Data professionals (analysts, scientists, operators, etc.) utilize data to extract insights from it and subsequently to make decisions that impact day-to-day operations as well as long-term strategy for organizations. The process of going from data to insights and using decisions typically involves (a) extracting data from varied structured and unstructured sources; (b) normalizing, cleaning, and stitching such varied data sources to obtain “ground truth”; (c) extracting structure within data, interacting with it, and visualizing it to obtain insights; (d) predicting, optimization, and scenario analysis to make decisions.
However, while data professionals are busy extracting insight from data, the underlying business is often changing beneath their feet. In the case of using analytics to power operational decisions, like those often seen in logistics, e-commerce, supply chain, or finance, business rules and market conditions are often changing daily. What we want to get to is a state where we can enable iterative agility. Really the only way to do this is to utilize cloud-native automation, as opposed to what is predominantly desktop or on-premises automation.