Data lakes vs. data warehouses
Successful analytics depends on choosing the right approach to storing your enterprise data.
Successful analytics depends on choosing the right approach to storing your enterprise data.
Three tech leaders discuss the future of analytics and data architecture — and how to get the most value from them.
If your organization is using multi-tenant big data clusters (and everyone should be), do you know the usage and cost efficiency of resources in the cluster by tenants? A chargeback or showback model allows IT to determine costs and resource usage by the actual analytic users in the multi-tenant cluster, instead of attributing those to the platform (“overhead’) or IT department. This allows you to know the individual costs per tenant and set limits in order to control overall costs.
Cloudera Data Platform (CDP) supports access controls on tables and columns, as well as on files and directories via Apache Ranger since its first release. It is common to have different workloads using the same data – some require authorizations at the table level (Apache Hive queries) and others at the underlying files (Apache Spark jobs). Unfortunately, in such instances you would have to create and maintain separate Ranger policies for both Hive and HDFS, that correspond to each other.
This blog is part of our ongoing "meet the analyst of the future" series, which profiles analysts who are transforming their organizations and supercharging their careers by embracing the future of analytics today.