Accelerating Data Science Using Machine Learning Automation - Data Manager Online

For many companies, today, the demand for data and analytics is now everywhere in the enterprise. Projects are underway to improve customer engagement, reduce risk and optimize business operations. Data sources are also growing rapidly with new data coming from both inside and outside the enterprise in many different varieties. Also although analytics are needed almost everywhere, the current approaches to developing them are slow and expensive. To support this demand, the modern analytical environment has also expanded going way beyond the traditional data warehouse to become an analytical ecosystem comprising multiple data stores and platforms optimised for different kinds of analytic workloads.