What you need to know about Microsoft’s Power BI now
Come microservice, come cloud, the line-of-business application is always going to be with us. We need to know how our businesses are working: how much we’re selling, how much we’re buying, how our customers are feeling, and every one of a thousand little markers that show the pulse of business.
And that leaves us with the ever-present question: How do we show that information? That’s where business intelligence tools come in, to let us ask questions and get answers, exploring the ever-growing pool of business data we’re storing in our myriad business systems.
Microsoft’s tool for that business data exploration is Power BI, even if you didn’t realize that.
After all, Power BI began life as a set of extra query tools for Excel, taking tabular data and helping you slice and dice it before delivering well-formatted graphical answers. It could connect to SQL Server’s OLAP tool, acting as a familiar (if not user-friendly) user interface to billions of rows of data.
Now a full-fledged web service and a companion desktop app, Power BI is a standalone analytics tool that keeps much of the familiar Excel way of working but adds its own tools. With natural language tools for querying data, you can ask questions and get answers—via the Cortana voice interface if you like. Power BI’s machine learning-powered features also help identify interesting data, guide visualizations of trends, and point out outliers in your data.
Power BI is an interesting mix of software-as-a-service and desktop app. You can use the desktop app to explore your data and build reports; but it’s the combination of app and cloud service that really makes sense.
It’s best to think of the desktop Power BI app as a way to get initial insights, where you find out the right questions to ask. You can turn the resulting report into a live dashboard on the cloud service, connected to live data and giving near-real-time analytics of trends and indicators.
One of Power BI’s more useful features is the sheer number of data sources it can use: from traditional databases and spreadsheets to modern SaaS services like Zendesk and Github. Business data now resides in so many different places that it’s difficult to be sure what’s relevant, so it’s good to be able to query as many of the repositories as possible. You can even connect Power BI to the statistical language R, using it to display complex statistical information on a range of charts.
In Power BI, you can also use public data with your own information. By mixing public and private data, you can put business information in context. If sales are dropping, is that because your sales team isn’t doing its job, or is there a general slowdown in your business sector? And if there is a sector slowdown, are you performing better than expected, or worse? The more information you have, the better the decisions you’ll make.
Building queries and data transformations is easy enough in Power BI.
