The Three P’s of Data Engineering

New Tool Helps States Reduce Unemployment Insurance Overpayment

This blog is dedicated to help agencies – who are wary of domestic and foreign abusers of the Unemployment Insurance system – by describing our successful fraud detection work, where and how it is being used, and how to leverage the lessons learned and tools built to identify FWA.

Four Common Data Engineering Pitfalls (and How to Avoid Them)

Data Engineers are experts that work with data storage and transfer technologies. In this blog Dr. William Goodrum highlights four common pitfalls for data engineering projects and how to avoid them.

What is the Value of Data Engineering?

Updating a Data Pipeline with AWS’s Latest Offerings

Do We Have the Right Data?

In this blog, Jeff Deal discusses the problem of organizations waiting until they have perfect data before starting an analytics project. In our experience the mistake of “waiting for perfect data” probably kills more projects than any other. So how do you know if you have the right data?

Data Engineering with Discipline

When trying to get decision-making insights from data, we often must start with helping to clean and organize the data architecture so we can build data science and machine learning models, a process called data engineering. This blog explores process of preparing data for analytical analysis.

What is Data Wrangling and Why Does it Take So Long?

What is a Data Detective? How to go Deeper With Your Data