Over the years I have presented many times to various clients describing Business Intelligence (BI) solutions using the Microsoft BI solutions stack.
In all of my sessions, regardless of the specific focus, each time I always start with the same 2 content slides.
- The first is always the positioning graphic from the Gartner Magic Quadrant for Business Intelligence & Analytics. This shows all top BI vendors and how they are positioned against each other, and is republished yearly (typically in Feb). This is often a great introduction as to why Microsoft BI is such a great play. If interested an introduction to the paper is here, but you can also find the full report on various web sites (https://www.gartner.com/doc/2989518/magic-quadrant-business-intelligence-analytics)
- The second is always a definition of exactly what Business Intelligence (BI) actually is, and this is the purpose of this short blog.
And so, lets dig down into a business definition for Business Intelligence!
So PASS officially kicked off this morning leading into the next 3 days of back to back sessions.
You could certainly tell that the keynote was on… I mean the dining room was pumping…!
Oh that’s right, everyone is at the keynote!
So the Keynote session was hosted by Joseph Sirosh Group Vice President, Data Group.
The big tell for the key note was undoubtedly the SQL Server 2016 CTP3 and just whats packed to the rafters within the software. If you want to learn more about that then I recommended step across to this link here http://blogs.technet.com/b/dataplatforminsider/archive/2015/10/28/sql-server-2016-everything-built-in.aspx
Key Takeaways from the Keynote;
- SQL 2016 is really a major release that really solidifies the Microsoft view of a solid foot in both the On Prem and In Cloud data platform camps.
- “The future is both earth and sky!”
- The release offers much On Prem capability like Polybase (to APS), R integration (advanced analytics), Always Encrypted, SSAS/SSRS improvements
- The release also provides the ability to seamlessly integrate from On Prem to Azure Cloud – and/or back like Polybase (to HDInsight), Stretch Database – and SQL already has capability to use Azure VM’s for SQL AAG solutions and Azure backups.
- An interesting takeaway – the human size of human genome is approx 1.5 Gigabytes, or about 2 CDs worth of storage space. How small do you feel now?
I then attended 4 sessions, but today there is really only time to blog about this one, mostly for me it was the most impressive in regards to capability and just how far its come!
The session was SQL Server in Azure Virtual Machines – Features and Best Practices and was presented by Luis Vargas is a Senior Program Manager Lead in the SQL Server team.
Its time to take a well deserved 1/2 time break in my 8 part post series on SQL Partitioning and so I have decided to take a slight “light-hearted” tangent and talk about visualisations, or more specifically Pie Chart visualisations.
In all seriousness, this actually came up as I overheard a conversation at a client site debating the usage of this very visualisation.
Now – If you believe everything you read on the Internet about Pie Charts you may begin to think they are the proverbial trouble-maker of the BI World, but I believe that they deserve a chance to prove themselves!
So to prop up my rickety case, this post will explore Pie Chart Visualization Best Practices and then compare the default Pie Chart visualization from 10x industry leading BI/Reporting Tools to see how they stack up against this Best Practice list.
And so, lets get into the nitty gritty of creating and eating pie charts!