AI and machine learning give new meaning to embedded analytics

Data democratization, the concept of empowering any employee to make data-driven decisions for their company regardless of skill set, was supposed to rival the Elysian Fields in its paradise-worthy promise of analytics. It's easy to see why this concept made such a big splash in the enterprise. Since the early 2000's, companies have been amassing raw data, which has morphed into the $203 billion big data analytics market. But this data always lacked transparency. Housed in messy data architectures that led to siloed information, companies struggled to gain a singular big picture into what their data was telling them. IT departments were left to sort through data warehouse integrations and complex extract, transform, load processes to try and create structure so any data analytics tool would single view into solving business problems.