Yesterday the Power BI team released a new version of Power BI, which have included the most wanted feature ever.
The ability to share your reports outside your organisation, and easily do that. The feature was the most upvoted on the Power BI forum, and it show very clearly that Microsoft and the Power BI team is listening to the end users.
Yeah, that’s a DAX-powered, Power BI dashboard, right here in our website – a website that runs on WordPress, which is Linux for crying out loud. Don’t know what Linux is? No worries, just translate it as “there’s zero Microsoft software behind PowerPivotPro.com, and yet – BAM! Power BI, right here!”
And the dashboard in question is a near-real-time view of the traffic on this very site! Check back in an hour and you will be able to “see” yourself on the map (especially easy if you use one of the “rarer” browsers.)
Check out the technical walkthrough if you’re interested in doing something similar yourself.
However, running DMV queries against a Power BI Desktop model (which of course runs a local version of the same engine that powers Analysis Services Tabular and Power Pivot) and more importantly doing something useful with the information they return, isn’t straightforward. You can run DMV queries from DAX Studio but that will only give you the table of data returned; you need to copy and paste that data out to another tool to be able to analyse this data. Instead it’s possible to use Power BI Desktop’s own functionality for connecting to Analysis Services to connect to its own local data model and run DMV queries.
It looks like there are some limitations to this technique, but for quick and dirty work, it works.
Power BI can connect to many data sources as you know, and Spark on Azure HDInsight is one of them. In area of working with Big Data applications you would probably hear names such as Hadoop, HDInsight, Spark, Storm, Data Lake and many other names. Spark and Hadoop are both frameworks to work with big data, they have some differences though. In this post I’ll show you how you can use Power BI (either Power BI Desktop or Power BI website) to connect to a sample of Spark that we built on an Azure HDInsight service. by completing this section you will be able to create simple spark on Azure HDInsight, and run few Python scripts from Jupyter on it to load a sample table into Spark, and finally use Power BI to connect to Spark server, load, and visualize the data.
If you’re totally unfamiliar with Spark but interested in data processing, now’s a good time to start digging into the topic.
There are lots of reasons to use Power BI, other than, it’s so cool. For instance, Power BI makes it easy to see, in one glance, all the information needed to make decisions. It also allows you to monitor the most important information about your business. Power BI makes collaboration easy and when I say easy I mean EZ! You can also create customized Dashboards tailored to those C-Suite folks or make a completely different dashboard based on the same data for those that actually do the work.
I’m personally astounded at how far visualization tools have come in half a decade.
The Personal Gateway takes the data and imports it into Power BI. If you want to extract data from a variety of different places such as an Oracle Database, and Excel Spreadsheets, the Personal Gateway will support this, and the Enterprise Gateway won’t. Remember the Enterprise Gateway only connects to three different data sources, and Excel and Oracle are not on that list. If you want to manage connection and refresh of the data as the administrator or provide access to the data to everyone who needs it, use the Personal Gateway.
It sounds like these are currently different enough that “both” might be the correct option within an organization, at least until Enterprise Gateway adds the missing features.
The Microsoft Power BI team was fast and furious in 2015, and there are no indications they are slowing down in 2016. If you haven’t checked out Power BI V2 since it was first released last summer, you might want to take another look. Many features have been added and updated since then. Based upon the release schedules since July, it seems there are 3 separate release cycles for Power BI:
The Power BI Service (PowerBI.com) gets weekly updates.
The Power BI Desktop tool gets monthly updates.
The Power BI mobile apps get monthly updates.
I expect no fewer than 6 updates per week from the Power BI team.
To my surprise, Power BI only lets you put multiple values on columns in a matrix. You can’t stack metrics vertically. Note: this is true as of 8 Jan 2016 but may change in the future. If you agree that this should be a feature in Power BI, please make your voice heard and vote for this idea on the Power BI forum and encourage others to vote for it as well.
The answer is a little complex. Considering how frequently Power BI gets updated, hopefully they’ll make this a bit easier in the near future.
Not only can we create and download custom visuals from PowerBI.com to extend the capabilities of Power BI, we can use R to create a ridiculous amount of powerful visualizations. If you can get the data into Power BI, you can use R to perform interesting statistical analysis and create some pretty cool, interactive visuals.
Dustin and Jan Mulkens are working on similar posts at the same time, so watch both of them.
Jan Mulkens has started a series on combining Power BI and R.
Fact is, R is here to stay. Even Microsoft has integrated R with SQL Server 2016 and it has made R scripting possible in it’s great Azure Machine Learning service.
So it was only a matter of time before we were going to see R integrated in Power BI.
From the previous point, it seems that R is just running in the background and that most of the functionality can be used.
Testing some basic functionality like importing and transforming data in the R visual worked fine.
I haven’t tried any predictive modelling yet but I assume that will just work as well.
So instead of printing “Hello world” to the screen, we’ll use a simple graph to say hello to the world.
First we need some data, Power BI enables us to enter some data in a familiar Excel style.
Just select “Enter Data” and start bashing out some data.
I’m looking forward to the rest of the series.