Why Data Engineering?

• Gives Your Data Velocity

  Stale data doesn’t allow you to make real-time decisions to more accurately predict things such as customer retention, churn, fraud, etc. It isn’t helpful to identify fraudulent credit card activity three weeks later. We not only need to have data to have data science, we also need timely data.

• More Data Means Better Predictions

  In the world of big data, more managed data means more accurate predictions. A lack of data and the ability to manage what is available inhibits many of our clients. Good models, good machine learning, and good AI are impossible without well-governed data pipelines in place.

• With No Data Engineering, You Have No Data Science

  Without data engineering, there is no data. Without data, there is no machine learning and no AI. Data science needs data upon which to apply algorithms.

• A world without data engineers? Not possible

  There is simply too much data being created for the old methods to remain relevant. Data engineering is a fundamental part of the new world of big data, not only increasing the amount of data collected, but also ensuring that is clean, consistent, and high quality.