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William McKnight

Hello and welcome to my blog!

I will periodically be sharing my thoughts and observations on information management here in the blog. I am passionate about the effective creation, management and distribution of information for the benefit of company goals, and I'm thrilled to be a part of my clients' growth plans and connect what the industry provides to those goals. I have played many roles, but the perspective I come from is benefit to the end client. I hope the entries can be of some modest benefit to that goal. Please share your thoughts and input to the topics.

About the author >

William is the president of McKnight Consulting Group, a firm focused on delivering business value and solving business challenges utilizing proven, streamlined approaches in data warehousing, master data management and business intelligence, all with a focus on data quality and scalable architectures. William functions as strategist, information architect and program manager for complex, high-volume, full life-cycle implementations worldwide. William is a Southwest Entrepreneur of the Year finalist, a frequent best-practices judge, has authored hundreds of articles and white papers, and given hundreds of international keynotes and public seminars. His team's implementations from both IT and consultant positions have won Best Practices awards. He is a former IT Vice President of a Fortune company, a former software engineer, and holds an MBA. William is author of the book 90 Days to Success in Consulting. Contact William at wmcknight@mcknightcg.com.

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

Recently in Data Warehouses Category

In "Top 10 Largest Databases in the World", the author covers the top 10 largest databases in the world. Their sizes are impressive indeed.

Speaking of large databases, I recently commented in an article that "The amount of information uptake into a corporation when RFID is implemented can be unprecedented. The largest data stores in the world soon will be in manufacturing and will comprise mostly item movement data."

Technorati tags: Data warehouse, RFID, DBMS

Posted November 1, 2007 2:35 PM
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To say you should “pick” your data warehouse executive sponsor carefully would be a rather strange statement. Not many DW programs can pick their sponsor. Usually, it’s the other way around. The program staff must deal with the sponsor that has chartered that course of action for the organization. DW programs need to have that top down driver and support at the executive level. Nonetheless, the executive sponsor acceding to his or her roles is critical to success and hopefully those roles are clear or there is the opportunity to make them clear.

I have worked with all manner of executive sponsor, from those who intuitively get it and put forward the effort required for success to those who need some guidance. Most are more than willing to listen and align their actions with successful practices for DW success. Generally, I ask my sponsors to invest in understanding DW systems generally and within their company; lead, as necessary, the governance meetings; provide overall direction for the DW and keep the DW out of internal cross-fire.

I’ve stopped asking them to define data elements and transformation rules!

Technorati tags: Data Warehouse,

Posted October 3, 2007 1:46 PM
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End clients generally end up overrating the usability of packaged data models, whether as stand-alone models or those models inherent in their software packages. Sooner or later, some amount of what I call ‘original data modeling’ is going to be necessary in any enterprise. Modeling expertise is a must-have though companies go to enormous lengths sometimes to avoid it. I don’t advocate necessarily changing packaged models in applications. However, no untouched application models, or combinations thereof, are going to be completely sufficient for a data warehouse in Fortune clients.

Technorati tags: data warehouse, data model

Posted September 26, 2007 7:09 PM
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Time for the Wednesday (or thereabouts) “What” (what I have learned…). OK, I seem to be endlessly prompted in my client work with these learnings so there’s no shortage of them, but sometimes I don’t have an elegant preamble to a blog entry. So, I’ll just say it.

You’ve got to tie that warehouse data back to source or users will cry foul. It doesn’t matter how dirty the source data is. If you want to change the data en route to the warehouse to clean it, fine, change it, but bring the original data as well in a different set of columns in order to prove your tie-out.

Tie-out should make you more comfortable with your ETL as well. It sometimes involves adding pre-extract queries to the source data and post-load queries to the warehouse data. It sometimes involves ‘spot’ query checks, which can get tricky. I.e., the method used to pick your spot data can come under scrutiny. It also gets tricky when the ETL is run intra-day or real-time, when ETL cycles are at an absolute premium. However, you still need to do it IMO. These tie-out results go in your operational metadata.

Tie-out is part of weaning users from their old ways to the new way (the data warehouse way). It’s part of the bottoms-up approach to a successful data warehouse rollout. Ask key users what they will use to deem the warehouse effort successful – and do that and more. Remember, users are from Missouri - the show-me state - and IT is from Mars (according to many users I have dealt with.) And if they don’t ask about tie-out, do it anyway!

Technorati tags: data warehouse, ETL

Posted September 20, 2007 7:32 AM
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Here’s one more on the theme of what I’ve learned. You’ve heard of Don’t Mess with Texas? Well, how about Don’t Mess with Excel!? Users love the sense of control over the data and the ability to perform their own calculations. (Other) BI tools will not sweep Excel out of any enterprise. However, precisely because of its flexibility, Excel is notorious as a source system for data warehousing and its applications need to get into a DBMS to serve the organization in that capacity.

DW teams often need to start as data providers to the organization, where knowledge workers from all over will pull for spreadsheets. Eventually, through value propositions (see previous ‘what I’ve learned’), those teams should increase their service to where they are providing BI and running the business, not just reporting on it. The Excel issue is a flashpoint for the whole ‘why do we exist’ issue for DW teams.

Technorati tags: data warehouse, Excel

Posted September 5, 2007 9:23 AM
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