Since now is the time when we reflect on the past year and make resolutions for next year, in this post I reflect on my Data Roundtable posts from the past year and use them to offer a few New Year’s data resolutions for you and your organization to consider in
I have participated in many discussions about master data management (MDM) being “just” about improving the quality of master data. Although master data management includes the discipline of data quality, it has a much broader scope. MDM introduces a new approach for managing data that isn't in scope of traditional data quality
As this is the week of Christmas, many, myself included, have Christmas songs stuck in their head. One of these jolly jingles is Santa Claus Is Coming To Town, which includes the line: “He knows if you’ve been bad or good, so be good for goodness sake!” The lyric is a
I have a rule – any conversion or upgrade will require the creation of a decommission plan. A decommission plan should include the following: A list and definition of each database, table and column (source and target). A list and definition of each of the current programs in use (you
The physical data model should represent exactly the way the tables and columns are designed in the in the database management system. I recommend keeping storage, partitioning, indexing and other physical characteristics in the data model if at all possible. This will make upkeep and comparison with the development, test
We've explored data provenance and the importance of data lineage before on the Data Roundtable (see here). If you are working in a regulated sector such as banking, insurance or healthcare, it is especially important right now and one of the essential elements of data quality that they look for
I have a question --- do we need a logical data model for a conversion? Here are my thoughts. I believe the answer is yes if the conversion has any of the following characteristics: The target application is created in-house. This application will more than likely be enhanced in the
In my previous post I explained that even if your organization does not have anyone with data steward as their official job title, data stewardship plays a crucial role in data governance and data quality. Let’s assume that this has inspired you to formally make data steward an official job title. How
To perform a successful data conversion, you have to know a number of things. In this series, we have uncovered the following about our conversion: Scope of the conversion Infrastructure for the conversion Source of the conversion Target for the conversion Management for the conversion Testing and Quality Assurance for
Here on the Data Roundtable we've discussed many topics such as root-cause analysis, continual improvement and defect prevention. Every organization must focus on these disciplines to create long-term value from data quality improvement instead of some fleeting benefit. Nowhere is this more important than the need for an appropriate education strategy, both in
