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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 http://www.COBICC.com, danL@danLinstedt.com

About the author >

Cofounder of Genesee Academy, RapidACE, and BetterDataModel.com, 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 http://www.b-eye-network.com/blogs/linstedt/.

Master Metadata - this is the term these days that I use to define enterprise level metadata efforts. In fact, Master Metadata (MM) is just as important as Master Data Management (MDM). Ok, maybe it should be called Master Metadata Management - (MMDM). But really, just what is Metadata? Data about data, wow - that's cool; not really - it's just the nature of the business. In this short entry we'll explore technical versus business metadata definitions.

Are there differences between the two? Not really, it's all metadata, so why separate them - well we want to classify different types of metadata so that we understand how to work with metadata, set it up, govern it, and how tools should work with it.

Technical Metadata: data about the processes, the tool sets, the repositories, the physical layers of data under the covers. Data about run-times, performance averages, table structures, indexes, constraints; data about relationships, sources and targets, up-time, system failure ratios, system resource utilization ratios, performance numbers.

I think you get the picture... Technical metadata include metrics and KPA's for IT, the business of doing IT work, monitoring and managing IT and physical environments. Technical metadata is produced by tool sets, tool vendors, and their repositories. Technical metadata is in essence - everything we deal with "under the covers" that hides complexity from the business users but makes the systems run.

Business Metadata: Data about the Technical Metadata, data layers that provide definition of the functionality, definition of the data, definition of the elements, and definition of how the data is used within business. Business Metadata is definitional in nature, one might also say that Business Metadata includes business requirements, time-lines, business metrics, business process flows, and business terminology.

The point is, we need both to do business properly - many vendors who offer metadata solutions do not properly differentiate between the two. Business metadata is often left behind as the vendors "tout" they have metadata in their solutions, but upon closer inspection it ends up being just technical metadata.

There are ways to bridge the gap today, but it requires standards, best practices and manual efforts (to some degree) and sometimes, multiple tool sets. Our firm has constructed best practices and a metadata tool vendor score-card which looks at all these categories. Contact me for more information.

Cheers,
Dan L
daniel.Linstedt@MyersHolum.com


Posted July 24, 2006 3:56 AM
Permalink | 1 Comment |

1 Comment

A fascinating and laudable set of concepts. It sounds so axiomatic, but I haven't heard of successful implementations. Politics, changes, enterprise size, etc, seem to get in the way. How do you address such issues? How have you found it works on an ongoing basis?

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