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The flashcards below were created by user
mjweston
on FreezingBlue Flashcards.
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understand the problem
identify processes involved
identify info required to solve the prob
gather & process data & analyze the results
act
steps to identifying the right sources of data
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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
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workflows
are task-oriented and often require more specific data than processes
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volume
variety
velocity
validity - correct/quality
veracity - meaningful
volatility - how long does it need to 'live'
six V's of big data
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validity
true understanding of context that comes from triangulation of data
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triangulation
to examine the context in different ways & from different perspectives
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volitility
refers to data's useful lifespan - only keep what you need - is it relevant, or will it be in the future
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veracity
the idea that data must lead to an "ah ha" moment & actionable results
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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
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data governance
data security
data architecture
data quality
data ownership
metadata warehouse
pillars of Enterprise Data Management (EDM)
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cost of initial data acquisition
cost of data maintenance - security, privacy, etc.
two dimensions of cost of data
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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
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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
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