Data ArchitectureData Engineering

Data beats intuition

“Data beats intuition” was a quote I heard at the AWS symposium in Brussels this year. And it’s true. We tend to value our intuition above anything, but we often fail to acknowledge that our intuition is fueled by data and information. Were you to reverse-engineer your intuition, you would find that it is fueled by the data and information you have gathered during your life so far. But it’s fueled by just our own data. The goal is to combine the data and information in larger numbers to elevate decision making. Businesses are relying more and more on being data driven instead of the intuition of a select few. But what is data driven? Just using data for making your decisions?

Mathematics is, in my opinion, a great example of a data driven field. It uses experts to derive definitions and theories based on data. These can then in turn be used to further understanding in the field by other experts, acting as steppingstones for future endeavors. A new mathematician does not have to start from the mere basic numbers, they can build upon definitions that are proven by those who went before them, proven by data. But what about theories that are not yet proven? Sometimes theories get disproven as more data arrives, but the great thing is that disproving a theory is often as valuable as proving a theory.

As it should be in business. We derive information from data but it’s worth noting that the definition of certain information can change over time. For example, segmentation of sales by gender would have been just 2 values, male and female. Today, that is a whole new definition. It’s an illusion to define the world today and expect these definitions to hold forever, let alone the next year. The same goes for your business, it is a living entity with ever changing definitions of its own as your business grows. As we keep generating more data, definitions get clearer but are almost never constant.

To accommodate these changing definitions, data professionals build robust architectures to store and process data. Storing data is much more than just storing, it’s about building quality checkpoints, pivot points on which you can build multiple solutions. So, whenever a definition does change, you don’t have to redo all the work that has come before. We build our own steppingstones to further the goal, learning from change and harnessing the power of data. It’s like building a road to reach your goal and you build crossroads at certain spots, just in case the road you build reaches a dead end. You don’t have to go to the beginning, you can go to the last crossroad and build from there. This way of working stimulates exploration, from one crossroad you can explore multiple avenues to gain new insights.

Using data is no guarantee for success, it never has been. It can, however, help you reach success. By providing you the best architecture for your needs, we can help you define your data and redefine when needed. We will encourage you on your journey to be successful by building quality checkpoints for reporting and exploration. Please, explore the data as much as possible and fail as often as you can. Success is one step beyond your last mistake.

If you would like to learn more, please contact us for a talk on our reference architecture and how we can help you become truly data driven, tog(a)ether.