Happy New 2011 Year!

Happy holidays to visitors of this blog and my best wishes for 2011! December 2010 was so busy for me, so I did not have time to blog about anything. I will just mention some news in this last post of 2010.

Tableau sales will exceed $40M in 2010 (and they planning to employ 300+ by end of 2011!), which is almost 20% of Qliktech sales in 2010. My guesstimate (if anybody has better data, please comment on it) that Spotfire's sales in 2010 are about $80M. Qliktech's market capitalization exceeded recently $2B, more than twice of Microstrategy ($930M as of today) Cap!

I recently noticed that Gartner trying to coin the new catch phrase because old (referring to BI, which never worked because intelligence is attribute of humans and not attribute of businesses) does not work. Now they are saying that for last 20+ years when they talked about business intelligence (BI) they meant an intelligent business. I think this is confusing because (at least in USA) business is all about profit and Chief Business Intelligent Dr. Karl Marx will agree with that. I respect the phrase "Profitable Business" but "Intelligent Business" reminds me the old phrase "Crocodile tears". Gartner also saying that BI projects should be treated as a "cultural transformation" which reminds me a road paved with good intentions.

I also noticed the huge attention paid by Forrester to Advanced Data Visualization and probably for 4  good reasons (I have the different reasoning, but I am not part of Forrester) :

• data visualization can fit much more (tens of thousands) data points into one screen or page compare with numerical information and datagrid ( hundreds datapoints per screen);


• ability to visually drilldown and zoom through interactive and synchronized charts;


• ability to convey a story behind the data to a wider audience through data visualization.


• analysts and decision makers cannot see patterns (and in many cases also trends and outliers) in data without data visualization, like 37+ years old example, known as Anscombe’s quartet, which comprises four datasets that have identical simple statistical properties, yet appear very different when visualized. They were constructed by F.J. Anscombe to demonstrate the importance of Data Visualization (DV):

Anscombe's quartet

I		II		III		IV
x	y	x	y	x	y	x	y
10.0	8.04	10.0	9.14	10.0	7.46	8.0	6.58
8.0	6.95	8.0	8.14	8.0	6.77	8.0	5.76
13.0	7.58	13.0	8.74	13.0	12.74	8.0	7.71
9.0	8.81	9.0	8.77	9.0	7.11	8.0	8.84
11.0	8.33	11.0	9.26	11.0	7.81	8.0	8.47
14.0	9.96	14.0	8.10	14.0	8.84	8.0	7.04
6.0	7.24	6.0	6.13	6.0	6.08	8.0	5.25
4.0	4.26	4.0	3.10	4.0	5.39	19.0	12.50
12.0	10.84	12.0	9.13	12.0	8.15	8.0	5.56
7.0	4.82	7.0	7.26	7.0	6.42	8.0	7.91
5.0	5.68	5.0	4.74	5.0	5.73	8.0	6.89

In 2nd half of 2010 all 3 DV leaders released new versions of their beautiful software: Qlikview, Spotfire and Tableau. Visokio's Omniscope 2.6 will be available soon and I am waiting for it since June 2010... In 2010 Microsoft, IBM, SAP, SAS, Oracle, Microstrategy etc. all trying hard to catch up with DV leaders and I wish to all of them the best of luck in 2011. Here is a list of some other things I still remember from 2010:

• Microsoft officially declared that it prefers BISM over OLAP and will invest into their future accordingly. I am very disappointed with Microsoft, because it did not include BIDS (Business Intelligence Development Studio) into Visual Studio 2010. Even with release of supercool and free PowerPivot it is likely now that Microsoft will not be a leader in DV (Data Visualization), given it discontinued ProClarity and PerformancePoint and considering ugliness of SharePoint. Project Crescent (new visualization "experience" from Microsoft) was announced 6 weeks ago, but still not too many details about it, except that it mostly done with Silverlight 5 and Community Technology Preview will be available in 1st half of 2011.


• SAP bought Sybase, released new version 4.0 of Business Objects and HANA "analytic appliance"
  


• IBM bought Netezza and released Cognos 10.


• Oracle released OBIEE 11g with ROLAP and MOLAP unified
  


• Microstrategy released its version 9 Released 3 with much faster performance, integration with ESRI and support for web-serviced data


• EMC bought Greenplum and started new DCD (Data Computing Division), which is obvious attempt to join BI and DV market


• Panorama released NovaView for PowerPivot, which is natively connecting to the PowerPivot in-memory models.


• Actuate's BIRT was downloaded 10 million times (!) and has over a million (!) BIRT developers


• Panopticon 5.7 was released recently (on 11/22/10) and adds the ability to display real-time streaming data.
  

David Raab, one of my favorite DV and BI gurus, published on his blog the interesting comparison of some leading DV tools. According to David' scenario, one of possible ranking of DV Tools can be like that: Tableau is 1st than  Advizor (version 5.6 available since June 2010), Spotfire and Qlikview (seems to me David implied that order). In my recent DV comparison "my scenario" gave a different ranking: Qlikview is slightly ahead, while Spotfire and Tableau are sharing 2nd place (but very competitive to Qlikview) and Microsoft is distant 4th place, but it is possible that David knows something, which I don't...

In addition to David, I want to thank  Boris Evelson, Mark Smith, Prof. Shneiderman, Prof. Rosling, Curt Monash, Stephen Few and others for their publications, articles, blogs and demos dedicated to Data Visualization in 2010 and before.

Permalink: http://apandre.wordpress.com/2010/12/25/hny2011/

Columnstore index in SQL Server 11.0 will accelerate DW queries by 100X

Microsoft reused its patented VertiPaq column-oriented DB technology in upcoming SQL Server 11.0 release by introducing columnstore indexes, where each columns stored in separate set of disk pages. Below is a "compressed" extraction from Microsoft publication and I think it is very relevant to the future of Data Visualization techologies. Traditionally RDBMS uses "row store" where



heap or a B-tree contains multiple rows per page. The columns are stored in different groups of pages in the columnstore index. Benefits of this are:

• only the columns needed to solve a query are fetched from disk (this is often fewer than 15% of the columns in a typical fact table),


• it’s easier to compress the data due to the redundancy of data within a column, and


• buffer hit rates are improved because data is highly compressed, and frequently accessed parts of commonly used columns remain in memory, while infrequently used parts are paged out.

"The columnstore index in SQL Server employs Microsoft’s patented Vertipaq™ technology, which it shares with SQL Server Analysis Services and PowerPivot. SQL Server columnstore indexes don’t have to fit in main memory, but they can effectively use as much memory as is available on the server. Portions of columns are moved in and out of memory on demand." SQL Server is the first major database product to support a pure Columnstore index. Columnstore recommended for fact tables in DW in datawarehouse, for large dimensions (say with more than 10 millions of records) and any large tables designated to be used as read-only.

"In memory-constrained environments when the columnstore working set fits in RAM but the row store working set doesn’t fit, it is easy to demonstrate thousand-fold speedups. When both the column store7and the row store fit in RAM, the differences are smaller but are usually in the 6X to 100X range for star join queries with grouping and aggregation." Your results will of course depend on your data, workload, and hardware. Columnstore index query processing is most heavily optimized for star join queries. OLTP-style queries, including point lookups, and fetches of every column of a wide row, will usually not perform as well with a columnstore index as with a B-tree index.

Columnstore compressed data with a factor of 4 to a factor of 15 compression with different fact tables. The columnstore index is a secondary index; the row store is still present, though during query processing it is often not need, and ends up being paged out. A clustered columnstore index, which will be the master copy of the data, is planned for the future. This will give significant space savings.

Tables with columnstore indexes can’t be updated directly using INSERT, UPDATE, DELETE, and MERGE statements, or bulk load operations. To move data into a columnstore table you can switch in a partition, or disable the columnstore index, update the table, and rebuild the index. Columnstore indexes on partitioned tables must be partition-aligned. Most data warehouse customers have a daily, weekly or monthly load cycle, and treat the data warehouse as read-only during the day, so they’ll almost certainly be able to use columnstore indexes.You can also create a view that uses UNION ALL to combine a table with a column store index and an updatable table without a columnstore index into one logical table. This view can then be referenced by queries. This allows dynamic insertion of new data into a single logical fact table while still retaining much of the performance benefit of columnstore capability.

Most important for DV systems is this statement: "Users who were using OLAP systems only to get fast query performance, but who prefer to use the T-SQL language to write queries, may find they can have one less moving part in their environment, reducing cost and complexity. Users who like the sophisticated reporting tools, dimensional modeling capability, forecasting facilities, and decision-support specific query languages that OLAP tools offer can continue to benefit from them. Moreover, they may now be able to use ROLAP against a columnstore-indexed SQL Server data warehouse, and meet or exceed the performance they were used to in the past with OLAP, but save time by eliminating the cube building process". This sounds like Microsoft finally figured out of how to compete with Qlikview (technology-wise only, because Microsoft still does not have - may be intentionally(?) - DV product).

Permalink: http://apandre.wordpress.com/2010/12/03/columnstore-index/

SAP HANA scales linearly

SAP released HANA today which does in-memory computing with in-memory database. Sample appliance with 10 blades with 32 cores (using XEON 7500) each; sample (another buzzword: "data source agnostic") appliance costs approximately half-million of dollars. SAP claimed that"Very complex reports and queries against 500 billion point-of-sale records were run in less than one minute" using parallel processing. SAP HANA "scales linearly" with performance proportional to hardware improvements that enable complex real-time analytics.

Pricing will likely be value based and that it is looking for an all-in figure of around $10 million per deal. Each deal will be evaluated based upon requirements and during the call, the company confirmed that each engagement will be unique (so SAP is hoping for 40-60 deals in pipeline).

I think with such pricing and data size the HANA appliance (as well as other pricey data appliances) can be useful mostly in 2 scenarios:

• when it integrates with mathematical models to enable users to discover patterns, clusters, trends, outliers and hidden dependencies and


• when those mountains of data can be visualized, interactively explored and searched, drilled-down and pivot...

8/8/11 Update: The 400 million-euro ($571 million) pipeline for Hana, which was officially released in June, is the biggest in the history of Walldorf, Germany-based SAP, the largest maker of business-management software. It’s growing by 10 million euros a week, co-Chief Executive Officer Bill McDermott said last month. BASF, the world’s largest chemical company, has been able to analyze commodity sales 120 times faster with Hana, it said last month. Russian oil producer OAO Surgutneftegas, which has been using Hana in test programs since February, said the analysis of raw data directly from the operational system made additional data warehouse obsolete.

Permalink: http://apandre.wordpress.com/2010/12/01/sap-hana/