9 key rules for transitioning a data and analytics strategy to the cloud

The availability of cloud services focused on data and analytics technology has matured in the last few years.

Now, with varied cloud service options for storage and compute, enterprises are able to have better control on cost. With flexible pricing models, enterprises adopting cloud to modernize their data and analytics architecture is increasing.

Cloud transformation is a good case to build a strong data foundation supported by some of the paramount capabilities like real-time, higher performance, scalability, reliability, AI integration and ease of delivery. However there are several questions to be asked before getting started on the data warehouse cloud transformation journey:

Further confusion is created by the proliferation of varied cloud services and options that are available across all cloud platforms, including Microsoft, Amazon or Google.

Following are the nine key rules to be considered in getting an on-premises data and analytics environment successfully transformed to the cloud.

Perform a comprehensive analysis of the existing data warehouse to understand the functionality delivered and the pros and cons. This will create the existing data environment documentation.

Having this provides visibility in terms of current state complexity and helps in building a confident transformation project plan. This will also help in getting to know commonality in terms of data, challenges and design patterns, and build an optimized, consolidated cloud transformation.

Since many of the larger data environments would have got built across 20-plus years, automation of this discovery and assessment process is a must.

Rule 2: Understand business stakeholder pain points and their needs

Plan for sessions with the business team to understand their current challenges and what is critical for them. This will help in delivering key business needs as part of cloud transformation. As you talk to the business units, it’s important to present some of the cloud capabilities and use cases relevant to the business.

Rule 3: Choose the cloud platform and its services

Choosing a cloud platform is generally driven at the enterprise level, but choosing the cloud services is driven by the functionality required by the data teams.

The important task is in listing the functionality in the existing environment and mapping them to the services on Azure or AWS or GCP. This is also an opportunity to bring in cloud services that will improve existing processes like automating manual data uploads, more frequent data refresh and cognitive services.