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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.

Optimize the DRP for Business-Critical Analytics Research & Tools

Start here – read the Executive Brief

Read our concise Executive Brief to find out why you should optimize the DRP for business-critical analytics, review Info-Tech’s methodology, and understand the four ways we can support you in completing this project.

1. Identify critical analytics in business processes

Discover critical analytics data sets within business processes. Evaluate critical dependencies, single points of failure, and worst-case scenarios for analytics downtime.

2. Determine DR requirements for critical analytics

Document critical analytics data in the Data Criticality Inventory Tool. Define levels of criticality within analytics data, and assess RTO and RPO requirements for each data set.

3. Update the DR solution to meet analytics DR requirements

Leverage Info-Tech’s Executive Presentation Template and the Project Planning and Prioritization Tool to support the implementation of an optimized DR solution.

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Guided Implementation




Workshop: Optimize the DRP for Business-Critical Analytics

Workshops offer an easy way to accelerate your project. If you are unable to do the project yourself, and a Guided Implementation isn't enough, we offer low-cost delivery of our project workshops. We take you through every phase of your project and ensure that you have a roadmap in place to complete your project successfully.

Module 1: Map Out Key Business Processes

The Purpose

  • Identify critical business processes that rely on analytics data.
  • Determine where within the business process is analytics data critical and what the business impact is if the analytics data was not available during downtime.  

Key Benefits Achieved

  • Define analytics data dependencies within critical business processes.
  • Uncover knowledge gaps where the business is leveraging analytics data in a way that IT is not aware of.




Document critical business processes.

  • Document a prioritized list of key business processes.

Map out data-driven business processes.

  • Create visual business process documentation.

Determine where analytics data becomes critical in the business process.

  • Identify data dependencies within the business process.

Module 2: Initiate the Data Criticality Assessment

The Purpose

  • Establish a program to evaluate which data sets warrant higher availability.
  • Identify and document which repositories currently hold critical analytics data.

Key Benefits Achieved

  • Differentiate levels of criticality within data sets and identify the most critical analytics data.
  • Determine which repositories should be given the highest priority.




Create the data criticality inventory scheme.

  • Organized data criticality schema.

Identify and describe data repositories.

  • Documented list of data repositories.

Begin documenting data sets in the data criticality inventory.

Module 3: Complete the Data Criticality Assessment

The Purpose

  • Document all critical analytics data sets into the data criticality inventory tool.
  • Determine DR requirements for each specific data set.
  • Evaluate potential DR solutions based on DR requirements.

Key Benefits Achieved

  • Catalog of critical analytics data sets that are matched to each repository.
  • Differentiate between each data set and prioritize available resources.
  • Overview available options and select a best-fit solution.




Complete the data criticality inventory.

  • Finalize the Criticality Inventory Tool.

Assign RTO and RPO requirements based on business impact.

  • Updated business impact analysis.

Assess the recommended recovery solutions based on DR requirements.

  • Review DR solution recommendations.

Module 4: Optimize the Disaster Recovery Plan

The Purpose

  • Define an appropriate deployment model for the desired DR solution.
  • Garner executive support for current and future DR projects.
  • Document the necessary project steps to implement the desired DR solution.

Key Benefits Achieved

  • Select a DR solution that fits into your current DR environment and management appetite for DR initiatives.
  • Level set people, process, and technology requirements for the DR solution.
  • Organize tasks and determine FTE gaps or budget gaps within the implementation plan.




Review the DR solution selection methodology.

  • Select the appropriate DR solution based on a benefits/costs analysis.

Craft the Executive Presentation Deck.

  • Create a tailored executive presentation which summarizes progress to date and future initiatives.

Complete the Project Planning and Prioritization Tool.

  • Prioritized list of projects with FTE and budget analysis.
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About Info-Tech

Info-Tech Research Group is the world’s fastest-growing information technology research and advisory company, proudly serving over 30,000 IT professionals.

We produce unbiased and highly relevant research to help CIOs and IT leaders make strategic, timely, and well-informed decisions. We partner closely with IT teams to provide everything they need, from actionable tools to analyst guidance, ensuring they deliver measurable results for their organizations.


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What Is a Blueprint?

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Each blueprint can be accompanied by a Guided Implementation that provides you access to our world-class analysts to help you get through the project.

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Guided Implementation 1: Identify critical analytics in business processes
  • Call 1: Evaluate the criticality of each business process as it relates to business impact.
  • Call 2: Leverage tabletop planning exercises to map out business processes.
  • Call 3: Determine where the critical business process requires analytics data.

Guided Implementation 2: Determine critical analytics DR requirements
  • Call 1: Leverage the Data Criticality Inventory Tool to determine current data criticality and location.
  • Call 2: Review the results of the data criticality assessment.
  • Call 3: Interpret the results of the data criticality assessment and compare against current DR solution.

Guided Implementation 3: Update the DR solution
  • Call 1: Leverage the Evaluate Cloud, Co-lo, and In-House DR Deployment Models blueprint to optimize current DR solution.
  • Call 2: Craft an executive presentation plan to keep executives engaged.
  • Call 3: Use the Project Planning and Prioritization Tool to document next steps.


Frank Trovato

David Xu


  • 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

Search Code: 79202
Last Revised: May 5, 2016

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