5 rules of productive data teams
A recent report showed that at least 80% of the analytics projects fail to deliver business value. This is so despite some of the smartest and most well-versed people are working on this field. I will resolve this seemingly paradoxical situation by giving 5 rules for successful data functions. We are discussing the teamwork, leadership, business integration, development, and cultural aspects of these teams through various examples of smaller and larger companies.
Lead Data Scientist, AGT International
Agoston did his doctoral studies at ELTE (Budapest, Hungary) and worked at two prestigious research institutes of the Hungarian Academy of Sciences: at the Brain Imaging Centre and at the Insitute of Computer Science and Control (also known as SZTAKI). As time went by, his focus turned to applied research. First, he lead the R&D function at Synetiq and now he is a lead data scientist at AGT International. His focus is on doing data science beyond the hype: applying statistics & machine learning (RL, DL) with software development (Lean, XP) best practices to bring promises to reality. He runs a blog on Medium about effective data science teams.
Fun facts: He designed his own 3D presentation toolkit, have a gift to find people interested in science in every part of the world, and plays cricket.