If your data doesn't have intuitive column names, you can add a "synonym" to a data model -- in Desktop only -- for alternate ways to refer to a column. Click on the Relationships icon in the left panel (it's the third icon showing three boxes), select the Modeling ribbon, and you should see a Synonyms icon and list of fields to the right. If you click in the text box under Origin City, for example, you can enter additional substitute names such as Leaving.
In just a few weeks of working with Power BI, I found it to be a fairly intuitive platform for loading in data and quickly doing basic data exploration and visualization.
As of the Microsoft Data Insights Summit in March, Power BI was missing some functionality I consider basic -- text searching for slicers, conditional formatting for tables, calendar data-pickers as slicers -- but Microsoft has made progress since then on improving the platform. Conditional formatting for tables was added in the May 31 desktop update, searchable slicers arrived in the June 30 update and Microsoft says better date-range pickers are in the works.
The platform is being updated fairly frequently -- once a month for the Desktop, more often for the cloud service -- offering the promise of continued new features and functionality. And as an R user, I'm intrigued by the integration of R scripts within the software and Microsoft's recent announcement R graphics in the Power BI service (Pro account needed) -- although you definitely don't need to know or use R for Power BI.
If you already use Excel -- especially on Windows -- or are otherwise a Microsoft shop with corporate data stored in Microsoft infrastructure, I'd recommend downloading Power BI, signing up for a free account and taking Power BI for a test drive. If you don't use other Microsoft products, it may still be worthwhile to try the platform if you want to do some quick data exploration and analysis and don't currently have a favorite platform, since Power BI will pull in a lot of other data formats besides spreadsheets, SQL Server and Microsoft Azure.
While I was somewhat underwhelmed with the two online Content Pack data connections I tried (Adobe Analytics and Google Analytics), largely because they didn't cover long-term site content trends, that's not to say some of the others like Salesforce or MailChimp wouldn't work for you. And Microsoft is developing what it calls enterprise-class "solution templates" -- there are a couple of offerings for Salesforce and Dynamics CRM, for example -- that are aimed to make it easier to gear up corporate analytics reporting. (Microsoft says that Content Pack publishers are typically responsible for what scenarios to focus on.)
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