Today we released our Databricks Unified Analytics Platform video. This short video illustrates to analytics leaders how Databricks can unify their analytics efforts onto one platform. This unification makes analytics teams more efficient and enables them to tackle tougher analytics problems.
Many organizations are moving to Spark for the awesome big data processing power it provides. And with the Databricks platform, they see how Spark can be even faster, when it is optimized, by the team that started the Spark research project at UC Berkeley that later became Apache Spark, for the cloud. These companies also benefit from the security Databricks builds into its platform. But the biggest benefit they see is the collaborative nature of the Databricks platform. Databricks enables the unification of:
People – Databricks provides one place for data scientists, data engineers, and business users to collaborate using a unified workspace, making it easier to tackle advanced analytics efforts and share insights across the organization.
Process – Databricks streamlines analytic workflows through job scheduling, real-time notifications, and automation of your analytics process. This frees up your engineering teams so they can tackle higher valued tasks.
Platform – Databricks provides the integrations that enable one seamless platform – from data lakes and warehouses to streaming data, to your security and permissions. Databricks also runs Serverless, automating the provisioning of clusters. This takes your team out of the business of a DataOps/DevOps role, and allows them to focus on the high value analytics functions they provide.
This video provides a quick introduction to show how the Databricks Unified Analytics Platform enables these teams to come together. For more information, see the Databricks Unified Analytics Platform page.