Smart Data - Not Big Data
I visit many companies only to find that the databases in question are just messy piles of unorganized and unstructured data. And please do not assume that such disarrays are good for my business. I'd rather spend my time harnessing meanings out of data and creating values, not taking care of someone else's mess all the time. Really smart data are small, concise, clean and organized. Big Data should only be seen in "Behind the Scenes" types of documentaries for manias, not for everyday decision-makers.
I have been already saying that Big Data must get smaller for some time (refer to "Big Data Must Get Smaller") and I would repeat it until it becomes a movement on its own. The Big Data movement must be about:
- Cutting down the noise
- Providing the answers
There is too much noise in the data, and cutting it out is the first step toward making the data smaller and smarter. The trouble is that the definition of "noise" is not static. Rock music that I grew up with was certainly a noise to my parents' generation. In turn, some music that my kids listen to is pure noise to me. Likewise, "product color," which is essential for a database designed for an inventory management system, may or may not be noise if the goal is to sell more apparel items. In such cases, more important variables could be style, brand, price range, target gender, etc., but color could be just peripheral information at best, or even noise (as in, "Uh, she isn't going to buy just red shoes all the time?"). How do we then determine the differences? First, set the clear goals (as in, "Why are we playing with the data to begin with?"), define the goals using logical expressions, and let mathematics take care of it. Now you can drop the noise with conviction (even if it may look important to human minds).
Stephen H. Yu is a world-class database marketer. He has a proven track record in comprehensive strategic planning and tactical execution, effectively bridging the gap between the marketing and technology world with a balanced view obtained from more than 30 years of experience in best practices of database marketing. Currently, Yu is president and chief consultant at Willow Data Strategy. Previously, he was the head of analytics and insights at eClerx, and VP, Data Strategy & Analytics at Infogroup. Prior to that, Yu was the founding CTO of I-Behavior Inc., which pioneered the use of SKU-level behavioral data. “As a long-time data player with plenty of battle experiences, I would like to share my thoughts and knowledge that I obtained from being a bridge person between the marketing world and the technology world. In the end, data and analytics are just tools for decision-makers; let’s think about what we should be (or shouldn’t be) doing with them first. And the tools must be wielded properly to meet the goals, so let me share some useful tricks in database design, data refinement process and analytics.” Reach him at firstname.lastname@example.org.