Applying Machine Learning in Your Data Warehouse

Machine Learning (ML) is a routine and necessary part of organizations in today’s modern business world. The origins of ML date back to the 1940s when logician Walter Pitts and neuroscientist Warren McCulloch tried to create a neural network that could map out human thought processes.

Organizations can use their data along with ML algorithms to build a mathematical model to make faster, better-informed decisions, and the value of data to organizations today cannot be understated. Data volumes will continue to grow rapidly and organizations that can most effectively manage their data for predictive analytics and identify trends will have a competitive advantage, lower costs, and increased revenue. But to truly unlock this capability, you must bring ML closer to the data, provide self-service tools that do not require a deep data science background and eliminate unnecessary data movement in order to speed up the time it takes...