Data has become one of the most important assets of companies in the digital age; However, the concept of “Data” is so new and broad that even experts in this field approach it with very different definitions and perspectives.
As difficult as it is for data scientists to label data and develop accurate Machine Learning Models, managing models in production can be even more daunting.
Big Data Analytics uses advanced analytical techniques against massive, diverse datasets from different sources and contains structured, semi–structured, and unstructured data of varying sizes from terabytes to zettabytes.
Predictive analytics transforms data into actionable insights, but only when combined with the decision-making process. As businesses become more adept at predictive analytics, data harmonisation becomes critical to success. What exactly is data harmonisation, and why is it important?