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Dan Linstedt

Bill Inmon has given me this wonderful opportunity to blog on his behalf. I like to cover everything from DW2.0 to integration to data modeling, including ETL/ELT, SOA, Master Data Management, Unstructured Data, DW and BI. Currently I am working on ways to create dynamic data warehouses, push-button architectures, and automated generation of common data models. You can find me at Denver University where I participate on an academic advisory board for Masters Students in I.T. I can't wait to hear from you in the comments of my blog entries. Thank-you, and all the best; Dan Linstedt,

About the author >

Cofounder of Genesee Academy, RapidACE, and, Daniel Linstedt is an internationally known expert in data warehousing, business intelligence, analytics, very large data warehousing (VLDW), OLTP and performance and tuning. He has been the lead technical architect on enterprise-wide data warehouse projects and refinements for many Fortune 500 companies. Linstedt is an instructor of The Data Warehousing Institute and a featured speaker at industry events. He is a Certified DW2.0 Architect. He has worked with companies including: IBM, Informatica, Ipedo, X-Aware, Netezza, Microsoft, Oracle, Silver Creek Systems, and Teradata.  He is trained in SEI / CMMi Level 5, and is the inventor of The Matrix Methodology, and the Data Vault Data modeling architecture. He has built expert training courses, and trained hundreds of industry professionals, and is the voice of Bill Inmons' Blog on

In this entry, I return to Nanohousing(tm), the notion of utilizing nanotechnology for computing, and Business Intelligence purposes. Remember that these writings are an attempt to go beyond the horizon, and are futuristic guesses on what specific points of nanotech can be applied to within the DW / BI world. It will take years to get to these points, but rest assured - changes are happening. One of the areas that have really interested me in nanotech is the notion of DNA computing, that is using DNA strands form and function (combined) to serve specific computational purposes and answer specific questions.

"The hope of this field is that the pattern matching and polymerization processes of DNA chemistry, combined with the enormous numbers of molecules in a pound, will make feasible computations that are now too hard for conventional computers." DNA Computing,

First I'd like to point out (as I have a few times before) that the notion of form and function are recombined at the DNA computing level. In the BI/DW world of today, we have separated form from function, and it is inhibiting our ability to move forward, not to mention it is a severe drain on flexibility, scalability, and applicability. Form in our BI / DW world today would consist of models: Process models, business models, data models, architecture models, network models, and so forth. Function would be what these models do with the data / information passing through them.

For instance, data models today hardly resemble the business processes in which the data sets flow - while there have been some advances, like UML and Object Oriented modeling - they are still (for the most part) diversified from the true business functions. We strive to make sense of the data, and the architectural modeling paradigms by assigning metadata - descriptive context. We also are now headed back towards convergence of business function and "architecture" with Master Data Models and Master Data sets. Finally we're beginning to get it - but still, the nature of the RDBMS engine in today’s world is to apply common functionality to models designed by external means. They are not tightly coupled.

When we examine DNA Computing as a function of nanotechnology we find this to be a tightly coupled form and function process. The "model" in which the data sits, even where the information is encoded within the strand becomes important. The "function" is built in to the type of DNA strand created - in a bio-chemical sense.

"No arithmetical operations are performed, or have been envisioned, in DNA computing. Instead, the potential power of DNA computing lies in the ability to prepare and sort through an exhaustive library of all possible answers to problems of a certain size. ... A single strand of DNA can be abstracted as a string made up of the letters A, C, G, T. ... Complementary strands of DNA will form a doulbe strand (the famous double helix). Two strings are complementary if the second, read backwards is the same as the first, except that A and T are interchanged, and C and G are interchanged."

Now what happens in the BI / DW space if we were to follow this "wet-technology" model? What would happen if we were to combine form and function like the DNA computation machine? Would we see tremendous leaps in traditional computational power? I hypothesize that this is true, that if we were to simulate DNA computation in a newly designed DNA type database engine we would see a number of things happen. But remember, I'm not talking about traditional DNA modeling software on a traditional CPU / Computing Engine - no, I'm talking about a machine that currently only exists in bio-tech labs, in the test tubes.

Ok, so what could we do better today that we haven't done in the past, and do it on conventional computing resources?
We can begin converging form and function, start small (like a web-service for example), combine it with security, access rules, metadata, and definition of groups from a common set of elements (taxonomies). Cross it with the functionality of a web-service and make it available to the world. Self-encapsulated, it might interact (on it's own) with other web-services, in other words - discovery and deterministics are parts of this web-service. It discovers other web-services, and then decides if the other available service has information it can use, and if it has access - pulls the information in and assimilates it automatically.

Obviously the web-service is part of an extended neural network, which is capable of being taught, learning on it's own, and being corrected over time. So we still have some incorporation of traditional practices (due to the ultimate abstraction). This is a fundamental difference between the computational world and the DNA computing world. DNA Computing uses bio-chemistry to solve it's problems, and learn new things. Security is built in (as a function of what a DNA strand can and cannot "tie" to, bond with, cut and merge to - and how it will execute these things.

As a matter of interest to DARPA, here is an interesting look at the applications of nanotech in today's world.

How do you see DNA computing affecting the future of BI / DW?

Dan Linstedt
CTO, Myers-Holum, Inc

Posted November 17, 2006 7:46 AM
Permalink | 1 Comment |

1 Comment

The usual dictum is to let form follow function. It is fine to reverse this when wool gathering a little, but bear in mind that when contemplating a shiny new hammer everything starts to look like a nail.
It is hard to guess the time frames, but I suspect by the time such wet technologies could find commercial application to massively parallel processing they would be superseded by quantum superposition methods. And the latter may offer more potential for improvements that are qualitative, not merely quantitative.

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