Why I don’t buy the Big Data “Red Hat of Hadoop” Story

Great read!!

Emergent Business Networks

It’s official. As of 19 August 2013, Big Data has officially past the “peak of inflated expectations” and is hurtling down the rollercoaster ride to the “trough of disillusionment”. Hold on tight boys and girls, this will be a white knuckle ride. This is the point when the rollercoaster reaches the top and you sense the change and then hear the screams as you hurtle down.

Its official because Gartner, who coined the hype cycle, declared it so. They maybe right or wrong, but it’s certainly official (and official does impact reality in Enterprise-Land).

Its not your first time on a rollercoaster, so you knew the top was coming, right? Plenty of smart folks have been predicting this. Robin Bloor for example was articulate, analytical and ahead of the curve on this in 2012.

The problem with the Big Data hype phase was that most of the energy was used…

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SSAS on Windows Azure Virtual Machines

Chris Webb's BI Blog

You may have already seen the announcement about Windows Azure Virtual Machines today; what isn’t immediately clear (thanks to Teo Lachev for the link) is that Analysis Services 2012 Multidimensional and Reporting Services are installed on the new SQL Server images. For more details, see:

SSAS 2012 Tabular is also supported but not initially installed.

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GeoFlow Public Preview Available

Chris Webb's BI Blog

First big news from the PASS BA Conference: the public preview for GeoFlow is now available. You can download it here:

Here are the official announcements with all the details:

GeoFlow is an addin for Excel 2013 that allows you to visualise your data on a 3D map, to zoom in and explore that data, and record ‘tours’ of this data. It’s a lot of fun! As a taster, here’s a screenshot of a visualisation showing English secondary schools exam results data (average A-Level point score per pupil) broken down by school gender of entry:


UPDATE: one other thing I have to mention is that when this was announced in the keynote at the PASS BA Conference this morning, Amir Netz did an absolutely astounding demo showing GeoFlow’s touch-based capabilities running on a massive Perceptive Pixel screen (I think it was this one: http://www.perceptivepixel.com/products/82-lcd-multi-touch-display). It was…

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SAP Visual Intelligence vs. Microsoft PowerPivot and PowerView

business intelligist

In this post I will review the latest version of SAP Visual Intelligence – 1.08 – and see how it stacks up against the Microsoft self-service BI tools, Excel, PowerPivot and PowerView. In the initial release, Visual Intelligence only supported SAP Hana, but in its latest iteration few other data sources are supported:

  1. CSV File
  2. SAP Hana
  3. SAPBW as exposed as a view in SAP Hana
  4. MS Excel
  5. Freehand SQL (basically ODBC)
  6. SAP Business Objects Universe

Just to clear some confusion that this list may generate, Visual Intelligence does not access BW objects directly, instead, Hana has some connectivity to connect to BW models, DSOs and Query Snapshots and then expose those as a Hana view, in short, Visual Intelligence knows how to plug into Hana but not BW.

Data import

Since I don’t have Hana running on my laptop, I decided to use a CSV file to load in…

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Alessandro Alpi's Blog

Usually I found some questions on the forums about that topic. For instance:

  1. “WHERE or HAVING?”
  2. “Is the ON clause more efficient than the WHERE clause?”
  3. “Why the field aliases cannot be used with the GROUP BY clause?”
These three questions are syntax oriented. Actually there are a lot of requests about subqueries, temporary objects, sort operations and so on. This kind of questions can be replied reading this logical process document (pdf). I love it and I share it everywhere, also when training in classes/on the job.
It is a LOGICAL workflow used by the Query Processor in order to generate the related PHYSICAL process for retrieving data.

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business intelligist

Microsoft once again is ranked the highest in its ability to execute by Gartner in its magic quadrant for Business Intelligence.  The report is pretty long and boring, but if I were distill it down to a few salient points, I would choose the following:

  1. Companies see a dramatic improvement in BI capabilities going from SQL Server 2008 R2 to SQL Server 2012
  2. Microsoft got a node for some of the upcoming stuff including Explorer, GeoFlow and PolyBase
  3. Gartner mentioned “shortening product update cycles” for Microsoft SQL, Office and Sharepoint
  4. “it is widely deployed in large enterprises as a standard with among the highest data volumes and user counts”
  5. Microsoft is dinged on basically two fronts, mobility and CPM.

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Tableau from a SQL Server guy – Part 2

As I mentioned in my previous post, I have been playing with Tableau Desktop in my spare time. I am just experimenting with it and there are no structured instructions that I am following. In this post, I intend to connect to Excel data source and do some analysis. I chose the sample excel provided by Tableau which is mostly located in “My Documents\My Tableau Repository\Datasources\Sample – Superstore Sales (Excel).xls”. Once connected, Tableau will try to create Dimensions and Measures for you. It seems like, all the numeric field are converted to measures and string fields are converted to dimensions. To test my theory, I added two columns in the source excel. One called Sales Category with string values and other Weight with numeric values. Sure enough Sales Category became a dimension and Weight became a measure.

Strings are converted to dimensions and numeric values are converted to measures

Strings are converted to dimensions and numeric values are converted to measures

You will also observe a small icon beside each field. The icon kind of represents the data type. For e.g. ‘Abc’ means it’s a character data, a # represents numeric field. There are certain special icons. For e.g. a little globe means the field has something to do with geography data, small square with clock is date/time field, that chart like thing is a bin(more on this later) and pin is Group (again more on that later). You can change data type by right clicking on the field  and selecting Change Data Type. You can move stuff from measures to dimensions and vice a versa (of course if it makes sense!). For e.g. Order Id in measures does not make much sense, you can drag it to dimension panel and it will become a dimension. My gut feeling is that measure is treated just like another dimension, something similar to what SQL Server 2012 Tabular does. Creating a hierarchy is simple enough. Right click on a field from dimension panel and select create hierarchy. Drag the fields under the hierarchy name.



Coming to the bins and groups part mentioned above. I was a bit puzzled and struggled to get my head around the concept. Once I got hang of it, its is one of my favourite features. Bins are like buckets of data or data groups. For e.g you have a persons age as measure, you can group it in bins of 0-10,10-20,20-30 and so on or as ‘Kids’,’Adults’ etc. This tutorial is a good starting point.

That’s it for this post. In the next post, I am going to try to answer some questions based on some interesting datasets I have found using Tableau. So stay tuned!!