Five Things to Consider Before Performing a Workload Migration

Legacy data warehouse transformation is complicated and risky.  A successful migration requires a detailed evaluation on multiple parameters – including queries, tables, sub-queries, database views, users, applications, target query execution engines, and more.

To help guarantee that your workload migration is primed for success, we’ve put together a list of five things to consider before you get started.

Many other companies have been able to minimize the risks of a workload migration project by automating the whole process. Automation reduces the time required and removes error-prone manual activities while transforming the experience using a powerful, proven process. (More about that later).

1. Plan every detail by establishing your modernization objectives, determining the strategy and target blueprint, defining the roadmap and expected ROI. (More on that below).

When moving to a big data platform, your migration requires a tried and tested strategy to be sure to deliver the expected outcome.

Before getting started, work with the IT organization and your workload migration partners to define the overall goal of the migration, and define the project success criteria. We recommend starting by analyzing the current EDW workloads and the requirements for new analytical processing in the modernized environment. Then preparing the data to be migrated. (By the way, we call this the Assessment phase, and we’ve got tools that can automate the all-important assessment process for you and help you ensure that you do not overlook any critical steps).

2. Make predictions on performance in the new environment

Many companies rely on the broad experience of their partners to help with the approximation here, but we’ve witnessed far too many organizations skip this step. To understand how your applications will perform in the new environment, you will need to understand the current performance profile inside out. Gathering performance statistics and understanding them is mission critical. Performance optimization can help with huge datasets.  However, this step is complicated, and many organizations choose to work with partners even during the planning stage of the workload migration initiative.  Successful migration hinges on getting this preparation right and using a repeatable methodology is crucial at this step (We’ve got one).

3. Plan for the costs

It’s essential to know how much your application will cost to run in the new environment. Typically, migration to a big data environment curbs overall cost. Effective cost planning also ensures that the project does not get derailed due to inaccurate forecasting or project planning, because a new system running alongside a legacy solution can increase the operational cost by 100%. However, after migration, many enterprises realize a 300% ROI.

4. Identify aging or outdated software

Look, we still love, value, and appreciate the legacy data warehouse. It’s been the rock of the enterprise for decades. You don’t have to eliminate it entirely, but if you want the best capabilities and performance, it’s time to migrate to a modernized warehouse architecture. We can help you identify what you need to migrate and we can even define a data-driven roadmap for you.  In fact, we can simplify, optimize, and automate the whole process for you using our proven methodology.

5. Visualize your long-term success

Consider the long-term costs and benefits when making workload migration decisions. For example, investing in a good partner with experience might cost more upfront than tackling this internally, but the key is to build for scale and flexibility in the long term.

Now what?

Impetus Technologies specializes in helping large organizations to modernize their decision support environments. We are helping many organizations realize their EDW workload modernization goals with a successful implementation from start to finish. We do this by applying automation and our many lessons learned from our experience as the proven partner of choice for many leading enterprises. We offer a unique mix of full lifecycle consulting services, software tools, data science capabilities, and technology expertise:

  • Full lifecycle services

  • Technology strategy

  • Solution architecture

  • Production implementation

  • Ongoing support

No need to reinvent the wheel when doing workload migration today. For a free consultation with our experts and to learn more, call us today.

 

Venkat Chakravarthi
Venkat Chakravarthi
VP of Modern Data Architecture Practice