Optimize the DRP for Business-Critical Analytics
As analytics become more critical to business processes, whether it's big data or “small” data, your DRP needs to keep up.
- The criticality of analytics is often not clearly defined as it evolves from simply collecting data to generating insights that drive business decisions.
- As analytics and its source data continue to grow, it’s also too costly to simply apply the same backup and DR strategy to all of your data.
- The compute power required to drive analytics engines presents yet another potentially costly challenge for DR planning.
Our Advice
Critical Insight
- Business users who depend on analytics are not thinking about DR. IT needs to be proactive to understand when analytics evolve from “nice to have” to critical, before a disaster occurs.
- Not all source data and/or generated analytics require the same DR strategy (e.g. depending on to what extent historical data is used to drive analytics and how long it takes to regenerate analytics).
- Old decommissioned servers, often used to provision DR sites, may not provide the required performance for analytics engines.
Impact and Result
- Start by defining business process workflows to identify when and how analytics are being used and whether analytics can simply be regenerated or deferred.
- Evaluate the criticality of source data and generated analytics, based on business requirements, to determine appropriate recovery time and recovery point objectives.
- Adapt your existing DRP and DR solution to meet the storage, velocity, and compute requirements for critical analytics.
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Contributors
- Dr. Bernard A. Jones, Business Continuity Consultant – BC Management/B. Jones BCP Consulting, LLC
- Steve Tower, Management Consultant, Disaster Recovery Plans & Assessments
- Jack Norris, SVP, Data & Applications, MapR
- Three additional contributors who wished to remain anonymous
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