Data is no longer just a buzzword. We live in a data-driven world, and if you know how to interpret and use data in your organization, it can make all the difference. Power BI and Power Query are good tools for this, which you can integrate into your workplace. First, let us see what Power BI is and how you can use it to your advantage within your workspace, regardless of your role within your organization. Power BI is a group of software services, apps, and connectors that combine to turn your unconnected data sources into readable, visually immersive, and interactive insights.

 The data may be an Excel spreadsheet or a gathering of cloud-based and on-premises data warehouses. Power BI lets us fluently connect to our data sources, fantasize and discover what is essential, and share that with anyone we want. 

The parts of Power BI 

Power BI consists of several rudiments that all work together, starting with these three basics 

• A Windows desktop operation called Power BI Desktop.
• An online (Software as a Service) service is called the Power BI service.
• Power BI mobile apps for Windows, iOS, and Android bias.

 Power Query is so awesome that it has been called the “best thing to happen to Excel in 20 years” by industry experts. Power Query is a data preparation and transformation engine. Power Query has a graphical interface for getting data from sources and a Power Query Editor for applying the change. Because the engine is available in numerous services and products, the destination where the data will be stored relies on where Power Query was used. Using Power Query, we can achieve the extract, transform, and load (ETL) processing of data. 

With that said, let us look at a detailed guide for Automating Excel reports. 

2. Step-by-step Instructions for Automation of Excel Reports 

• Produce a folder and store all the data lines that will supply data to the report in that folder. Each file must be proportional with respect to the others. Each file must have the exact number of columns and column heads, and the columns must be arranged in the same layout. 

• From the Data tab of the Ribbon, select Get Data and choose From File, From Excel as shown in Figure. 

• Choose the Excel Workbook folder that contains the files we wish to combine for detailing intentions. 
• Next, choose Combine & Load To… in order to begin the flow of combining the files and loading them into our report. 
• Click OK to proceed that we want to continue the process. 

• In the ensuring Import Data dialog box, select PivotTable Report as the endpoint for our combined data. 
• Next, Excel will give you the combined data in the PivotTable Field List. Create your PivotTable report by dragging fields from the Field List into the desired quadrants within the PivotTable to complete the first report creation process. Save the worksheet in which the PivotTable report is contained. 
• Next, store the file with the new data in the same folder as all prior months’ files when the new data becomes available. Then open the workbook that contains the PivotTable, right-click on it, and select Refresh from the menu. The PivotTable will update to include the newly updated data after we do so. 
• When fresh data becomes available, just place the file containing the new data in the same folder as all previous months’ files. Then open the PivotTable-containing worksheet, right-click it, and choose Refresh from the menu. After we do so, the PivotTable will update to include the newly updated data. After we build the initial report with Power Query, any subsequent data updates to the report will take only a few seconds of your time… That is true automation. 

 3. Let us Understand this Automation Through an Example 

   AN EXAMPLE OF POWER QUERY AUTOMATION 

 To illustrate how helpful Power Query can be when automating a report, assume the following scenario. 

Let’s take the Finances of the HR Department of a Manufacturing Company, and compare all expenditures by ledger for the current and the previous year.

Now with the help of Power BI and Power Query, this task can be done quickly by avoiding basic manual processes of making data.  

Power Query will help make all the expenditures data for the mentioned years into some informational data by cleaning, extracting, and filtering all the necessary expenditure data. 

• Each month, we make a report summarizing all expenditures by general ledger account. 
• To prepare this report, we got an extraction of data from a database that summarizes the past month’s activity. 
• We need to include the data file we receive each month with all the past data files sustained for the year to provide year-to-date information in our report. 
• Presently, we spend significant time copying and pasting data and updating formulas to complete the report. 

With Power Query, we can automate our report by developing a query that pulls data from all the files in a given folder to create a single data set. We can quickly create a PivotTable from this single data set to summarize the transactions by general ledger account and by month. Then, when next month’s data becomes visible, we place the file containing the data into the folder where the files containing the previous month’s data are stored and refresh our PivotTable. At that point, our report immediately updates to include last month’s data. In other words, we can update our report by simply dragging and dropping the new file into the folder with the rest! 

Conclusion  

Excel is amazing, but it becomes very powerful when combined with Power Query. Power Query not only simplifies the flow of importing data from multiple source files but arranges them into an Excel sheet in a perfectly usable and suitable format. 

 Excel’s Power Query feature is one of the most noteworthy features ever added to Excel. You can quickly start making the most of your existing data with this duo. As demonstrated above, this tool provides business professionals unprecedented options for linking and transforming data and automating many reporting processes. So, have you got your hands on it yet? 

Frequently Asked Question

BI has helped manage our data to make it easily accessible and analyzed so that decision-makers can come to conclusions quickly and easily. 

To give you some context, 75% of the global workforce uses BI regularly. 

But the problem is that many are still unaware of some of the advanced features BI offers to help their business scale exponentially. Today, we will share those Advance Features of BI with you that not only helps save time but will let you use your data in hand with better clarity. 

Top 5 Advanced Power BI Features  

• Natural Language Q & A Question Box
• Azure Machine Learning Integration
• Custom Visual Development with R and Python Script
• Easy integration with Microsoft Power Suite {Power App, Power Automate, and Power Query}
• Predictive Analysis

    1. Natural Language Q & A Question Box    

• Sometimes the quickest way to get answers from our data is to ask using natural language. For illustration,” what were the total sales last time.” 
• Making Q&A explore data using intuitive, natural language capabilities and admit answers in the form of maps and graphs. Q&A is different from a hunting machine- Q&A only provides results about the data in Power BI datasets.
• To produce a featured question, select the further options ellipsis in the top-right corner of Power BI, point to Settings, and select Settings. Select Datasets> Retail Analysis sample> Featured Q&A questions. Select Add a question. We can type our questions in the text box. 

Which visualization does Q&A use?

• Q&A picks the stylish map or graph grounded on the displayed data. Occasionally data in the underpinning dataset is defined as a specific type or order, and this helps Q&A know how to show it. For example, if data is described as a data type, it’s more likely to be displayed as a line map. Data distributed as a megacity is more likely to be displayed as a chart. 
• We can also tell Q&A which visual to use by adding it to your question.  
• But we should understand that it may not always be viable for Q&A to display the data using the visual type we requested. Q&A will prompt us with a list of workable visual types. 

The Q&A visual in Power BI reports

• In Power BI reports, there’s a specific type of interactive visual called the Q&A visual. When a report developer adds this visual to a report, report end users can ask natural language questions and produce a new report visual that represents the answer to that question. The Q&A visual behaves like other illustrations in a report; it can be cross-filtered/cross-highlighted and supports bookmarks and commentary. 
• We can identify a Q&A visual by its question box across the top. This is where we’ll enter or class questions using natural language. The Q&A visual can be used repeatedly to ask questions about our data. When we leave the report, the Q&A visual resets to its dereliction. 

     2. Azure Machine Learning Integration

• Since this point also involves integration with machine learning in Power BI, it would help the users with the complete visualization of the outcomes of the Machine Learning Algorithm. This can be done simply by dragging, dropping, and connecting all the data modules. 
• The first step to integrating an Azure ML model with Power BI is to train the said model using any options available in “Azure ML Resources” and post it consequently. The model is also read from Power BI and integrated with a dataset. Latterly, the model output is displayed in the Power BI dashboard.
   

   3. Custom Visual Development with R and Python Script 

While Power BI supports numerous standard data visualizations out of the box, it’s also possible to make our own with custom data visualizations. By adding open-source data- viz libraries from R and Python, judges can produce largely customizable visualizations to add to their coming Power BI report. 

What is R Script?

An R script is a text file containing (nearly) the same commands that you would enter on the command line of R.(nearly) refers to the fact that if you’re using sink() to shoot the output to a file, you’ll have to enclose some commands in print() to get the same output as on the command line. 

Can Power BI be used with R? 

 The Power BI services supports viewing and interacting with illustrations created with R scripts. Illustrations created with R scripts, generally called R illustrations, can present advanced data shaping and analytics similar to forecasting, using R’s rich analytics and visualization power.

How can we write an R script in Power BI? 

• In Power BI Desktop, select Get Data, choose Other> R script, and also select Connect. 

• Just copy our script into the script window and select OK, If R is installed on our original machine. The rearmost installed interpretation is displayed as your R machine.  
• Select OK to run the R Script.

What is Python script?

A Python script is a pack of commands in a file designed to be executed like a program. The file can contain functions and import colorful modules, but the script must be run within a Python interactive shell or through the command line to achieve a specific task. 

Can Power BI be used with Python? 

Using Python in Power BI, we can extend the normal capabilities of the tool and enhance the way Power BI works. We can perform external data analysis using frameworks like Pandas, run external Python scripts from Power BI, produce and manipulate datasets, and produce visualizations using Python libraries. 

How do you write a Python script in Power BI? 

• In Power BI Desktop, select File > Options and settings > Options > Python scripting. The Python script options page appears. 
• If necessary, specify your local Python installation path in Detected Python home directories. 
• Select OK. 

   4. Easy integration with Microsoft Power Suite {Power App, Power Automate, and Power Query} 

Power BI is presently available as part of the Office 365 Enterprise E5 version.

• Integration of Power BI with Power Automate 

Use Power Automate to merge Power BI with your favorite apps and services. With Power Automate, we create automated workflows to get notifications, synchronize files, collect data, and more. 

• How can we integrate Power BI and Power Automate? 

In Power BI Desktop, On the Insert tab, select Power Automate (preview) in the Power Platform section. Once you choose the visual, it automatically gets added to your current report runner with getting started instructions. 

• Power Automate can Pull Data from Power BI 

With Microsoft Power Automate, you can automate exporting and distributing Power BI reports to various formats and scripts. In this composition, you create your inflow from scrape. You use the Import to train for Power BI Reports action to automatically distribute a Power BI report via email. 

• Integration of Power BI with Power App 

 Power BI and PowerApps are crucial parts of the Microsoft Power Platform. Once you use these tools, you can enjoy lots of business openings.  

With  PowerApps and Power BI integration, we have a bigger picture and more significant perceptivity into our business while making the utmost of our information. 

Power apps in Microsoft refer to the enhanced app development terrain that allows us to make robust and custom operations. It comes with an excellent collection of functions, data platforms, connectors, and services necessary for speeding up the entire app development process. 

How to Integrate Power BI with PowerApps? 

Power BI and PowerApps work in tandem, regardless of who initiates them. We can develop business processes that give crucial visualization and analysis once these two platforms are connected. We can also act immediately from anywhere and anytime, thanks to the apps we built using Power BI and PowerApps connectivity. 

Step 1: Create a Data Set  

Step 2: Create an Invoice Data Table 

Step 3: Create a Power BI Report  

Step 4: Publish the Power BI Report  

Step 5: Calculate the Due Over Delays  

Step 6: Switch to Report Edit Mode  

Step 7: Choose the Fields  

Step 8: Design the Application  

Step 9: Modify and Design the Default Gallery Layout  

Step 10: Create the Item Controls  

Step 11: Add a Screen for Email  

Step 12: Add an Email Icon  

Step 13: Name the Application  

Power BI and PowerApps integration bring uniqueness to a business’s market. If we have the opportunity to create multi-faceted business applications, we can efficiently meet all our business requirements. We also have the chance to shape the future of our business. 

 5. Predictive Analysis 

Predictive analysis is a proficiency to see what will happen in the future. The predictive analytics model uses applied mathematics techniques with evolving technologies, like computing and Machine Learning to create correct predictions. 

The predictive analysis answer uses current and historical facts, events, or patterns in historical and transactional knowledge. 

Power BI element Auto ML automates machine learning model creation so that users will build high-quality predictive models. 

 Data visualization with Artificial Intelligence reflects the main elements of our data forcing predictions through our machine learning models. 

Predictive Analytics in Power BI

Predictive analytics could be challenging, requiring a spread of study techniques and analytical capabilities. However, we can summarize the predictive analytics world in four straightforward steps.   

• Determine the problems and solutions that require predictive analytics. 
• Evaluate knowledge assortment and experimentation. 
• Build and train an exact predictive analytic model. 
• Business Method Automation to introduce unjust insights in business applications.  

Conclusion

As per Gartner’s report, by 2020, businesses using BI have an increase in profits compared to those not using BI. Over the years, Power BI has cemented itself as a business intelligence and reportage tool that enables users to form intuitive reports. These advanced features make BI even more robust and flexible. You get more options for reporting and sharing, along with various elements to tailor solutions to precise needs. So, explore the advantages of these advanced Power BI features and make the most of your business data seamlessly. 

As analytics tools and techniques quickly emerge, most businesses are now turning to business intelligence (BI) to overcome their data management challenges. Among these tools is the Microsoft Power BI. Power BI provides completeness of vision and can execute heavy enterprise data in no time. Microsoft Power BI is used by management and department reps, with reports and forecasts created to assist marketing and sales reps. Power BI also helps provide data for management on how the department or individual employees are progressing toward their goals.  

Our previous blog: Power BI Use Cases, we discussed some popular Power BI dashboards that businesses use to derive data-driven decisions. Today, we will look at

Power BI benefits

1. Connect Your Data with Ease 

Power BI makes it simple to bring all of your data into one place for easier access and visibility in your reporting efforts. The tool supports numerous connectors, allowing businesses to load data from various popular cloud-based sources. They include Azure (Azure Data Warehouse), Google Analytics, Dropbox, SalesForce, and OneDrive, as well as Excel spreadsheets, CSV files, and data stored on-premises, such as SQL Database. 

You can load pre-built Power BI dashboards in seconds and execute robust data analysis in minutes with these built-in connectors. You can always tweak components to your satisfaction or have your data professionals start from the beginning by importing your information and creating your dashboard and reports. If you need a nudge on how to do it, you can quickly discuss it with our Power BI consultants via this link for free. 

   2. Rapidly Deploy Decision-Support 

 With Self- service BI, Microsoft is dispelling the stereotypes that business intelligence is expensive, difficult to use and implement, and sluggish to produce significant business value. Self-service BI  provides low-cost, quickly deployable decision assistance, allowing any worker to work from a reliable and up-to-date set of data, provided in a context and detail level suited to job role and data access credentials. 

Self-Service BI:

• Makes data easier to understand 
• Adds important performance indicators to data models 
• Shares Data Insights. 
• Allows Open Source Visualizations. 

  3. Delivers Real-Time Updates 

As data is sent or streamed in, dashboards refresh in real-time. Viewers will be able to solve problems and spot possibilities due to this swiftly. Real-time data and visuals can be displayed and updated in any report or dashboard. Factory sensors, social media sources, and anything else that can collect or transmit time-sensitive data can be used as streaming data sources. 

  4. Unlock Key Data Patterns 

 Have advanced Excel users in your enterprise? The good news is they can help leverage Power BI’s familiar Power Pivot tools like clustering, forecasting, grouping, and quick measures to delve deeper into their data and uncover patterns more quickly. 

Excel users will be comfortable with the inbuilt self-service Power Query tool, making it simple to ingest, transform, integrate, and augment business data in Power BI right away. Another unnoticed benefit is that Power BI interacts smoothly with Excel, eliminating the need to export files. 

 5. Make Faster Business Decisions Using Power BI 

There’s no doubt that you can use Power BI’s disruptive capabilities to make smarter and faster business decisions. Thus you can offer more value to your business. This automated business intelligence tool can also help you achieve self-service business intelligence and boost your competitiveness. 

Taking common business data, such as an Excel spreadsheet, and translating it to Power BI, is a great way to demonstrate the platform’s worth to stakeholders. You can go even further by importing data from your company’s third-party platforms, which would otherwise be inaccessible through traditional methods. 

 6. You Can Create Custom Visuals 

Power BI has many predefined data visuals that you can benefit from in your interactive reports. You can even add an individual touch to your data by using free custom visuals produced by developers (or in-house) shared with the Power BI community. This will help you display your data in a way that best tells your data journey. 

There’s an astonishing range of rich and complicated visuals to take advantage of using custom visual files available from both Microsoft and the community over at the AppSource Marketplace, including bullet graphs, sparklines, decision trees, correlation plots, heatmaps, and more. If you want to present your data uniquely, Power BI makes it simple to generate custom visualizations rather than relying on standard options. 

   7. Ensures Compliance for your Business 

With Power BI, you can count on one of the most extensive and fastest-growing business intelligence clouds. Data visualizations can be produced and communicated across various global data centers, including regional clouds. As a result, you can rest assured that you’ll fulfill data privacy laws like HIPAA and GDDP and industry-specific rules.

Try Power BI And See The Results 

It’s clear why businesses are turning to Power BI for improved insights, dynamic dashboards, and comprehensive reporting. Most firms have already started cultivating a strong data culture and leveraging Power BI’s features. 

For your business, it’s time to take advantage of the numerous tools and services available to benefit you in preparing a booming Power BI implementation and improving data insights. If you’re thinking about embarking on a business intelligence journey and want to take your company to new heights, request a demo.