Building an Analytics Team From the Ground Up

With the advent of The Data Age, the collection and investigation of data is becoming essential for business success. In fact, a majority of businesses have begun leveraging analytics teams to assist them in gathering, analyzing, interpreting and leveraging data. As the data industry continues to progress, the importance of effectively utilizing and analyzing data will become even more essential, and analytics teams are projected to give businesses an edge over their competition. To help develop an effective analytics team, businesses should seek to cover, at a minimum, the following team roles:

Analytics Manager – Lead and manage the analytics team. May be in direct contact with business executives to ensure that the team is aligning with the company’s overall analytics needs. Analytics managers should have solid communication skills as they must often translate technical knowledge so that peers in other departments can comprehend.

Data Architect – Designs and oversees data models, queries and infrastructures to ensure that the team is generating the appropriate amount and type of data. Data Architects should possess the ability to view data and infrastructures from a number of perspectives, especially on a micro and macro level.

Product Developer – Set up projects prior to their start to ensure that tracking aligns with desired results. Developers should have a strong grasp of coding and may work closely with Data Architects throughout each project.

Analyst – Directly analyzes the collected data and, depending on the volume of data, typically consists of a few different team members. Analysts should be excellent thinkers with an interest in psychology, as they often will need to consider the thought process of their audience to uncover new questions/answers.

Reporting Developer – Develops analytics reports for managers and company executives to overlook on a quarter and annual basis. Reporters are growing essential for businesses and organizations as they strive to directly align business initiatives with insights developed from analytic data, as opposed to simply leaving data within a database that may be difficult to read.