A recent on-line survey found that most companies still tackle their data quality issues with manual coding. I was curious about this and asked some of my clients about the actual lag time between realizing that they had a data quality issue and deploying a software tool to apply automation to the problem. The answers were surprisingly similar. A data steward at one of our insurance clients explained it this way: - Read the rest of this entry »
It is not very often that I get to toot someone’s horn (other than mine), but I met the most amazing programmer. No, it’s not my husband, but this young woman that came to work for us a few months ago. Actually, I think she is much like I was at 26 years old. She is ready to take on the world, climb the corporate ladder, and create her career. - Read the rest of this entry »
We are often called upon to help IT teams “sell” data governance or master data management programs to executives who either don’t have the background, education, or the emotional fortitude to look corporate information processes in the face, stare them down, and declare them ugly. - Read the rest of this entry »
I think project managers come in two flavors:
Let me explain the differences. A Technical Project Manager has a tendency to work side by side with the programmers, and gets very involved in process and code creation. The TPM is very concerned with the data model and making sure it can generate the data definition language (DDL), and create a table in the database. Not that this is bad, but sometimes a TPM does a bit of micro-management - Read the rest of this entry »
This week I attended the CDI-MDM conference in New York, and presented a workshop on Data Quality and Data Profiling for MDM. I was asked a number of times during the event my opinion as to which approach to record matching was better: the deterministic approach or the probabilistic approach? In a nutshell, deterministic matching, like parsing and standardization, relies on defined patterns and rules for assigning weights and scores for determining similarity. Alternatively, probabilistic matching relies on statistical techniques for assessing the probability that any pair of records represents the same entity. - Read the rest of this entry »
The management concerns about data (as discussed in previous blogs) are:
The final concern of my management team is third party data— Data that usually enhances the existing BI environment, but is not always of the best quality. Let’s define what that really means. - Read the rest of this entry »
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