BI and Data Warehousing Flashcards

1
Q

The concept of a data warehouse is seen as a way to provide the following three things:

A
  1. Reduce data redundancy
  2. Improve the consistency of information
  3. Enable an enterprise to use its data to make better decisions
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2
Q

Planning, implementation, and control processes to provide decision support data and support knowledge workers engaged in reporting, query, and analysis is known as:

A

Data warehousing and business intelligence

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3
Q

The primary driver for data warehousing is to support these three things:

A
  1. Operational functions
  2. Compliance requirements
  3. BI activities
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4
Q

The implementation of a Data Warehouse should follow these eight guiding principles:

A
  1. Focus on business goals
  2. Start with the end in mind
  3. Think and design globally; act and build locally
  4. Summarize and optimize last, not first
  5. Promote transparency and self-service
  6. Build metadata with the warehouse
  7. Collaborate
  8. One size does not fit all
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5
Q

A data warehouse is a combination of two primary components:

A
  1. An integrated decision support database
  2. The related software programs used to collect, cleanse, transform, and store data from a variety of operational and external sources
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6
Q

Unstructured data refers to data that is not predefined through a ______?

A

data model

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7
Q

Bill Inmon approach - Inmon defines a data warehouse as a “_____ ______, integrated, time variant and non-volatile collection of data in support of managements decision making process”

A

subject oriented

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8
Q

Kimball defines a warehouse as a “copy of ______ data specifically structured for query and analysis”

A

transaction

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9
Q

Kimball’s approach calls for what type of model?

A

Dimensional

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10
Q

In a data warehouse, data that needs correction is rejected, corrected at its source, and ideally ____?

A

re-fed through the system

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11
Q

Often the content for the data dictionary comes directly from the ______ model.

A

logical

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12
Q

Documented data lineage serves these three purposes:

A
  1. Investigation of the root causes of data issues
  2. Impact analysis for system changes or data issues
  3. Ability to determine the reliability of data, based on its origin
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