For business users to produce effective analytics and insights, they depend on data they can trust. However, as more data pours into the enterprise, the data landscape is becoming more complex. Today we have data in multiple cloud systems, NoSQL databases, Data Warehouse relational databases, Hadoop systems, and a myriad of small data stores. Worse, self-service projects are often stand-alone and start by people creating their own copy of data -- which makes the generation of trusted, sharable analytics and insights a real problem.
Should we force people to use inflexible, slow-to-change ‘production’ data warehouses, or do nothing and accept the ‘side effects’ of autonomous self-service analytics?
Neither. In this webcast by industry veteran Mike Ferguson, you'll learn about the justifications, requirements, and means for creating a trusted data foundation that your entire enterprise analytics program can depend on.