This category contains 18 posts

#BreakingBad at #SQLSATWPG

I’m very excited to be presenting my Breaking Bad presentation on OStress and SQL Profiler to SQL Saturday Winnipeg on November 22nd. There are 20 sessions that will be presented in 4 separate tracks with speakers from all over North America. (And a recent addition from South America) The first person to refer to me … Continue reading

#SAP, Breaking Data, and Re-enabling #SQLServer Database Referential Integrity Constraints #Microsoft #FTW

Many times as Data professionals we no longer have full control over the quality of data in the source systems. I am discussing SAP in my example, but I could have easily mentioned PeopleSoft, SalesForce, or a number of other purchased solutions. Usually those solutions are purchased and then we are tasked with maintaining those … Continue reading

Creating my own #ETL data validation #FTW

Recently on the same project I created an Agile Data Warehouse and Extract, Transform, and Load automated test suite, I was tasked to create a data validation process. We need to create a foundational process that could be leveraged to provide ongoing data validation for the data load process. We were responsible for loading data … Continue reading

How to create 10,000 Extract, Transform, and Load automated tests using 4 tables #agile #data

The thing I love about my chosen profession is the ability to learn new things and improve on lessons learned from past projects. Recently I was able to take on a problem that I have experienced on multiple past projects. “How can we easily create automated tests for a Data Migration or Extract, Transform, and … Continue reading

Business Case for creating a Data Model and Data Normalization

I recently came across a great article by @datachick on “Why having a Data Model is important?” on DataVersity. Highly recommended read. Karen Lopez provides a great list of items on why she finds a Data Model helpful. I do believe there is something missing from the list of items though. All of the items … Continue reading

12 Rules to create a Dimensional Model from a Normalized Model in an #agile way

Recently I have been on a project where I have been fortunate enough to develop both a normalized Operational Data Store and a Dimensional Data Warehouse. In addition to this, I have been fortunate to be able to recreate the Dimensional Data Warehouse three times over. This has been because the project has been done … Continue reading

My SQL Saturday Experience #SQLsat175

I just recently completed my presentation at SQL Saturday in Fargo. The experience was excellent. The facilities at the Microsoft Executive Briefing Centre in Fargo were outstanding. Very impressive organization throughout the entire event. I am very much looking forward to presenting at future SQL Saturdays. I was presenting on my experiences installing and configuring … Continue reading

#Agile Data Conversion

Last year I presented on Agile Data Warehouse – the final frontier at SDEC12. You can find the presentation¬†here if you are interested. This year on the same project I have been challenged with another new frontier. Now that we are executing and evolving the Data Warehouse, the question was posed as to how we … Continue reading

Adaptive Data Model – #Agile or Anathema?

I have seen the concept of an Adaptive Data Model proposed as an Agile method to Data Modelling lately. (Most recently in Ken Collier’s excellent book – “Agile Analytics”) The theory is that you can be more Agile using an ¬†Adaptive Data Model instead of a traditional Data Model of the business domain. Definition An … Continue reading

The state of #Agile according to Data Modellers

DataVersity released their snapshot survey on Data Modelling and the results aren’t good for Data Modellers who want more adoption of Agile by the Data Modelling community. Before we get into the details, DataVersity is a great source of references and webinars for all things data. You can find them by clicking on this link: … Continue reading