Creating Data Products in a Data Mesh, Data Lake or Lakehouse for Use in Analytics (9-10 June 2022, Stockholm)
Data Warehouse Automation & Real-time Data – Reducing Time to Value in a Distributed Analytical Environment
Smart Infrastructure & Smart Applications for the Smart Business – Infrastructure & Application Performance Monitoring
15 March, 2018
9am EST / 1pm GMT
2pm EST / 6pm GMT
For business users to produce effective analytics and actionable insights, they need 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 with different users 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? Or neither.
In this webinar with 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.
To register for the webinar, or for more information, please click here