We see an increasing adoption of Big Data, Machine Learning (ML) and Artificial Intelligence (AI) in the market. One of the main drivers for this are the changes in how the solutions are implemented, from on-prem, which has been a huge hurdle for lots of companies out there, to cloud.
As we all know, Big Data in itself does not lead to any type of business value, but applying ML and/or AI on it does. It is also well known that the majority of the time spent in advanced analytics projects are spent on data integration, and that is where Databricks gets into the picture, by simplifying the bridge between data engeneers and data scientists. It also adds important functionality to handle security, and performance.