the bottom of this blog.

For this solution, I’m going to use Power Query to extract records from delimited data.

Below is the Opportunities table within Power Query.

As you can see, there are multiple values concatenated into a single record. In the 2nd row, for example, there are 4 different values presented. These 4 values are merged together under the Competitors and Competitor Amounts columns.

The first thing I’m going to do is use Text.Split.

Text.Split returns a list after splitting a text value based on a specific delimiter.

To start using Text.Split, I’m going to copy the delimiter used in this table.

Once I’ve done that, I’m going to add a custom column.

I don’t have to change the name just yet. I just need to do a Text.Split under Custom Column Formula.

This formula needs a text value. So I’ll just choose the Competitors column on the right pane and it’s automatically added to the formula.

I also need a separator given as a text. So inside a pair of quotation marks, I’m going to paste the delimiter I copied earlier. Then, I’ll add the closing parenthesis.

Once I press OK, I’ll end up with a list object.

For the second record, I have a list that contains four values. This corresponds to the 4 values also shown in the Competitors column and Amounts column.

Now that I’ve split the list, the next step is to add the corresponding value from the Competitor Amounts column. I’m going to the chúng tôi to do that.

Think of chúng tôi as an actual zipper. It takes a list of lists and combines the items.

Looking at the example below, just think of the first list (1 and 2) as the green track on the zipper.

Then, think of 3 and 4 as the red track.

When chúng tôi is applied, they come together in the middle. So 1 from the 1st group is combined with 3 from the 2nd group. The same thing happens for 2 and 4. This can be seen on the output, where there are two new groups that have been formed.

There may be times when the lists involved have different lengths. This means that if the lists are combined, the missing data will be returned. To create exact pairs despite the lack of data, a null value is added.

Going back to the Opportunities table, I’m going to add another custom column.

This time, I’m going to add the Competitor Amounts column to the formula.

I’m also going to add chúng tôi .

Checking below, it shows that there are no errors detected.

Looking at the formula, it shows that this syntax where the Competitors column was referenced returned a list.

But the syntax for the Competitor Amounts columns also returned a list.

Recalling what chúng tôi does, it takes a single list of lists and combines them.

Seeing that there are two lists showing up, I need the list initializer to bring those lists together. That’s why I’m adding these curly brackets.

Once I add the closing curly bracket at the end, I just need to press enter. That will give me a list object.

If I do the same thing to the second record, it shows a list object containing 4 lists. That also matches the number of values in the delimited data under Competitor Amounts.

I’ll use the sideward arrows to the right of the heading of the Custom column to expand the data into new rows.

Pay attention to the second record as I expand to new rows.

You’ll see that all the values from that record get expanded down.

On the third record, I show the combination of the second values.

So I’m going to use the sideward arrows again. But this time, I’m going to extract the values from that list.

I’m going to give it a custom separator.

I’ll use the double pipe as my delimiter. This should make the distinction among the values in the delimited data clearer.

Once I press OK, the values are concatenated right into the Custom column.

I no longer need the Competitor and the Competitor Amounts columns, so I’m going to remove those columns.

As for the Custom column, I’m going to split that.

On the transform tab, I’m going to select Split Column. I’m going to split it by the delimiter.

In the window, I’m going to give the double pipe as basis.

Once I press OK, the data will now be split into separate columns.

I’ll just rename these new columns to make it easier to figure out what the data is about. I’ll call this the Competitor column again.

Then I’ll call the other column the Amount column.

Obviously, the Amount column contains numbers. But if you look at the icon representing the data type, it shows that I have text instead of numbers. So I’ll start fixing that.

I’m based in Europe, so we use a period as a thousands separator instead of a comma. I’m going to use Replace Values to clean that up.

In the window, I just need to put a comma under Value To Find, and a period under Replace With.

Once I press OK, all the commas will now show periods instead.

The next thing I’m going to do is remove the dollar sign in front of the values. Again, I’ll use the Replace Values tool. This time, I’ll leave the space for Replace With with a blank.

Once I press OK, the values will only show the numbers without any currency.

I’ll replace the double dash with a blank.

And once I press OK, I have the right format for all the entries under the Amount column.

As I mentioned earlier, you can extract values from delimited data in different ways. But for me, this approach is one of the easiest and fastest ways to do it.

Since I got the idea for this solution from one of the members of the Enterprise DNA community, this also shows how important the Enterprise DNA Forum is. You can really see each problem from many different perspectives. From there, you can just choose a solution that you think would work best for you.

All the best,

Melissa

Top 10 Power Bi Training And Online Courses For Data Intelligence

Unlock the power of Data with Business Intelligence

Business intelligence (BI) brings a varied collection of strategies that uncover the hidden insights beneath the data sources and convert raw data into intelligent information for business decision making. To stay competitive, businesses must rediscover and use the data they have generated, this makes BI so important. Business intelligence, lets organisations to extract insights from a pool of accessible data to deliver exact, significant, and nearly real-time inputs for decision making. Here are the Top 10 Power BI Training and Online Courses for Data Intelligence-  

• Platform- Coursera • Offered by: University of California, Davis This specialization is offered in collaboration with Tableau, and is aimed for newcomers to data visualization with no prior experience using Tableau. In this course, you will view examples from real world business cases and journalistic examples from leading media companies. By the end of this specialization, you will be able to generate powerful reports and dashboards that will help people make decisions and take action based on their business data. You will use Tableau to create high-impact visualizations of common data analyses to help you see and understand your data. You will apply predicative analytics to improve business decision making and work on a capstone project in which you will use sample data to create visualizations, dashboards, and data models to prepare a presentation to the executive leadership of a fictional company.  

• Platform- Coursera • Offered by: PwC This Specialization will help you get practical with data analysis, turning business intelligence into real-world outcomes. You will explore how a combination of better understanding, filtering, and application of data can help you solve problems faster. You’ll learn how to use Microsoft Excel, PowerPoint, and other common data analysis and communication tools. Besides, you will be invited to join PwC’s talent network. Those who opt into this talent network will receive information about PwC career opportunities, thought leadership, and happenings in the PwC global network.  

• Platform- Udemy • Instructors: Manuel Lorenz, Maximilian Schwarzmüller In this course you will learn why Power BI offers you a comprehensive set of Business Intelligence tools for your data analysis goals. You will be mentored to imagine to quickly structure your data, to easily add calculations to it and to create and publish nice-looking charts in just a few minutes. You would get to know the different tools of the Power BI universe and learn how to use them and learn how to use the Query Editor to connect Power BI to various source types, how to work on the Data Model and understand the difference between those two steps and build relationships between different tables. You will learn how to use Power BI Service to create dashboards and to share and publish your results  

• Platform- Udemy • Instructors: Maven Analytics, Chris Dutton, Aaron Parry In this course, you’ll be playing the role of Lead Business Intelligence Analyst for Adventure Works Cycles, a global manufacturing company.  To design and deliver a professional-quality, end-to-end business intelligence solution, armed only with Power BI and a handful of raw csv files. By the end of the Adventure Works project, not only will you have developed an entire business intelligence tool from the ground up using Power BI, but you will have gained the knowledge and confidence to apply these same concepts to your own Power BI projects.  

• Platform- Udemy • Instructors: Kirill Eremenko, SuperDataScience Team This course begins with Power BI basics. You will navigate the software, connect it to a data file, and export a worksheet, so even beginners will feel completely at ease. To be able to find trends in your data and make accurate forecasts, you’ll learn how to work with hierarchies and timeseries. Also, to make data easier to digest, you’ll tackle how to use aggregations to summarize information. You will also use granularity to ensure accurate calculations. In order to begin visualizing data, you’ll cover how to create various charts, maps, scatterplots, and interactive dashboards for each of your projects.  

• Platform- LinkedIn • Instructors: Gini von Courter Discover how to quickly glean insights from your data using Power BI. This formidable set of business analytics tools which includes the Power BI service, Power BI Desktop, and Power BI Mobile—can help you more effectively create and share impactful visualizations with others in your organization. In this course, Gini von Courter helps you get started with this powerful toolset. Gini begins by covering the web-based Power BI service, explaining how to import data, create visualizations, and arrange those visualizations into reports. She discusses how to pin visualizations to dashboards for sharing, as well as how to ask questions about your data with Power BI Q&A. She also provides coverage of Power BI Mobile and shows how to use the data modeling capabilities in Power BI Desktop.  

• Platform- LinkedIn • Instructors: Gini von Courter In this course, discover how to leverage this easy-to-use tool to more efficiently model and visualize data. Learn how to connect various data sources, including Excel, databases, and web data sources like Wikipedia. Explore how to search and transform your data using the built-in Query Editor. Plus, instructor Gini von Courter shows how to build and arrange visualizations, create interactive reports, share your work, manage your published files in the Power BI service, and more.  

• Platform- LinkedIn • Instructors: Helen Wall In this course, instructor Helen Wall shines a spotlight on one of its most powerful and practical features: dataflows. Using dataflows in Power BI, you can easily ingest, transform, integrate, and enrich data from a wide variety of sources. Using practical examples, Helen explains how to boost efficiency and eliminate duplicate work by using dataflows to scale the extract, transform, and load (ETL) process across many users of Power BI data and dashboards. She demonstrates how to connect to various data sources within the Power BI cloud platform; leverage Power Query Online to transform data into useable data sets accessible to users; connect a Power BI Desktop file to a Power BI dataflow in the cloud; share dataflows to ensure that several users can connect to the same ETL process; schedule refresh schedules for those dataflows; and more.  

• Platform- LinkedIn • Instructors: Gini von Courter In this course, Gini von Courter shows how these applications are used to create business solutions. Learn how to build custom mobile or browser apps, automate workflows, design engaging visualizations and dashboards, and even create chat bots to deploy to customers and employees. By the end of this course, you’ll understand which of the Power Platform tools you should leverage for your own unique business scenarios.  

• Platform- LinkedIn • Instructors: Helen Wall

Business intelligence (BI) brings a varied collection of strategies that uncover the hidden insights beneath the data sources and convert raw data into intelligent information for business decision making. To stay competitive, businesses must rediscover and use the data they have generated, this makes BI so important. Business intelligence, lets organisations to extract insights from a pool of accessible data to deliver exact, significant, and nearly real-time inputs for decision making. Here are the Top 10 Power BI Training and Online Courses for Data Intelligence-• Platform- Coursera • Offered by: University of California, Davis This specialization is offered in collaboration with Tableau, and is aimed for newcomers to data visualization with no prior experience using Tableau. In this course, you will view examples from real world business cases and journalistic examples from leading media companies. By the end of this specialization, you will be able to generate powerful reports and dashboards that will help people make decisions and take action based on their business data. You will use Tableau to create high-impact visualizations of common data analyses to help you see and understand your data. You will apply predicative analytics to improve business decision making and work on a capstone project in which you will use sample data to create visualizations, dashboards, and data models to prepare a presentation to the executive leadership of a fictional company.• Platform- Coursera • Offered by: PwC This Specialization will help you get practical with data analysis, turning business intelligence into real-world outcomes. You will explore how a combination of better understanding, filtering, and application of data can help you solve problems faster. You’ll learn how to use Microsoft Excel, PowerPoint, and other common data analysis and communication tools. Besides, you will be invited to join PwC’s talent network. Those who opt into this talent network will receive information about PwC career opportunities, thought leadership, and happenings in the PwC global network.• Platform- Udemy • Instructors: Manuel Lorenz, Maximilian Schwarzmüller In this course you will learn why Power BI offers you a comprehensive set of Business Intelligence tools for your data analysis goals. You will be mentored to imagine to quickly structure your data, to easily add calculations to it and to create and publish nice-looking charts in just a few minutes. You would get to know the different tools of the Power BI universe and learn how to use them and learn how to use the Query Editor to connect Power BI to various source types, how to work on the Data Model and understand the difference between those two steps and build relationships between different tables. You will learn how to use Power BI Service to create dashboards and to share and publish your results• Platform- Udemy • Instructors: Maven Analytics, Chris Dutton, Aaron Parry In this course, you’ll be playing the role of Lead Business Intelligence Analyst for Adventure Works Cycles, a global manufacturing company. To design and deliver a professional-quality, end-to-end business intelligence solution, armed only with Power BI and a handful of raw csv files. By the end of the Adventure Works project, not only will you have developed an entire business intelligence tool from the ground up using Power BI, but you will have gained the knowledge and confidence to apply these same concepts to your own Power BI projects.• Platform- Udemy • Instructors: Kirill Eremenko, SuperDataScience Team This course begins with Power BI basics. You will navigate the software, connect it to a data file, and export a worksheet, so even beginners will feel completely at ease. To be able to find trends in your data and make accurate forecasts, you’ll learn how to work with hierarchies and timeseries. Also, to make data easier to digest, you’ll tackle how to use aggregations to summarize information. You will also use granularity to ensure accurate calculations. In order to begin visualizing data, you’ll cover how to create various charts, maps, scatterplots, and interactive dashboards for each of your projects.• Platform- LinkedIn • Instructors: Gini von Courter Discover how to quickly glean insights from your data using Power BI. This formidable set of business analytics tools which includes the Power BI service, Power BI Desktop, and Power BI Mobile—can help you more effectively create and share impactful visualizations with others in your organization. In this course, Gini von Courter helps you get started with this powerful toolset. Gini begins by covering the web-based Power BI service, explaining how to import data, create visualizations, and arrange those visualizations into reports. She discusses how to pin visualizations to dashboards for sharing, as well as how to ask questions about your data with Power BI Q&A. She also provides coverage of Power BI Mobile and shows how to use the data modeling capabilities in Power BI Desktop.• Platform- LinkedIn • Instructors: Gini von Courter In this course, discover how to leverage this easy-to-use tool to more efficiently model and visualize data. Learn how to connect various data sources, including Excel, databases, and web data sources like Wikipedia. Explore how to search and transform your data using the built-in Query Editor. Plus, instructor Gini von Courter shows how to build and arrange visualizations, create interactive reports, share your work, manage your published files in the Power BI service, and more.• Platform- LinkedIn • Instructors: Helen Wall In this course, instructor Helen Wall shines a spotlight on one of its most powerful and practical features: dataflows. Using dataflows in Power BI, you can easily ingest, transform, integrate, and enrich data from a wide variety of sources. Using practical examples, Helen explains how to boost efficiency and eliminate duplicate work by using dataflows to scale the extract, transform, and load (ETL) process across many users of Power BI data and dashboards. She demonstrates how to connect to various data sources within the Power BI cloud platform; leverage Power Query Online to transform data into useable data sets accessible to users; connect a Power BI Desktop file to a Power BI dataflow in the cloud; share dataflows to ensure that several users can connect to the same ETL process; schedule refresh schedules for those dataflows; and more.• Platform- LinkedIn • Instructors: Gini von Courter In this course, Gini von Courter shows how these applications are used to create business solutions. Learn how to build custom mobile or browser apps, automate workflows, design engaging visualizations and dashboards, and even create chat bots to deploy to customers and employees. By the end of this course, you’ll understand which of the Power Platform tools you should leverage for your own unique business scenarios.• Platform- LinkedIn • Instructors: Helen Wall In this course, Helen Wall focuses on the front end of the Power BI application—the dashboard—where users interact with charts and graphs that communicate trends in their data. Throughout this course, Helen steps through how to design and customize the setup of visuals and charts to make it easy to use, understand, and interact with the dashboard model. Learn how to work with data from open-source websites, create visuals such as heatmaps and sparklines, compare multiple variables with trendlines and violin plots, and build engaging maps. To wrap up, she demonstrates how to create and share your finished product: an intuitive, engaging dashboards.

Update Your Power Bi Dashboards

This is a quick tutorial about how you can make your Power BI dashboard and app more presentable and business-themed using Power BI Online. Microsoft recently unveiled a series of updates for Power BI and it’s recommended you utilize these updates to maximize your data management. You may watch the full video of this tutorial at the bottom of this blog.

The dashboard is the key for better data insights, which is why it’s important to organize it in an effective manner.

I hope you’re familiar with the potential of apps within your organization and online service. If you want some tips on how to maximize your Power BI Online Service, I suggest you read this tutorial here.

For this tutorial, I’ll focus more on how you can update and customize the look of your Power BI dashboard.

Now, let’s take a look inside my sample app here. On the left side, I can easily navigate to the different reports and dashboards inside the app.

The most important thing that I want to show you is how to create a theme or background in the dashboard. For instance, changing the color of the dashboard to make it more interesting. 

After that, you’ll see the respective workspace as well as the Power BI dashboards, reports, and more.

You can also embed images into the background themes. To do this, you need to create an image first within PowerPoint. It’s better if you use corporate images in your Power BI dashboard just like in my example below. 

I don’t recommend images that are too light in your Power BI dashboard so you need to have a darker background image. In my example, I just overlaid a dark-colored text box on top of my corporate image. Doing this can help your lighter visualizations stand out in your reports – it’s something you can do very quickly.

After that, just group the image and text boxes together, and then save it as an image.

Once you save the image successfully in your OneDrive, you need to open and view it online.

Turn on the Background Image option, and then paste the image address in the Image URL box.

You can also update the background color, tile background color, tile font color, as well as the tile opacity, depending on what you want your Power BI dashboard to look like.

The things I mentioned are pretty simple and easy to do, but it generally adds a big value to your dashboard. It’s all just a matter of getting the right contrast for your image in the background. Moreover, you might need to consider the colors you have inside your tiles and make sure it blends well. This is how you make your Power BI dashboard more business-themed.

Finally, this is how the updated Power BI dashboard will now look like.

This update from Microsoft is really worth trying. It really makes a big difference in the way you present and distribute your information across different teams. This is also one way to keep your consumers engaged and come back for more.

I hope you take time and enjoy finding contrasting colors that fit nicely in your Power BI dashboard.

Don’t stop learning. Until next time!

Sam

Power Bi Challenge #9 Wrap Up

We’re once again done with another Power BI Challenge. Judging who the winner is has become more and more challenging as we see participants getting better and better with every round.

This challenge is about currency conversion. It involves a company that buys scrap and waste recyclables. Because the company deals with clients from all over the globe, it meant having to deal with a number of currencies.

Let’s see how our participants came up with a report for this scenario.

Power BI Challenges

The Power BI Challenge happens every three weeks, with each challenge covering real-life scenarios where Power BI can be used to create insightful reports. Whether you’re a member of Enterprise DNA Online or not, you’re welcome to join. These challenges have made our community even more collaborative than before, with everyone having amazing discussions on the different solutions being submitted.

So far, we’ve succeeded in featuring different scenarios from different industries and fields every round. This has helped expose participants to various problems that they might encounter in the future.

Because of this, the Power BI Challenge has also turned into a powerful learning experience for everyone. In fact, some of the best submissions are now featured in the Power BI Challenge Showcase where members of Enterprise DNA Online can interact with the reports and experience firsthand how they work.

To pick the winners, we look at the 4 pillars that make a powerful Power BI report:

Data modeling

DAX calculations

Loading and transforming data

Reports and visualizations

It’s worth mentioning again that there is so much benefit in joining the challenges even if you feel like your skills are not yet at par with the other participants.

As Haroon shared in the last challenge, he has observed participants who have consistently been joining us from day 1. Challenge after challenge, their submissions have become more insightful, more creative and more impressive. This shows that if you really want to make serious progress as a Power BI user, it’s best to immerse yourself in these challenges and gain as much feedback as you can from the community.

The winner will get a complimentary membership to Enterprise DNA Online aside from having their work featured in the Power BI Challenge Showcase. Winning members can share the membership with someone who they think will benefit from the resources available within the portal.

We have separate winners for members and non-members. We also have a newcomer category where first-timers are given the chance to win an amazing package.

Challenge #9 Results

This challenge was extremely challenging. Coming up with a winning report meant having to combine DAX, power query and visualizations just to deliver the insights required. The dataset really pushed the participants to apply different techniques and apply every bit of knowledge they had about Power BI.

We admit that sometimes, we become mesmerized with the technical details and analysis. But we also know that the winning report should not only amaze us with fancy tricks. It should also deliver exactly what is being asked for in the project brief.

In this case, we would like to congratulate Alex Badiu for submitting the whole package!

Someone on the forum actually summed it all up for us when he said, “I’ve never seen someone able to provide so much information with so little on the page!” Our thoughts, exactly!

Great job, Alex!

As for our non-member category, great job to Rachwen Mosbehi who also managed to deliver so much insights while being as creative as possible.

Rachwen’s submission showed that your reports can be insightful and beautiful at the same time. This is truly amazing work, Rachwen!

We also mentioned earlier that we have a first-time participant winner. This can either be a member or a non-member; you just need to let us know that it’s your first time to participate in the challenge, and you’ll get the chance to win amazing prizes.

Our winning submission from a first-time participant comes from Craig Tysall.

Craig managed to give us so much detail in his report. We’re excited to see what else Craig has to offer in the next challenges.

Congratulations, Craig!

If you think you have what it takes to deliver the requirements for our next challenge, stay tuned for more information! Remember that it might be scary to jump in and participate especially if you’re just a beginner. But saying yes to the next challenge also means you’re saying yes to being better as a Power BI user.

All the best,

Enterprise DNA Team

Update the detailed information about Power Bi Copilot: Enhancing Data Analysis With Ai Integration on the Bellydancehcm.com website. We hope the article's content will meet your needs, and we will regularly update the information to provide you with the fastest and most accurate information. Have a great day!