An often raised question and a subject for a lot of blog posts in the data quality realm is whether data quality challenges should be solved by people or technology.
As in all things data quality I don’t think there is a single right answer for that.
Now, in this blog post I will not tell about what I then think is the answer(s) to the question, but simply tell about what I have seen been chosen as the solution to the question, which have been both people centric solutions and technology centric solutions.
If I look at the situations where people centric solutions have been chosen versus the situations where technology centric solutions have been chosen, the first differentiator seems to be numbers:
- If you have only a small number of customers and a single channel where entered, the better solution to optimal data quality and uniqueness seems to be a people centric solution.
- If you have millions of customers and multiple channels where entered, the only practical solution to optimal data quality and uniqueness seems to be a technology centric solution.
- If you have only a small number of products and a single channel where entered, the only sensible solution to optimal data quality and uniqueness seems to be a people centric solution.
- If you have thousands of products coming from multiple channels, the most reliable solution to optimal data quality and uniqueness seems to be a technology centric solution.
So, based on common sense the answer to the people or technology question is that it magically depends on the numbers.
Liliendahl on Data Quality 
I totally aggree. This is a great way of getting a feel for which solution mindset that could be best suited in a certain situation. This is also true for any data integration solution. I also like to spice it up with other differentiators:
– How “important” is the data for every involved party?
– Is the data highly volatile/dynamic?
– How much
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– How much risk is involved in every record? E.g. may there be human lifes at stake?
– What’s the business impact? 10 duplicate records may be enough to loose millions of dollars.
All these
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All factors above help to determine how the solution should look like; people or technology centric.
Dario, thanks for the magic numbers of comments 🙂
On LinkedIn Nigel Devenish says: Regarding your “people vs technology” argument around the Magic Numbers, how would you cater for complexity. Does technology not address complexity as well as data volumes, or is the multiple channels and multiple product/people denote complexity rather than data volumes?
I answered: I think complexity oftentimes is discussed when choosing between a people centric or technology centric solution, but the outcomes as I have seen it may go either way. Some complex problems, often mathematical challenges, call for a technology centric solutions. Other complex problems may not be outlined in the degree of details and logic needed for a technology solution, so here you choose a people centric solution.