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To Cloud or Not to Cloud – Should You Migrate Your Data Warehouse?

Legacy data warehouses have many challenges and raise many questions that drive a continuing discussion about the health of the data warehouse.  Some of my colleagues at Eckerson Group have declared that the data warehouse is dead while others position it as a tool in the data toolbox or as evolving and being reinvented as a modern data warehouse. I very firmly believe that the data warehouse is alive and that it has an important place in the future of data management.  Cloud migration is one option for data warehouse modernization with many benefits including scalability, elasticity, cost savings, and performance gains.

Despite the many benefits, cloud data warehousing isn’t the right fit for every organization or for all data warehouses. When deciding whether to migrate to the cloud, systematically assess your needs in the sixteen areas described below. Then perform SWOT analysis to help you make an informed decision.  

  •  Data Warehouse Architecture – If your data warehouse is well designed, cost-to-value efficient, and able to meet business needs then architecture is not a strong driver for cloud migration. Cloud migration is a good time to modernize data warehouse architecture.
  • Technical Debt – Evaluate the amount of technical debt that you have assumed or will assume in the future. When entropy, lack of reliable documentation, and aging technology create future technical issues, cloud data warehousing offers solutions to reduce or minimize technical debt.
  • Technology Architecture – Compatibility with technology architecture is an important consideration. When cloud hosted applications are part of technology direction, and when your organization has invested in building cloud skills and expertise, then cloud data warehousing is a natural fit.
  • Networking – Moving data across networks—most commonly the internet—is an inherent part of cloud-hosted systems. Limited network bandwidth, as discussed earlier, is only one issue. Concerns about security of data moving over networks may inhibit cloud adoption.
  • Data Warehouse Operations – When downtime and error frequency are concerns for an on-premises data warehouse cloud hosting offers some solutions. The data warehouse maintenance burden may also be reduced as the migration process improves structure, consistency, and quality of documentation.
  • Data Center Operations – Cloud adoption is a form of outsourcing that directly affects data center operations. Moving to the cloud reduces the data center footprint with corresponding reduction of cost and staffing—an effect sometimes called infrastructureless culture.
  • Disaster Recovery and Business Continuity – When disaster recovery and business resumption are key concerns cloud hosting offers some unique advantages. Give cloud migration strong consideration when your data warehouse is business critical or mission critical. Also consider whether data warehousing is sufficiently integrated into your DRBR plan and the time and cost of recovery for a lost or corrupted data warehouse.
  • Scalability and Elasticity – Scalability and elasticity are substantial benefits of cloud systems and are among the top reasons to migrate a data warehouse to the cloud. Though inviting characteristics they are of little value, however, if you without real business and technical needs for scaling and dynamic resource allocation.
  • Data Types – When the data warehouse must be fitted into modern data architecture—big data, unstructured data, NoSQL databases, data lakes, etc.—cloud migration can help. Many of the big data technologies are cloud optimized and co-locating data lake and data warehouse has some clear advantages.
  • Agility – The “instant infrastructure” characteristics of cloud deployments reduce project delays and enhance agility. Consider this to be a plus when you have or anticipate an ongoing flow of new projects.
  • Governance – Cloud migration adds new dimensions to data governance responsibilities. When migrating to the cloud it is important that data governance practices recognize and adapt to cloud governance issues.
  • Security – Security is an often-cited concern for cloud hosted data, a concern that may be more about perception than reality. Evaluate service provider security practices including physical security and hardening of servers. Virtual private cloud (VPC) increases the security level for cloud hosted data. Securing data as it moves across networks is a practical concern.
  • Compliance – Consider carefully the degree to which your data is subject to regulatory compliance. Data privacy, protection of personally identifying information (PII), and data location are primary concerns that sometime lead to hybrid deployments with privacy-sensitive data hosted locally and less sensitive data in the cloud.
  • Data Quality – Cloud hosting has data quality implications. Ask questions about service provider data quality capabilities and about data quality responsibilities. Data governance should certainly have a role in data quality discussions.
  • Self-Service – Self-service reporting and analysis capabilities can be enhanced with cloud deployments. Many of the self-service tools are cloud optimized. When data analysts need capability to write back to the data warehouse, cloud hosting may be an inhibitor.
  • Commitment – Politics and people can’t be overlooked as real considerations when making the decision to move your data warehouse to the cloud. Do you have the resources, support, sponsorship, and political will to do it right?

SWOT Analysis for Cloud Migration

Keeping in mind the sixteen factors described above, conduct SWOT analysis to develop conclusions about feasibility of cloud migration for your data warehouse. The matrix below suggests some areas to consider in each area when performing SWOT for data warehouse migration.

These short lists are intended to promote breadth and depth of thought when identifying strengths, weaknesses, opportunities, and threats. It is not an exhaustive list so don’t be limited by lists. Inform the SWOT process using other good sources of information such as the Eckerson Group report BI and Data Management in the Cloud: Issues and Trends.

Developing a SWOT matrix is only the first step of analysis. Next, review the matrix to answer these questions:

  • How can you leverage strengths to best advantage?
  • How will strengths help to overcome weaknesses and threats?
  • How will strengths help to capitalize on opportunities?
  • How can you remediate weaknesses to minimize their impact?
  • How can you turn opportunities into realities?
  • How can you mitigate or eliminate threats?

 With this analysis you are well positioned to make an informed decision when answering the question To Cloud or Not to Cloud.

Dave Wells

Dave Wells is an advisory consultant, educator, and industry analyst dedicated to building meaningful connections throughout the path from data to business value. He works at the intersection of information...

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