Why do we need analytics engineering?

Now that you understand the core definition and skills behind the term, it is time to deep-dive into why the role is necessary. Without analytics engineering, data teams often struggle with the quality and reliability of data models. Data engineers might be overworked trying to maintain infrastructure while working on data modeling. Meanwhile, it is hard for analysts to trust the metrics that they report on, since they have limited visibility on the complex transformation process that goes into it. When metrics are wrong, business stakeholders might lose trust in data. Ultimately, it impacts business performance, since it becomes harder to make data-informed decisions.

Let’s illustrate this situation with an analogy.

A supermarket analogy

Consider the data team as a supermarket supply chain. The data engineer is responsible for procurement, planning the transportation of products from producers and storage points to the supermarket...