Trending March 2024 # Export Underlying And Extract Data Records Using Power Bi # Suggested April 2024 # Top 12 Popular

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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

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Analysing Customer Trend Using Dax In Power Bi

In this tutorial, we’re really going to use Power BI as an analytical tool to analyse customer trend. We’re going to work out how we can find our customers that are purchasing behind trend. You may watch the full video of this tutorial at the bottom of this blog.

We want to know this so we can keep a really close eye on how our customers’ purchases are going. We know that our top customers are going to bring the most of our profits, so we need to make sure that they are purchasing as they should be, based on historical trends.

We can analyse these insights really effectively in Power BI. I’m going to show you how you can do it by combining many techniques, not only with the data model, but more specifically with DAX formula.

In this demonstration, we’re analyzing trends by using a rolling total, so we’re going into how to calculate rolling sales over 90 days.

What’s cool about this is that we can look at any time frame, go back historically, and see the trends in our sales and make some analysis.

Here we’re comparing sales rolling this year versus last year. This is a great way to compare trends over different time periods, and so we use some time intelligence functions.

Down this table below, we look at the difference, which showcases the divergence and trends.

Another great thing about this is that we can actually drill down into every single customer.

The other two charts on the right side are looking at our entire portfolio of customers, while here we can see our customers, and really drill and see what they are buying or what they aren’t buying, so on and so forth. This will provide us some insights whether they’re way behind trend or way above trend.

If we drill into some very specific customers here, we can see where the trend change is, and we can really get some great insights from this.

This is what’s amazing about the new tables in Power BI. You can multi-select customers, and then utilise the power of the DAX formula and get significant insights.

Now I’m going to show you how to do this starting from scratch.

So, first we create a new measure table. We go Enter Data, and name it Sales Insights.

Then, we can create our Rolling Total. I’ve showcased the Rolling Total in another tutorial, but here I want to show you how to create this with the DATESBETWEEN, which is a really cool time intelligence function.

We’ll call this measure, Rolling Sales 90D. Then, we’ll use CALCULATE Total Sales, and DATESBETWEEN on the next line.

What DATESBETWEEN does is that it allows us to put a start date and an end date, and then calculate up between those dates.

Next, we put on our Dates and create a dynamic 90 days back. We go MAX Date here, will which return the current days in the context. We put – 90, and then go MAX Dates again on the next row.

We push enter, and then put it inside our table. We’ll be drilling into 2023, so we create a filter for that.

Since we want to see the trends, we look at the rolling 90 days, but not this year. We will look at last year. This is where we can branch out into some further time intelligence.

So we create a new measure, and call it Rolling Sales 90D LY (for last year). We use CALCULATE function, then our Rolling Sales 90D, and SAMEPERIODLASTYEAR with our Dates column.

We’re doing exactly the same calculation, but we’re doing it one year with the SAMEPERIODLASTYEAR function, which allows us to jump back in time.

 As we put this into our visualization, we can see the rolling sales this year versus last year in 90 days.

Moreover, we can branch out further to see the Difference in Rolling Sales. To create the measure, we simply minus rolling sales last year from this year.

We put it into our visualization, then add our Dates slicer so we can look at any time frame. Then, we utilise our data model and create another table for our Customers. We add our Difference in Rolling Sales as well.

Furthermore, we use these Data Bars to make this table really pop out. To do this, we simply go Conditional Formatting. We just change a few of the colors, sort it, and change the format to dollars.

And now we have an amazing dashboard with lots of great insights to extract.

By combining techniques, you should be able to work out which customers are purchasing behind trend – in real-time or for any time frame you specify.

Think about the follow-up actions that could occur from diving into this insight. We could inform the sales representative or regional manager that we should be going out and meeting these clients, we should be communicating with them, and we should be offering them promotions.

By doing so, we will be managing the effectiveness of our sales cycle and our selling strategies out there in the market.

Power BI is an incredible analytics tool that enables you to put some great analysis like this together in a relatively efficient way.

Dive in and have a look at how you can do this, and then try and visualize how you can actually implement this with your own data, in your own models. This will add a lot of value to your organization.

All the best!

Sam

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.

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).

Power Bi Vs Tableau: Similarities And Differences

Power BI vs Tableau – Overview

From interface and performance to data preparation and analytics, there are multiple factors contributing to the difference between Power BI and Tableau. Have a look.

What is Power BI?

Power BI is a data visualization tool that enables businesses to connect to various data sources, clean the data, and create interactive visualizations, reports, and dashboards. Developed by Microsoft, the tool provides a user-friendly interface that allows teams to explore data, discover insights, and share them with others in an organization.

Features and Capabilities of Power BI

Power BI enables businesses to analyze data and share insights across organizations, helping to make data-driven decisions. Some of the key features of Power BI include:

A wide of visualizations and data sources

Customizable dashboards

Easy-to-use interface

Q&A box for faster navigation to desired information

Report sharing

Data Connectivity Options and Integration with Various Data Sources Visualization Options and Interactive Dashboards

Source: Microsoft

Power BI offers a strong set of interactive visualizations with which you can explore data. It includes various chart types like line charts, pie charts, bar charts, maps, and gauges. You can customize the visual appearance, apply filters, and drill down into details to gain deeper insights. Moreover, dashboards in Power BI provide a sweeping overview of key metrics and KPIs and the reports highlight a detailed analysis with visuals.

Collaboration and Sharing Capabilities Pricing and Licensing Models

Power BI’s desktop model is free and the tool also comes for a free trial for its versions. It typically has three pricing models:

Power BI Pro: $9.99/ user/ month

Power BI Premium: $20/ user/ month

Power BI Premium: $4,995/ capacity/ month

What is Tableau?

Tableau is a data visualization and business intelligence software that brings with itself a user-friendly interface allowing you to create interactive and visually appealing charts, graphs, dashboards, and reports. The tool has been in the use by businesses for a good time now, thanks to its powerful features and ability to connect to various data sources.

Features and capabilities of Tableau

Dashboard with a consolidated view

Collaboration and sharing on multiple platforms

Live and interactive dashboards

Data connectivity options and integration with various data sources Visualization options and interactive dashboards

Source: Tableau

With Tableau, you can visually explore your data in multiple ways. It supports a wide range of chart types, such as bar charts, line charts, scatter plots, maps, and more. Users can interact with the visualizations, drill down into details, apply filters, and dynamically change parameters. Tableau enables the creation of interactive dashboards, where you can combine multiple visualizations into a single view.

Collaboration and Sharing Capabilities

Source: Tableau

Tableau provides collaboration features that enable multiple users to work on the same project simultaneously. It allows for sharing visualizations and dashboards with others within the organization or publicly on the web. Tableau Server and Tableau Online facilitate secure sharing, publishing, and embedding of interactive visualizations.

Pricing and Licensing Models

Tableau has split pricing models between three user types:

Tableau Creator: $70/ user/ month

Tableau Explorer. $42/ user/ month

Tableau Viewer: $42/ user/ month

Key Differences Between Power BI vs Tableau

Power BI and Tableau are both popular business intelligence and data visualization tools that offer powerful capabilities for data analysis, but they have some key differences. Here are the main differences between Power BI and Tableau:

Company and Integration

Power BI: Developed by Microsoft, Power BI is tightly integrated with other Microsoft products like Excel, Azure, and Office 365, making it a preferred choice for organizations already using the Microsoft ecosystem.

Tableau: Developed by Tableau Software (now part of Salesforce), Tableau is platform-independent and can easily integrate with various data sources and other third-party tools.

User Interface and Ease of Use

Power BI: Power BI has a user-friendly and intuitive interface, making it more accessible to users who are familiar with Microsoft products. It is relatively easier to learn for individuals with basic Excel skills.

Tableau: Tableau’s user interface is known for its flexibility and interactive visualization capabilities. While it may have a steeper learning curve, it offers more sophisticated customization options for experienced data analysts.

Data Connectivity and Transformation

Power BI: Power BI has robust data connectivity with a wide range of data sources, including cloud-based services like Azure and online data platforms. Its data transformation capabilities are strong, especially with Power Query, enabling users to clean and prepare data effectively.

Tableau: Tableau also supports various data connections, but its data transformation capabilities are comparatively limited. Users may need to rely on other tools for extensive data cleaning and transformation.

Pricing and Licensing

Power BI: Power BI offers competitive pricing and various licensing options, including a free version with limited features and paid plans for individual users and enterprises.

Tableau: Tableau’s licensing costs tend to be higher than Power BI, which may be a consideration for smaller organizations with budget constraints.

Data Visualization and Interactivity

Tableau: Tableau is well-regarded for its powerful data visualization capabilities and ease of creating interactive visualizations, making it a preferred choice for data analysts and data-driven organizations.

Similarities Between Power BI and Tableau

Be it Tableau or Power BI, both are intended towards one end goal: data visualization. Thus, these tools have a lot in common. Here are the similarities between Power BI and Tableau:

Data Visualization Capabilities

The foremost similarity you will find in the Power BI vs Tableau debate is that both are great at data visualization capabilities. The tools allow businesses to create interactive and visually appealing dashboards, charts, graphs, maps, and other visual representations. Moreover, both offer a slew of visualization and customization options, which helps present data effectively and uncover insights.

Interactive Dashboards and Reports

Source: Tableau

Ease of use and management is a factor that goes a long way when it comes to Tableau or Power BI or any business tool for that matter. These data tools simplify this by enabling businesses to access their dashboards and reports without making an effort, leading to seamless tracking and good user experience.

Data Connectivity Options and Integration with Various Data Sources Support for Multiple Platforms (desktop, web, mobile)

One of the noteworthy aspects of Power BI or Tableau is that these tools have mobile apps for both iOS and Android devices, which allows businesses to access and interact with the platform easily. The responsive design of these tools enhances the usability and eliminates the need to juggle.

Collaboration and Sharing Features

Source: Microsoft

Power BI and Tableau feature powerful collaboration and sharing capabilities, which allows businesses to share dashboards, reports, and visualizations within their organization. The tools offer different options for sharing through secure online platforms, exporting to different formats for offline sharing, and embedding visualizations in websites.

Community Support and Resources

Whether a business uses Power BI or Tableau, both provide it with active user communities and bring extensive resources, including documentation, tutorials, forums, and user groups to the table. This helps companies understand the tools better, exchange and apply knowledge as well as different practices, and troubleshoot issues.

Use Cases and Industry Applications of Power BI vs Tableau

Decisiveness and efficiency are the need of the hour. From marketing to supply chain, data visualization is proving to be the fuel for every business in day-to-day operations. So, industries have a lot to gain from tools and services like Power BI and Tableau. Here are the use cases of both in different sectors:

Use cases Where Power BI is More Suitable

Data Analysis and Reporting: Power BI allows users to analyze large volumes of data from various sources and generate interactive visual reports and dashboards. Users can drill down into details, apply filters, and perform calculations to gain insights and make data-driven decisions.

Sales and Marketing Analytics: Power BI enables sales and marketing teams to analyze sales data, customer behavior, and marketing campaigns. It helps identify trends, track sales performance, measure campaign effectiveness, and optimize marketing strategies.

Financial Analysis and Budgeting: Power BI can be utilized for financial analysis, including budgeting, forecasting, and expense tracking. It allows finance professionals to visualize financial data, create financial reports, analyze profitability, and identify cost-saving opportunities.

Supply Chain and Operations Management: Power BI can provide insights into supply chain and operations management by visualizing data related to inventory levels, production efficiency, supplier performance, and logistics. It helps optimize processes, identify bottlenecks, and streamline operations.

Use cases Where Tableau is More Suitable

Financial Analysis and Planning: Tableau offers financial analysis, budgeting, and forecasting capabilities, which can help finance professionals analyze financial data, track revenue and expenses, perform profitability analysis, and create financial reports

Operations and Supply Chain Management: The tool can give a hand in optimizing supply chain management by analyzing data related to inventory levels, production efficiency, logistics, and supplier performance. It can also help identify bottlenecks, streamline processes, and improve overall operational efficiency.

Human Resources Analytics: The HR department can leverage Tableau to analyze different forms of HR data, be it employee performance or workforce demographics. The tool can help HR professionals   gain insights into talent management, retention strategies, and employee satisfaction.

Healthcare Analytics: Tableau finds applications in healthcare for analyzing patient data, clinical outcomes, resource utilization, and hospital performance. It also enables healthcare professionals to visualize and analyze data to improve patient care, optimize resource allocation, and identify areas for improvement.

Factors to Consider When Choosing Between Power BI vs Tableau Specific business requirements

It all begins and ends with business goals and requirements. The most important difference between Tableau and Power BI is why you want to use them. Identify your organization’s goals, data sources, intended users, budget, and specific use cases for the business intelligence tool. Understand the types of data you’ll be working with, the level of analysis required, and the desired visualization capabilities.

Technical expertise and user skill levels

When choosing between Power BI vs Tableau, you must also consider the user-friendliness of each tool’s interface and the learning curve for your team. Power BI’s interface may be more intuitive for users that are comfortable with the Microsoft ecosystem. Tableau is more visually oriented and suitable for users seeking data exploration.

Budget and cost considerations

Evaluate the compatibility of each tool with your existing data sources, databases, and other applications. Consider the ease of integration with platforms such as Excel, cloud services, and other third-party tools that you currently use or plan to implement.

Scalability and future growth potential

Yet another important factor, the scalability and deployment options offered by both tools must be considered. Assess the tools based on their ability to handle large data volumes, support for on-premises or cloud deployment. Moreover, determine the availability of dedicated server solutions for sharing and collaboration.

Comparing the pricing models and licensing options of both tools can significantly help you with Power BI vs Tableau decision. Tap factors, including upfront costs, subscription fees, and user-based licensing. Determine the total cost of ownership over the long term and which pricing structure matches right with your budget and expected usage.

Power BI vs Tableau: Which is Better?

Both data visualization tools are great to use, but depending on the purpose and level of usage, a business can opt for the one which seems more suitable. Whether you go with Power BI or Tableau, it is highly recommended to learn the know-how’s of these tools to stay ahead of the game. Our No Code AI program explain data visualization tools in dept. Enroll now and start learning.

Frequently Asked Questions

Q1. Is Power BI easier than Tableau?

A. Both the tools offer a wide range of services and work in ways that suit specific sectors and businesses. However, Power BI triumphs as an easier route to take because it is beginner-friendly.

Q2. Q2. Why is Power BI more popular than Tableau?

A. Power BI features a user-friendly interface that is more convenient for beginners compared to Tableau.

Q3. Does Tableau require coding?

A. No, Tableau does not require users to know programming languages nor does it demand any specific technical expertise.

Related

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

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