Leverage Big Data by Starting Small

Big data is becoming simply data. Get to the core of your business needs and pinpoint the data sources that will propel their processes.


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Neglecting to investigate big data use cases within your organization can result in:

  • Missed opportunities to differentiate competitively within your industry.
  • Business user frustration due to the limitations of current reporting.

Incorporating big data as a new initiative helps to:

  • Lay a foundation for collaborative innovation between business users and IT.
  • Provide impetus for investing in and improving core data management practices.

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Onsite 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 onsite delivery of our Project Workshops. We take you through every phase of your project and ensure that you have a road map in place to complete your project successfully.

Module 1: Undergo Big Data Education

The Purpose

  • Understand the basic elements of big data and its relationship to traditional business intelligence.

Key Benefits Achieved

  • Common, foundational knowledge of what big data entails.

Activities: Outputs:
1.1 Determine which of the four Vs is most important to your organization.
  • Relative importance of the four Vs from IT and business perspectives
1.2 Explore new data through a social lens.
1.3 Brainstorm new opportunities for enhancing current reporting assets with big data sources.
  • High-level improvement ideas to report artifacts using new data sources

Module 2: Assess Your Big Data Readiness

The Purpose

  • Establish an understanding of current maturity for taking on big data, as well as revisiting essential data management practices.

Key Benefits Achieved

  • Concrete idea of current capabilities.
  • Recommended actions for developing big data maturity.

Activities: Outputs:
2.1 Determine your organization’s current big data maturity level.
  • Established current state maturity
2.2 Plan for big data management.
  • Foundational understanding of data management practices in the context of a big data initiative

Module 3: Pinpoint Your Killer Big Data Use Case

The Purpose

  • Explore a plethora of potential use cases at the industry and business unit level, followed by using the variety element of big data to identify the highest value initiative(s) within your organization.

Key Benefits Achieved

  • In-depth characterization of a pilot big data initiative that is thoroughly informed by the business context.

Activities: Outputs:
3.1 Identify big data use cases at the industry and/or departmental levels.
  • Potential big data use cases
3.2 Conduct big data brainstorming sessions in collaboration with business stakeholders to refine use cases.
  • Potential initiatives rooted in the business context and identification of valuable data sources
3.3 Revisit the variety dimension framework to scope your big data initiative in further detail.
  • Identification of specific data sources and data elements
3.4 Create an organizational 4-column data flow model with your big data sources/elements.
3.5 Evaluate data sources by considering business value and risk.
  • Characterization of data sources/elements by value and risk
3.6 Perform a value-effort assessment to prioritize your initiatives.
  • Prioritization of big data use cases

Module 4: Structure a Big Data Proof-of-Concept Project

The Purpose

  • Put together the core components of the pilot project and set the stage for enterprise-wide support.

Key Benefits Achieved

  • A repeatable framework for implementing subsequent big data initiatives.

Activities: Outputs:
4.1 Construct a work breakdown structure for the pilot project.
  • Comprehensive list of tasks for implementing the pilot project
4.2 Determine your project’s need for a data scientist.
  • Decision on whether or not a data scientist is needed, and where data science capabilities will be sourced
4.3 Establish the staffing model for your pilot project.
  • RACI chart for the project
4.4 Perform a detailed cost/benefit analysis.
  • Big data pilot cost/benefit summary
4.5 Make architectural considerations for supporting the big data initiative.
  • Customized, high-level architectural model that incorporates technologies that support big data
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