Moving efficiently from Data Science to AI – Learnings from K AI journey
Last fall, one of our K Group’s AI team members was using Google search and started to think about the full search term suggestions it gave. “Why don’t we provide this functionality?” he asked. If the product search proposed relevant search terms already from the first letters, the user experience would improve significantly.
In this blog post, we’ll first introduce the background of the K AI team and then share some things that nowadays make our work much easier. We’ll go through our perceptions on how removing separate roles for data science, data engineering, and DevOps has reduced risks, the benefits of having our own environment, and the improved efficiency of the team. We believe these learnings can be valuable to all the organizations that are facing a similar transformation.
Read the full case here: https://www.reaktor.com/blog/moving-efficiently-from-data-science-to-ai-learnings-from-k-ai-journey/