Programs are the cornerstone of the Josh Bersin Academy, but they’re not the only way to learn. Members of the JBA also have access to a growing library of more than 200 Resources— micro-learning, the latest research, and on-the-job support for the modern HR professional. We publish at least 3 new resources every week and each resource is exclusive to the Academy, you can’t find this content anywhere else.
Most of our Resources tie into the topics we cover in Programs—like People Analytics. The next session of the People Analytics Program starts on February 10, and along with the program is a wealth of People Analytics resources that extend and deepen the learning and provide HR professionals with the practical tools they need to get better at People Analytics in the real world. Here’s an example of one of those Resources, called “Defining Data Roles,” which is all about the different tasks various data professionals take on in our organizations and how we as HR professionals can better integrate their skills:
Defining Data Roles
There are a lot of potential titles floating around the data space. And it can be tough to understand the distinctions between these various data roles, particularly because many companies treat them differently. At a small start-up, a single individual may wear all (or at least, many) of the data interpretation hats. At a bigger company, you may have entire teams devoted to different disciplines.
What does that mean for us? It means that we need to have a flexible understanding of what different jobs entail. While there are a few benchmark definitions that can give us a head start on understanding these roles, they’re all moving targets. There will be times where the best way to understand a given role is to ask.
- Data Scientist: Data scientists are responsible for gathering, cleaning, and interpreting data, and then sharing insights to help make data-driven decisions. In many cases, a data scientist designs experiments, runs models, and develops algorithms to better extract insights from the information. At a small company, this role might also encompass the roles of analyst and engineer.
- Data Analyst: Data analysts are primarily interpreters of data sets. They are unlikely to design algorithms or run experiments, but are typically responsible for parsing the results that come out of those experiments. It’s their job to solve business problems by querying the data, and then translating it into reports, summaries, and visuals that will help people across the company understand the results and make informed decisions. (They are not necessarily engineers, but may know a lot about the function they support.)
- Data Engineer: Data engineers may be involved in designing experiments and running models, but their role is more often concerned with maintaining data architectures—the software that keeps data flowing in. They are responsible for integrating sources, keeping all the information organized and searchable, and, in some cases, amassing large data warehouses.
- Database Administrators: Database experts know how databases work. They know SQL, how to design a database, and how to backup, administer, and query a database well. They often “run” the database after it is engineered and integrated.
- Data Visualization Experts: Data visualization experts, or “story tellers,” know how to take data and put it into meaningful infographics, charts, presentations, and stories that others can use. Without these people we cannot consume data, so they are experts in bringing data into life and helping us take action.