Last year, Microsoft added a preview connector enabling Power BI to query Amazon Redshift. This wasn’t publicised as an “official” data source, and took some steps in order to be able to even see the connector in Power BI Desktop. Crucially, you could only use this connector in Power BI Desktop, not when workbooks are deployed to the cloud. Yesterday, Microsoft announced the connector is now available within the Power BI Service, which means that workbooks containing Redshift data connections can now be deployed to the cloud. I’ve been working a lot with Redshift over the past year or so, and Power BI’s still my go-to data-viz solution, so I’m delighted to see the this announcement, as it means that Redshift-based workbooks can now be shared with others via powerbi.com.

Late last night, Amazon announced that their proprietary AWS data visualisation tool, Quicksight was now generally available in the US and Ireland. Quicksight aims to be a PowerBI-esque drag and drop visualisation tool, that allows you to access your data from AWS (and other sources) in seconds, regardless of scale. I’ve had a very quick go this morning, and visualised some data from a modest 1TB Redshift cluster after just a few minutes. The biggest challenge was finding out the correct IP range for Quicksight to enable access to my VPC (Thank you serverfault).

Ever since getting my hands on some Opta data, courtesy of Manchester City’s Analytics challenge all the way back in August 2012, I’ve been wanting to try something different with the data. Although it’s taken me over a year to get around to doing it, I’d initially thought of the idea of doing some kind of Network Graph to explore how the players were interconnected throughout a match, and potentially over an entire season. Since starting to play with Gephi some time ago, I figured it would be perfect for the job.

I’ve been meaning to write something on Power BI for a long time now, and I’m a little late in getting round to writing this, as most of the dust has already settled after Microsoft sent out the first round of invites to the Power BI for Office 365 preview, and a lot of people have produced some amazing work with Power BI. Chris Webb has written a pretty comprehensive review on his blog, as have countless others.

After launching a number of really neat self-service business intelligence plugins and components over the past couple of years, Microsoft has finally announced their complete self-service BI package: Power BI for Office 365. Incorporating Microsoft’s four big self-service BI components of the past year or so; PowerPivot, PowerView, Data Explorer and GeoFlow, the Power BI suite combines these parts into a single, unified offering. Most exciting of all though, is the inclusion of a mobile application for either Windows (I’m assuming Win 8) or iPad, which could very well be the secretive “Project Helix”, revealed at last year’s SharePoint Conference.

The other week, Microsoft announced GeoFlow for Excel 2013 at the SQL PASS Business Analytics conference in Chicago. While it’s not exactly new, it is at least, a pretty impressive looking addition to the data visualisation toolkit.

However, while GeoFlow finally brings 3D geographical visualisation to Microsoft’s self-service BI utility belt (in your face, Batman), it’s hard to make a case for it for any purpose except wowing executives and potential clients.

I recently posted some thoughts regarding Microsoft’s Windows-compatible Hadoop implementation, HDInsight. I was investigating it for a project that I figured would benefit from a distributed processing approach, although ultimately decided to pursue other alternatives. It led our team to make some quite interesting discoveries about Hadoop, and some scenarios of when current distributed processing solutions are and aren’t appropriate.

Hadoop. Everyone and their dog is talking about it. That and “Big Data”. There was an excellent post on Brent Ozar’s DBA Reactions Tumblr blog recently that encapsulated it perfectly, titled “When the executives ask if we’re Hadooping”. It’s a valid point though, Hadoop is mentioned in just about every article these days, along with the phrase “Big Data” (which I personally don’t like at all). The consensus, at least on the surface, seems to be that Hadoop will solve everyone’s problems, process anything, oh and bring world peace while it’s doing that. My sarcastic tone belies a genuine interest in playing about with it though. With so many people talking about Hadoop (in its many implementations), I was very keen to get an opportunity to try it for myself.