The Various Roles in Data Science
In just a few months, Big Data has reached the summit of the IT industry. In an economy where the term “mass customization” has taken on a new meaning and new capacities, the concepts of Good Data and Data Science have gradually become more important. It is now critical to better anticipate customer behavior, and understand and make use of the vast reserves and potential of internal and external data by building architectures that include an array of technologies.
The methods through which companies can take advantage of these tools are becoming clearer each day. One important question is that of the experience and skills that are needed to implement these platforms and ensure they are coordinated consistently and sustainably. The goal is to use internal and external data, both structured and unstructured, to improve competitiveness and take informed, and sometimes disruptive, decisions. To reach this goal, companies need to train their staff in Data Science, with clearly identified skills and roles.
What job descriptions are currently on the market? What roles and responsibilities should the identified jobs have? How can companies build a Data Science team, and how can it evolve over time?
This white paper contains answers to all these questions.