Ch 17 & 18 Big Data - Exam IV

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  1. understand the problem
    identify processes involved
    identify info required to solve the prob
    gather & process data & analyze the results
    steps to identifying the right sources of data
  2. processes
    tend to be degisned as high level, end-to-end structures useful for decision making and normalizing how things get done in an org - are comprised of one or more workflows relevant to the overall objective of the process
  3. workflows
    are task-oriented and often require more specific data than processes
  4. volume
    validity - correct/quality
    veracity - meaningful
    volatility - how long does it need to 'live'
    six V's of big data
  5. validity
    true understanding of context that comes from triangulation of data
  6. triangulation
    to examine the context in different ways & from different perspectives
  7. volitility
    refers to data's useful lifespan - only keep what you need - is it relevant, or will it be in the future
  8. veracity
    the idea that data must lead to an "ah ha" moment & actionable results
  9. Enterprise Data Management (EDM)
    a comprehensive approach to defining, governing, securing, and maintaining the quality of all data involved in the business process of an org - establishes policy about and ownership of key data types - sustains a single version of the truth
  10. data governance
    data security
    data architecture
    data quality
    data ownership
    metadata warehouse
    pillars of Enterprise Data Management (EDM)
  11. cost of initial data acquisition
    cost of data maintenance - security, privacy, etc.
    two dimensions of cost of data
  12. determine timeline
    speed & amt of data are critical
    use well-established framework
    budget & HR allocation
    how much risk are you willing to accept?
    steps of implementation roadmap
  13. 1-identify business owners, review strategy, establish goals, build team, integrate into EDM, define costs
    2-identify BD source, identify affected business processes, create technology and IT operating requirements, define desired business outcomes, leverage existing infrastructure, iterate with key business stakeholders
    3-deploy business application, deploy new/modified IT operations practices, refine big data requirements for veracity and volatility, tune applications for best performance, perform after-action assessment
    major stages of big data implementation
Card Set:
Ch 17 & 18 Big Data - Exam IV
2013-11-08 18:59:18
Operationalizing Big Data Applying within Your Organization

Operationalizing Big Data & Applying Big Data within Your Organization
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