Saying Yes!! (or at least Maybe) to NO SQL

Since the beginning of this year, the amount of chatter around the “NO SQL” (Not Only SQL) topic has increased. EDW conference seems to have made more people aware and whether on LinkedIn or other forums, there is a health amount of information exchange going on.

• Some are excited about the possibility of a new way to analyze data
• Others think this would make data quality management even more difficult

I think both groups are right. I also think it wouldn’t necessarily make data quality management more difficult, but make the challenge more obvious.

Where we all seem to agree on is the need to understand what the different tools are and the core strengths of different approaches. I think as a data profession, we need to be personally accountable to understand what can offer value to our colleagues and customers, and even if we don’t have a lot of time for research. I fundamentally believe that even if I don’t make the time to be aware of how a new technology or process may be of use, if the value (or marketing 🙂 is good enough, others will experiment and then when things stick, we may be playing catchup. I think it would be an err for the data profession is to repeat the same mistakes that were made when XML was first becoming popular and leaving these data structure definitions to the developers.

So saying Yes, No, or at least Maybe to NO SQL or any other innovation it up to us. In many instances, our experience with past technologies (relational, IMS…) can carry forward to how new technologies can make older approaches more scalable and viable. For the truely innovative thinking, it should at least be interesting enough to do some reading on it.

We live in “interesting times”, with the excitement and challenges of it all.