How To Move Your Analytics System To The Cloud

October 19, 2019 in Analytics



How To Move Your Analytics System To The Cloud

As an increasing number of data management and analytics platforms adopt cloud systems, they stand to gain from a range of benefits – quick deployments, low IT involvement and reduced need for hardware or software maintenance. As per a research study by BARC, “BI and Data Management in the Cloud: Issues and Trends,” the number of companies using the cloud for their business intelligence program increased from 29% to 43% in the past 3 years”. 

If you too are planning to migrate your analytics systems to the cloud, use this handy checklist to launch on the path that works best for your business.

Key Decision Points

The decision to migrate your analytics platform should be based purely on your business goals: 

  • Ask yourself and your IT team if the cloud can fit in your company’s business intelligence strategy. 
  • The second step is to set the budget for initial investment, OPEX/CAPEX approval, etc. Evaluate your current analytics solution, see what’s ready and what’s on-premise. 
  • The next step involves planning the cloud environment and determining the parts to be migrated to the cloud. Review and filter your data quantity, sources and data types. 
  • See how long it takes to install new technologies and roll out its services. Assess the unique security and privacy requirements and backup strategies. 

The trend towards hosting analytics system on cloud is unrelenting and is set to transform the analytics world too. However, you must do a cost-benefit analysis of migration, impact study on data assets, map the analytic work patterns and user workflows and use the right approach to migrate. 

Determining Migration Approach

You can move your analytics system to the cloud in 3 ways: 

  • Rehosting, 
  • Re-platforming or 
  • Repurchasing. 

Rehosting involves applications that are on-premise being moved to a public cloud service without any change in the analytics fabric. 

In re-platforming, applications are changed to improve performance in the cloud. Applications can be rescaled up or down easily and variations can also be introduced quickly after re-platforming. 

In repurchasing, applications are migrated to the new cloud-native platform with minimal recoding. The rewritten or recreated applications do not require any changes by the users. Repurchase allows basic scalability and frees up the on-premise capacity. This approach provides maximum agility, innovation and scalability. 

Best Practices

The most important step in determining whether to migrate to cloud or not is to understand the extent to which the business relies on the Universe (the semantic layer between your business data and the user’s front-end reporting tools). A large enterprise needs fewer front-end reporting tools and data sources. If you have an analytics platform with different Universes and are planning a transition to cloud, you’re likely to benefit and need a migration utility.

Some business users may be using some kind of cloud-based analytics. It is important to understand why they are partial to the tools they use. Determine the tools that your traditional BI business does not have. Seek help from a cloud migration resource and tool czar. Spend time learning the shortcuts, resources and tools to help your users. Not every tool is for everyone, but by familiarising with these accelerators, you can potentially save time and have a running start on resources that can add value.

The Final Move

Despite the obvious potential of cloud migration, every decision must be based on real business needs. To affirm this, consider first rolling out a pilot. Once it is complete, the cloud environment could be suitably scaled out to deliver actionable insights for further decisions. 

Migrating analytics system to the cloud can elevate the quality of data-driven decisions involving customer engagement or operational strategy. Identify your business needs and leverage cloud-based analytics for higher speed and lower cost and create a business-led insight-driven transformation.