Smart Data - Not Big Data
It's About the Users, Too
On the flip side, the decision-makers must change their attitude about the data, as well.
1. Define the goals first: The main theme of this series has been that the Big Data movement is about the business, not IT or data. But I've seen too many business folks who would so willingly take a hands-off approach to data. They just fund the database; do not define clear business goals to developers; and hope to God that someday, somehow, some genius will show up and clear up the mess for them. Guess what? That cavalry is never coming if you are not even praying properly. If you do not know what problems you want to solve with data, don't even get started; you will get to nowhere really slowly, bleeding lots of money and time along the way.
2. Take the data seriously: You don't have to be a scientist to have a scientific mind. It is not ideal if someone blindly subscribes anything computers spew out (there are lots of inaccurate information in databases; refer to "Not All Databases Are Created Equal."). But too many people do not take data seriously and continue to follow their gut feelings. Even if your customer profile coming out of a serious analysis does not match with your preconceived notions, do not blindly reject it; instead, treat it as a newly found gold mine. Gut feelings are even more overrated than Big Data.
3. Be logical: Illogical questions do not lead anywhere. There is no toolset that reads minds—at least not yet. Even if we get to have such amazing computers—as seen on "Star Trek" or in other science fiction movies—you would still have to ask questions in a logical fashion for them to be effective. I am not asking decision-makers to learn how to code (or be like Mr. Spock or his loyal follower, Dr. Sheldon Cooper), but to have some basic understanding of logical expressions and try to learn how analysts communicate with computers. This is not data geek vs. non-geek world anymore; we all have to be a little geekier. Knowing Boolean expressions may not be as cool as being able to throw a curve ball, but it is necessary to survive in the age of information overload.
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.