Deciphering Data Architectures

Chapter 2. Types of Data Architectures

It’s absolutely vital to invest time up front designing and building the right data architecture. I found this out the hard way early in my career. I was so excited to start building my solution that I breezed over important decisions about the design of the architecture and what products to use. Three months into the project, I realized the architecture would not support some of the required data sources. We essentially had to restart the project from scratch and come up with another architecture and different products, wasting a ton of money and time. Without the right planning, end users won’t get value out of your solution, they’ll be angry about the missed deadlines, and your company risks falling farther and farther behind its competitors.

When building a data solution, you need a well-thought-out blueprint to follow. That is where a data architecture comes into play. A data architecture defines a high-level architectural approach and concept to follow, outlines a set of technologies to use, and states the flow of data that will be used to build your data solution to capture big data. Deciding on a data architecture can be very challenging, as there is no one-size-fits-all architecture. You can’t flip through a book to find a stock list of architecture approaches with corresponding products to use. There’s no simple flowchart to follow with decision trees that will lead you to the perfect architecture. Your architectural approach and ...