Analytics Engineering with SQL and dbt

Preface

In the ever-evolving business world, a captivating concept known as analytics engineering has emerged. It quickly became the talk of the town, in demand by managers, presented by IT companies, and admired by users who marveled at the possibilities it offered. But amid the excitement, many didn’t know what analytics engineering was about. They thought it was about creating data pipelines, designing stunning visualizations, and using advanced algorithms. Oh, how wrong they were!

You can imagine this extraordinary world of analytical engineering as a cross between the meticulous investigator Sherlock Holmes, representing the analytical side, and the genius engineer Tony Stark, better known as Iron Man, representing the engineering side. Imagine the remarkable problem-solving skills of Sherlock Holmes combined with the cutting-edge technologies of Iron Man. This combination is what defines the true power and potential of analytical technology.

But beware: if you thought analytics engineering was limited to data pipelines and visualizations, you missed the deep deductive thinking that Sherlock Holmes, as a representation of a data analyst or business analyst, brings to the equation. This field is where analytical investigation crosses with the techniques of a software engineer or data engineer, represented by Tony Stark.

Stop for a moment and think about the importance of data in your business. Why do you seek it? The answer lies in the pursuit of knowledge. Analytic technology ...