All Pitchers and No Catchers

Data Engineers are needed just as much as catchers are.

When it comes to sorting through and analyzing the huge volume of data being collected by companies of all shapes and sizes, there’s no doubt good data scientists are useful. Able to slice and dice the data in any number of ways, data scientists are wizards with advanced math and complex statistical methods. Their ability to then clearly present results to key stakeholders is critical when it comes to contributing to business decisions. But no matter how talented, without quality data to work with, data scientists can’t do their jobs well.

Data Engineers are Key Players

Data engineers build and maintain the infrastructure that allows data to be collected and organized in the first place. Your data analytics team needs a balance between data engineers and data scientists. Without this, you will essentially have a team of “catchers” waiting on useful data, but no “pitchers” providing data! Both roles are essential to effective utilization of big data. However, it’s rare to find the complementary, but quite different, skill sets in one person. Business and sports bear a similarity in this regard: you need a well-rounded team if you are going to compete.

Providing Data Scientists with the Info They Need to Succeed

Some of data engineers’ essential functions include developing, testing, optimizing, and maintaining large scale databases, data warehouses and data lakes. Without meticulous attention to optimization from start to end of the data collection and organization processes, even using the most sophisticated methodologies data scientists can’t possibly produce reliable and meaningful results.

Laying the Foundation For Smarter Decisions

Think of data use as a triangle with key business stakeholders and strategists at the top. Data engineers and data scientists lay claim to the two points at the bottom. Together, they form the solid foundation on which good business decisions are based. Teams of data scientists and engineers must communicate well and collaborate before data is actually useful in terms of guiding fiscal, management and strategic decisions. Data scientists and engineers alike need to understand end users’ needs so the right kind of data is collected and then analyzed appropriately. This will help produce accurate results that will contribute to business decision-making.

We Can Help!

At QBIX Analytics, we know how important it is to organize good quality data so data scientists can do their jobs well. Contact us to discover how our data engineers can help you obtain, clean, organize and store data from any source.