Enterprise data warehouses (EDW) have long been the norm to handle analytic processing, but these systems have been pushed to their limits trying to support more data and increasing usage. These constraints on data flexibility, self-service access, and cost-effective scalability have forced IT teams into a pattern of saying "no" to new business demands as they focus on containing the costs of existing workloads. This has led many organizations to seek a better and cost-effective solution - expanding the value of their data warehouse landscape with a modern analytic platform that augments these legacy EDWs.
However, to effectively migrate workloads and relieve pressure from these systems can be challenging. Which workloads are ideally suited to each platform? How much of a workload can be offloaded easily and what changes or resources are needed to offload more complex portions? Is there an easy way to prioritize existing workloads to be offloaded? In the end, organizations are looking for ways to simplify and automate the process of offloading and optimizing these SQL workloads, while ensuring a seamless experience for their end-users.
Join Cloudera, MicroStrategy, and ESG to learn the journey organizations are taking to relieve pressure from legacy systems, so they can start saying "yes" to more.
We will be discussing:
- Industry trends related to the adoption of modern, Hadoop-based platform usage as it relates to existing EDWs.
- Key user challenges when migrating workloads.
- Guidance on implementing a successful offload strategy.
- Tools available for workload prioritization through auto-analysis and visibility into existing BI and ETL workloads.
- Business impact and strategies for end-user adoption.