We Accelerate Your Big Data Projects

We do this by helping you use your existing resources better, more efficiently, or building the right team.

We guarantee results and success.

Do you know if your team has the right skills to be successful with Big Data? What is your team’s probability of success?

Making sure the team has all of the right skills is crucial to your success with Big Data. A team missing critical skills or that has an ability gap have extremely low probablitities of success.

Most Big Data consultancies treat everyone the same – whether they are advanced or just beginners – leaving your team to sort out the mess.

Sorting out the mess takes time and effort, but companies want Big Data results now. This puts your team behind from the very beginning of the project. Other teams have been battling messes for months or more and are on the verge of failure. We figure out what’s wrong, fix the issues, and provide ongoing mentorship to keep the team from getting stuck again.

What is the difference between data science and data engineering? Does a data scientist or data warehouse engineer have all of the skills to create a Big Data project?

We wrote the book on creating successful Big Data projects called Data Engineering Teams. We invite you to read it and see how we help companies create strong data engineering teams that power data science and analytics teams.

From the Blog

Q and A: Viewpoints on Open Source

There are diverse viewpoints on open source and its usage as a service. I’ve attempted to give a synopsis of the issues and some background – but that’s only my viewpoint. I’m bringing in other people to give their diverse viewpoints to give a more well-rounded one. This is stemming from this Twitter thread. The […]

The Three Components of a Big Data Data Pipeline

The Three Components of a Big Data Data Pipeline There’s a common misconception in Big Data that you only need 1 technology to do everything that’s necessary for a data pipeline – and that’s incorrect. Data Engineering != Spark The misconception that Apache Spark is all you’ll need for your data pipeline is common. The […]