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Richard Hackathorn

Welcome to my blog stream. I am focusing on the business value of low latency data, real-time business intelligence (BI), data warehouse (DW) appliances, use of virtual world technology, ethics of business intelligence and globalization of business intelligence. However, my blog entries may range widely depending on current industry events and personal life changes. So, readers beware!

Please comment on my blogs and share your opinions with the BI/DW community.

About the author >

Dr. Richard Hackathorn is founder and president of Bolder Technology, Inc. He has more than thirty years of experience in the information technology industry as a well-known industry analyst, technology innovator and international educator. He has pioneered many innovations in database management, decision support, client-server computing, database connectivity, associative link analysis, data warehousing, and web farming. Focus areas are: business value of timely data, real-time business intelligence (BI), data warehouse appliances, ethics of business intelligence and globalization of BI.

Richard has published numerous articles in trade and academic publications, presented regularly at leading industry conferences and conducted professional seminars in eighteen countries. He writes regularly for the BeyeNETWORK.com and has a channel for his blog, articles and research studies. He is a member of the IBM Gold Consultants since its inception, the Boulder BI Brain Trust and the Independent Analyst Platform.

Dr. Hackathorn has written three professional texts, entitled Enterprise Database Connectivity, Using the Data Warehouse (with William H. Inmon), and Web Farming for the Data Warehouse.

Editor's Note: More articles and resources are available in Richard's BeyeNETWORK Expert Channel. Be sure to visit today!

Recently in 20081012TD-Partners Category

TD-P%20logo.jpgI am back in the office, escaped Las Vegas (at least for a week), and reflecting on the conference.

My first thought is that there was so much I missed. The last session was Three Crabby Old Men Predicting the Future of BI. I missed it because I had a plane to catch! aaaarrrrgggggg Someone please send me an audio of that session, please!

My second thought is that there were so many colleagues with whom I missed talking. The BI network surrounding Teradata (and other key vendors) is awesome! It is an exciting time for the BI community. There is a blending of ecosystems into a global community of professionals. Oh, how I wish that TDWI was a non-profit professional association. We really need an ACM-like entity to glue us together professionally.

A third thought is for the next generation of BI professionals. There are a lot of crabby old folks (like me) who are slowing down and need to pass the baton to the next generation. I know...speak for myself, since many of my 'old' friends were at those crap tables until 3am. The 30-ish BI professionals that I know are amazing - energy, enthusiasm, caring. We (the crabby old BI folks) need to provide them a springboard so that they can stand on our shoulders.

Finally, I am concerned about BI technology. We now have more power than we know how to manage. In some ways, it was good that we were constantly fighting the technology in the old days. It kept us focused on priorities and limited our ability to really screw things up. No more do we have that luxury! The issues surrounding the proper application of BI technology are deep and largely undiscussed. Is it ethical to do deep data mining on our customers? Is that not the same as a X-ray machine that reveals our intimate body parts at the public airport?

So, those are a few reflects from yet another BI conference. Bye until the next conference (in a week).

[Blog stream from the Teradata Partners Conference is here.]

Posted October 17, 2008 7:25 AM
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TD-P%20logo.jpgI spent several hours roaming the exhibit floor, mainly catching up with old friends at various companies. A new company that appear surprisingly was founded by an old friend - Andrew Cardno of former Compudigm fame. Andrew is quite a visionary when it comes to data visualization. In our conversation, he said that his goal is to make "the data warehouse a piece of art." If you know Andrew, you realize that this statement was made with total passion and conviction, void of any humorous connotation.

We all know that visual perception is our strongest sensory function accounting for 70% of all the information we perceived from the real world. So, what's new?

Andrew is blasting us with information in artfully done visual designs that highlight key dimensions, like time, spatial, hierarchies, and the like. He said, "Data should explode in our minds." In one glance, we should visualize both the overview and detail inherent in the data.

For the most part, the visualization consists of the raw data, cleanse and structured as it should be in any proper EDW. It is not images of aggregations or other analytics whose computations are hidden from the perceiver. Every bit hangs out there in the open! Maybe Andrew should rename his tool as the Data Nudist Colony. No clothing allowed on those bits! View six years of XXX revenue data in a glance.

Take a look at Andrew's new company BIS2 (Business Intelligence Systems Software). It is strictly a GP-rated site. They are still emerging, which is a nice way of saying that the product/service is not shipping. However, they have several beta sites in operation. And for a LV-size fee, they will performed a two-week magic show just for you. This is one company to watch.

[Blog stream from the Teradata Partners Conference is here.]

Posted October 16, 2008 8:23 AM
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Speakers were Stephen Brobst, CTO of Teradata, and Paul Kent, VP of Platform R&D for SAS Institute. I was especially curious about his session because of the visibility placed on the SAS partnership at this Teradata conference. This was an overview of joint development work between Teradata and SAS. Where they are going, and why we should be excited about it?

There are technology barriers that limited our ability to use advanced analytics. We need to stop copying/moving the data and eliminate the need of a Ph.D. to analyze the data.

The solution is to do in-database processing. If you have lots of data, keep it there! The old world has separate data marts and MOLAP cubes. The new world is to leverage SQL and parallel database engines. Teradata is extending its features because SQL is limited for advanced analytics. SAS algorithms are packaged up into user-defined functions/methods/types along with external stored procedures (Java). In addition, extensions are being added for geospatial, encryption, XML publishing. And, all this must scale linearly and efficiently.

Version 13 will have: new table type with no primary index (distributed uniformly like a deck of cards to avoid hot AMPs), efficiency in UDF, and the like. I would have like to hear more on these v13 features.

TD-P%20SAS.JPGStephen and Paul went through a comparison of old/new world for SAS analytics. Teradata-awareness inside a SAS Proc implied that there was additional logic to execute SQL to return the results to the SAS Proc. Another example is SAS Scoring Accelerator where SAS Enterprise Miner that generates the C code and publishes a UDF to be executed inside Teradata.

SAS is the first strategic partner for Teradata's In-Database initiative. There is a joint product roadmap and joint R&D engagement, along with SAS/Teradata Center of Excellence and SAS/Teradata Executive Customer Advisory Board. The result of this partnership is to reduce the time to build and deploy models from months to a week. From SAS perspective, there is lots of data on a grid computing cloud! We need to focus on moving the work to the data, not the opposite.

Another approach is to put the SAS processor physically close to the Teradata database. For example, the 2550 has space in the standard rack to place an application processor inside.
Teradata 13 will support SAS with: variant data type, input data ordering context area, fast work tables, and expanded table headers. Future useful Teradata features to support SAS analytics are: intrinsic functions, pivot/unpivot SQL operators, and tens of thousands of columns.

Paul noted that an important new feature to support SAS is input data ordering. An example was given for a Proc Forecast embedded into SQL as a UDT.

Stephen wrapped up with comments that there really is a deep collaboration with the R&D teams. It has been a challenge to the Teradata folks to think different. He remarked that, if you told me you needed 10,000 columns, he would immediately feel that the data model is broken. It is driving unique and messy stuff into the database. The goal is to do your analytics faster and easier.

My take on this... This is cool! Often these partnerships are merely a superficial marketing alliance, but this is at a deep level. This is the most significant presentation that I heard at this conference. It was a glimpse at the next generation of BI analytics that eliminates the technical and cultural barriers separating the database and analysis communities. We all must be one with BI. The smarts of SAS can not remain hidden in the back cubicles; those smarts must be relocated to the front desk touching customers and to the loading docks touching suppliers. And, the power of Teradata must enabled that relocation.

[Blog stream from the Teradata Partners Conference is here.]

Posted October 15, 2008 10:40 PM
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TD-P%20logo.jpgSpeakers were Imad Birouty, Program Marketing Manager for Teradata, and Jim Blair, Sr. Manager of DW Operations for Blue Cross Blue Shield. The session explored the relationship of data integration and business value. The key questions were: What is the value of an integration environment? Then, what is the cost of the infrastructure required to realize that value?

There are three options for providing enterprise analytics: no integration with separate data marts, some integration with mixtures of data marts and EDW, single EDW with one common data model.
Benefits are derived from cost savings, efficiency/optimization, biz opportunity. Better decision making should be based on the right data at the right time. Of course, this begged the issue of how do you determine right.

Limited business value is illustrated by two triangles that do not overlap. If the data is integrated, the triangles will overlap, resulting in an increase in the number of questions that can be answered. You need to see the illustration to appreciate the concept.

Upon questioning, Imad noted that the numbers were derived from a detailed enterprise logical model so that there is specific questions behind each of those numbers. Imad extended his analysis with a Data Overlap Analysis, which provided insights into the effort to add new applications by leveraging existing data elements.

Jim continued by covering a TCO (total cost of ownership) comparison of DW platforms among Teradata, IBM, Oracle, and an unnamed DW appliance vendor (whose name starts with N). Jim gave a credible detailed explanation of the infrastructure of his company, but it felt somewhat as a pro-Teradata sales pitch. However, the cost categories would be useful to other companies struggling with a credible TCO estimate for their DW infrastructure.

My take on this. . . Too general and needs specific examples. And the other hand, time was limited and quite a few slides were omitted in the talk. I urged them to extent this work by attributing business value to each question so that the benefit of cross-function integrated data is not just the number of questions to be answered, but a subjective estimate of the importance to the company.

[Blog stream from the Teradata Partners Conference is here.]

Posted October 15, 2008 10:38 PM
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TD-P%20logo.jpgWayne Eckerson, director of TDWI Research, talked on The Myth of Self-Service BI: Balancing Ad Hoc and Tailored Delivery to Achieve Widespread BI Adoption.

He feels that he is taking on a big sacred cow in the BI industry. Self-service BI (SS-BI) is good, promising to release users from their data prison by opening the doors on the data warehouse. DW is like a black hole that sucks up all data. Users were excited, but old habits are tough to change. Traditional DW has not been able to deliver. So, give them self-service BI tools! Right? Any problems? Yes!

TD-P%20Wayne.JPGWayne defines SS-BI as. . . empower users to create their own reports so users get what they want when they want it without having to ask IT.

What do user really want? Is it to form queries to retrieve, or to analyze data to make decision? Should be the latter. The reality is that there is lots of crud that conforms user to the way that BI tools work, rather than how users do their work. Only 20% are power users who are plugged in. The other 80% of users are out in the cold with: cannot find right report, inconsistent data, slow response time, and too complex to use.

There are are two types of SS-BI: ad hoc report creation versus ad hoc report navigation. Wayne applying systems theory to shifting the burden. He suggested that we need tailored delivery for ad hoc report navigation. Characteristics are: tailored to specific group of users, ability to personalize, and as performance dashboard. Each sandbox should contain about 20 dimensions and 12 metrics. This can replace hundreds of traditional reports.

Wayne offered the MAD Sandbox framework, which consists of:

  • Monitor via graphical data for managers

  • Analyze via summarized data for analysts

  • Drill-Thru via detailed data for worker bees

At Cisco Systems, they applied the MAD Sandbox. Often companies flip the pyramid upside down where everyone is drowning in detail data. To work, IT must to totally involved with MAD. As a company matures with this framework, they will embrace Double MAD, which extends MAD to:

  • Model

  • Advanced Analytics

  • Decide and Do

As a gut check, it is Self-Service BI or Self Serving BI? Be honest!

My take on this... I like the simple MAD framework. However, it hides two deep problems.

First, how do users get education on the business semantics embedded in a MAD sandbox. It is constantly changing. Users are shifting job responsibilities. New employees are hired. And, acquisitions bring in whole new crowds of users who come with totally different business semantics.

Second, what is the mechanism that enables consensus again and again on business semantics. Yes, this is a data governance issue. But, everyone must be involved far beyond the governance board.

[Blog stream from the Teradata Partners Conference is here.]

Posted October 15, 2008 10:34 PM
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