Having spent some time in an Enterprise Data Warehouse Competency Centre, one item I noticed was that we received a lot of input files, and we’re talking about hundreds of files a day coming from dozens upon dozens of different sources.
Needless to say we had over 80 source systems, legacy systems, web based systems and a few PC files as well. Each of those systems was responsible for sending us anywhere between 1 and 60 files per week. So needless to say there were lots of data related issues that came across my and my colleagues’ desks on a daily basis.
Is your EDW similar in nature? Do you have overworked data quality analysts?
Do you have source systems that just don’t care about the contents of the files they send you?
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Remember some of the goals of an Enterprise Data Warehouse is to create one version of the truth, to reduce redundancy, to streamline the decision making process and to reduce redundancy and improve data quality.
Apart from implementing data profiling tools, performing data assessments, monitoring thresholds, correcting code and asking for executive support for data quality in general. What else can you do?
If your organization is large enough and during these tryi…
Having spent some time in an Enterprise Data Warehouse Competency Centre, one item I noticed was that we received a lot of input files, and we’re talking about hundreds of files a day coming from dozens upon dozens of different sources.
Needless to say we had over 80 source systems, legacy systems, web based systems and a few PC files as well. Each of those systems was responsible for sending us anywhere between 1 and 60 files per week. So needless to say there were lots of data related issues that came across my and my colleagues’ desks on a daily basis.
Is your EDW similar in nature? Do you have overworked data quality analysts?
Do you have source systems that just don’t care about the contents of the files they send you?
Remember some of the goals of an Enterprise Data Warehouse is to create one version of the truth, to reduce redundancy, to streamline the decision making process and to reduce redundancy and improve data quality.
Apart from implementing data profiling tools, performing data assessments, monitoring thresholds, correcting code and asking for executive support for data quality in general. What else can you do?
If your organization is large enough and during these trying times, the budget permits it, and the organizational culture accepts it introduce a Data Quality Recognition Program.
What, a data quality recognition program, you said? Yes, I said, a data quality recognition program. The following list contains a few steps you will need to establish such a program:
1. Executive buy-in, (primarily needed for budget approval).
2. Advertise the program to all your source systems.
3. A means to track data quality by source system.
4. Identify qualifying systems (those with an owner).
5. Track the data issues and identify the source systems.
6. Compile the results annually.
7. Hand out the award or awards.
8. Advertise the winner(s) and their results.
You can also establish multiple awards, such as most improved data quality, best data quality, most timely data, most accurate data entry clerk, call centre with the best data quality or even a DQ troll award (for the worse data, if they have a sense of humor) and more. Really the type of awards and the number of awards is entirely up to you and of course the budget.
Make sure your award winners have a great day. Provide the team responsible or owner of the source system with a tangible award, or a plaque. It makes for an interesting conversation piece and it gives them bragging rights, especially on the resume.
Once your program is established and awards handed out, watch the data quality of your EDW improve over time, as everyone does their best to be named in the next award ceremony.
