In my last articles on Power BI Desktop (see the index at the bottom of the article), we have explored that Power BI has a rich set of visualizations. We can present data using various custom visuals available from Microsoft AppSource. These visuals are available free to download and use it as per our requirements.
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In this article, we’ll look at how to create a Word cloud generator in Power BI Desktop, including importing data, customization and more.
In my last article, Power BI Desktop Interactive chord diagrams, we learned about customized visualizations in Power BI Desktop. These visualizations are free to install and we can use them with our data set and customize charts as per our requirements.
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In my last article, Power BI Desktop Interactive chord diagrams, we underscored that Microsoft Power BI desktop has a rich set of customized visualization features. These visualizations can help to produce convert data to information in an efficient manner to an easy to understand format. We can freely download them from Microsoft AppSource
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Power BI desktop helps to create interactive reports and dashboards from a high and complex volume of the data. The Power BI desktop is an integrated tool where we can get the data from different sources.
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Every once in a while, teams from different functional areas of the business (i.e. business intelligence, software development, web development etc.) would join forces to form a cross-functional development team with a common goal of integrating a business intelligence artefact such as a SQL Server Reporting Services (SSRS) report into a front-end web application. There are many reasons for forming such a partnership including a lack of report-development skill by web developers, BI team owns a better reporting tool for data visualization, or maybe to prevent the software team from “reinventing the wheel” by developing a report that has already been produced elsewhere.
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Over the past three years, I read some interesting news about Microsoft which was “Microsoft acquires mobile business intelligence leader Datazen”. This news made me excited because showing Reporting Service reports in mobile devices can be painful and often not effective for end users. After this acquisition, Microsoft developers worked quickly to adapt the Datazen application to SQL Server Reporting Services and this effort culminated in Microsoft SQL Server Mobile Report Publisher.
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There is a growing trend among professionals and entire companies to move away from email as a primary means of communication and are even adopting alternative technologies. One of the most popular of these is Slack. Slack is a new kind of messaging and communication platform between colleagues, team or community members that allows them to integrate a lot of services including Visual Studio Team Service, Jira and GitHub.
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When I watched the 2018 FIFA World Cup Russia match, at the end of the match I saw a very interesting and stunning soccer field heat map analysis. After this, I decided to create a soccer field heat map in Power BI. So I wrote this article!
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The concept of the IOT (Internet of Things) is that every object that you might think of is somehow accessed and connected to other devices on the internet. Nowadays every electronic device is now becoming smart and these devices are now able to communicate with each other. Many ideas and technology on IOT are being developed and are even being used today.
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With the popularity of social networking and sharing sites and their widespread availability, internet marketing techniques have also been rapidly influenced. Sharing sites with high visitor traffic offers great potential for advertisers, so much so that it is almost unheard of now that brands or products do not have a profile or group on a social networking site. Markets have the opportunity to communicate directly with consumers by creating profiles or groups in sharing sites. Thanks to the comments and forums on the pages, they are able to follow both positive and negative attitudes of the target groups about themselves and thus have more precise ideas about what to do next.
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In this article, we will discover how to find the associations and hidden patterns in a dataset. The tool we will use for this is Power BI and not use any statistical functions or calculation.
Power BI is one of the most powerful business intelligence solutions in the market. A cloud-based, user-friendly interface and basic development abilities provide this solution to be more convenient for people to use.
As you may know, Microsoft now supports R script in SQL Server and Power BI. R script support opens magical gates of statistics world to Power BI. Custom Visual offers very useful and interesting visual components for Power BI. In this store, many useful visualizations have been created by Microsoft or the community itself. Some of these visuals use R script infrastructure and this feature allows us to create advanced visual analytic in Power BI. Only a Power BI account is enough to connect and download theses visuals. We will use these visuals in our examples.
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In the article How to plot a SQL Server 2017 graph database using SQL Server R, I highlighted the lack of built-in graph data visualisation as one major limitation of the SQL Server 2017 graph database feature. In the same article, I went on to suggest making use of SQL Server R as one workaround that could be utilised in order to successfully plot and visualise diagrams out of SQL Server 2017 graph database objects. However, whilst 3rd party graph database vendors such as Neo4j provide an interactive and hyperlinked graph diagrams that allows you to – amongst other things – easily drilldown and identify node-relationships as indicated in Figure 1, the graph plotted using SQL Server R is not very interactive in fact it is simply a static image file as shown in Figure 2.
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As I covered in a previous post How to connect to (and query) Power BI and Azure using PowerShell, Power BI can be difficult to manage and administer, unlike on-premises BI solutions. One such concern that will often require quick action is the failure of a dataset refresh.
If your reports and dashboards all rely on live connection or DirectQuery data sources like Azure SQL Database, Azure SQL Data Warehouse or SQL Server Analysis Services (on-premises or in Azure) then you won’t have to worry about dataset refreshes and this post will just be some interesting reading.
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This is the fourth article of a series dedicated to discovering geographic map tools in Power BI.
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This is the third article of a series dedicated to discovering geographic maps in Power BI.
In the ToC below the article you can find out references to the previous articles and the project’s goal.
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Introduction
This is the second article of a series dedicated to discovering geographic map tools in Power BI.
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Power BI is a self-service business intelligence tool from Microsoft which has been steadily gaining momentum in the last couple of months. One of the well-known disadvantages of Power BI is that it is basically cloud only. A lot of companies are not yet at the point where they feel comfortable having their data in the cloud or are premise bound for some other reasons such as data-sensitivity, data-sovereignty or compliance.
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Whether you’ve been using PowerBI for a while or you’re just getting started with it, chances are you’ll want to source at least some of your data from on-premises systems. Be that SQL server databases, Oracle, SSAS etc. The same process even applies if you’re sourcing from AWS which I’ll go into in more detail below. All of these data sources will require Microsoft’s On-Premises Data Gateway.
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This is the first article of a series dedicated to discovering geographic maps in Power BI using Bubble Map and Filled Map.
My goal is to illustrate to you the different visuals available in Power BI for making maps. Remember that Power BI is a product undergoing constant evolution; new features are added every month at a fast pace. And over time Power BI has gained more mapping capabilities compared to the starting point.
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Power BI is an extremely popular new Microsoft Tool to create reports. In a previous article, we talked about Power BI Cloud based services. In that article, we connected from a SQL Azure Data Warehouse database to the Power BI Cloud services. In this new article, we will work with the Power BI Desktop Tool from zero. The Power BI Desktop is a reporting software that can be installed in your Windows machine to create reports locally and connect to different data sources like Azure, SharePoint, Active Directory, Exchange, Facebook, Google Analytics and many other data sources. We will create Reports from a SQL Server database and finally we will extract information from Facebook. With Power BI, you can easily access to maps at street level around the world.
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Power BI is an extremely powerful tool to create dashboards and reports. In the last article, we learned how to create a Data Warehouse in Azure. In this new chapter, we will learn how to create reports from the Data Warehouse in Azure using Power BI in Azure.
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