All Catchers and No Pitchers
Updated: Jun 18, 2018
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 they may be, 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 to work with, but no “pitchers” providing that data in the first place!
Both roles are essential to effective utilization of big data and 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
Developing, testing, optimizing, and maintaining large scale databases, data warehouses and data lakes as well as large-scale data processing and extraction systems are essential functions performed by data engineers. 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 and together form the solid foundation on which good business decisions are based. Teams of data scientists and engineers must communicate well and work together before data is actually useful in terms of guiding fiscal, management and strategic decisions.
Data scientists and engineers alike need to understand the needs of the end users so the right kind of data is collected and then analyzed appropriately in order to produce results that will be accurate and 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 find out how our data engineers can help you obtain, clean, organize and store data from almost any source so you can make the best possible business decisions for your company.