Moving Data Warehouse Workloads? Know Before You Take Aim.

Rima MutrejaBusiness/Company

data warehouse workloads

When proposing a major enterprise IT undertaking, such as a re-platforming of an enterprise’s data warehouse workloads to a new data warehouse, “we just have to get off the old and expensive systems” isn’t what business and IT leaders want to hear to support a business case.

Let’s say you have at least a few dozen data warehouse workloads you could potentially shift to a new cloud-native database, such as Amazon Redshift or Microsoft Azure SQL DW. To successfully execute this project, which can be long, painful, and expensive, you will need to create a database re-platforming plan, define a compelling POC, and demonstrate ROI to justify taking this plunge. Typically, it can take up to a year to complete the research and create a plan for this type of a project.

One of the first steps in creating a data warehouse re-platforming plan is getting answers to the following questions:

  • Which data warehouse workloads can be successfully moved?
  • Which data warehouse workloads can be prioritized for re-platforming??
  • What is the implementation effort?

With Datometry’s recently released Hyper-Q QueryIntelligence (QI) Edition, the answers to the above questions can be obtained within minutes. The powerful Hyper-Q QI software takes the guesswork out of matching data warehouse workloads to new environments and provides an in-depth analysis of existing workloads at unprecedented level of detail and provides the critical intelligence to execute a re-platform effort.

The results include a complete and in-depth analysis of all features, data types, and query constructs used in the current database and a targeted suitability analysis of the new database. The Hyper-Q QI analysis is automated, requires minimal resources, is light-weight, and can be performed without any additional prep work.

The benefits of this insightful reporting enables enterprises to scale projects by choosing which workloads are best to shift now and get those early wins and deliver business value. Using the Hyper-QI analysis, enterprises can take on data warehouse re-platforming initiatives with confidence, significantly speed up the research process, shine a spotlight on the ROI, and eliminate the risk and complexity along the way.

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