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h1. |
The
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Aim
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of
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the
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Inception
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Phase
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To
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clarify
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the
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requirements
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by
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way
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of
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working
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reports,
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dashboards
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and
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OLAP
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views
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using
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prototypes
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based
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on
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real
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data.
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The
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problems
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that
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BI
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users
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have
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with
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a
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'dry'
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requirements
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process
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and
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why
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it
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is
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important
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to
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do
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prototyping
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during
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this
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phase.
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Why
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iteration
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is
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critical
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here.
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How
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to
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Gather
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Requirements
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The
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concept
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of
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a
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'Dry
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Spike'.
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Why
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Inception
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iterations
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(Dry
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Spikes)
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are
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not
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'potentially
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releasable'
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(because
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ETL
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and
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schema
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design
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is
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avoided).
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Why
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it
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is
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important
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to
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use
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real
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data:
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sponsors
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and
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users
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will
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be
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more
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excited
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by
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real
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data,
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real
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data
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can
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lead
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to
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higher
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ROI
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estimation.
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The
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problems
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with
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using
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real
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data
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(ETL,
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staging,
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latency,
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sensitivity
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etc).
...
How
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spreadsheet
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/
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flat-file
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data-sources
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and
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metadata
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can
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help
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(e.g.
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bypass
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access
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and
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security
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issues).
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How
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to
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select
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the
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data
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used.
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How
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to
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augment
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using
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spreadsheet-based
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calculations.
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The
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importance
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of
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validating
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data
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accuracy
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during
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inception.
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How
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to
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handle
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'real-time'
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and
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operational
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BI.
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Requirements:
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- How
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- to
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- spot
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- rip-and-replace
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- requirements
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- How
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- to
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- spot
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- desktop
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- reporting
...
- requirements
...
- How
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- to
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- spot
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- self-service
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- reporting
...
- requirements
...
- How
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- to
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- spot
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- ad-hoc
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- reporting
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- requirements
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- How
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- to
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- spot
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- OLAP
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- /
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- Pivot
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- View
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- requirements
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- How
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- to
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- spot
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- dashboard
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- requirementsHow
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- to
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- spot
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- ETL
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- requirements
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Child pages (Children Display)
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