In an ongoing discussion on LinkedIn there are some good points on: How important is data quality for big data compared to data quality for small data?
A repeated sentiment in the comments is that data quality for small data is going to be more important with the rise of big data.
The small data we are talking about here is first and foremost master data.
Master Data Challenges with Big Data
As with traditional transaction data master data is also describing the who, what, where and when of big data.
If we are having issues with completeness, timeliness and uniqueness in our master data any prediction based on big data matched with master data is going to be as chaotic as weather forecasts.
We also need to expand the range of entities embraced by our master data management implementations as exemplified in the post Social MDM and Future Competitive Intelligence.
Matching Big Data with Master Data
Some of the issues in matching big data with master data I have stumbled upon are:
- Who: How do we link the real world entities reflected in our traditional systems of record with the real world entities behind who’s talking in systems of engagement? This question was touched in post Making Sense with Social MDM.
- What: How do we manage our product hierarchies and product descriptions so they fulfill both (different) internal purposes and external usage? More on this in the post Social PIM.
- Where: How do we identify a given place? If you think this is easy, why not read the post Where is the Spot?
- When: Date and time comes in many formats and relating events to the wrong schedule may have us Going in the Wrong Direction.
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