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Data Management Foundations C175 > Lesson 7 > Flashcards

Lesson 7 Flashcards

1
Q

Business intelligence (BI)

A

A comprehensive, cohesive, and integrated set of tools and processes used to capture, collect, integrate, store, and analyze data with the purpose of generating and presenting information to support business decision making.

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2
Q

cube cache

A

In multidimensional OLAP, the shared, reserved memory area where data cubes are held. Using the cube cache assists in speeding up data access.

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3
Q

dashboards

A

In business intelligence, a web-based system that presents key business performance indicators or information in a single, integrated view with clear and concise graphics.

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4
Q

data cube

A

The multidimensional data structure used to store and manipulate data in a multidimensional DBMS. The location of each data value in the data cube is based on its x-, y-, and z-axes. Data cubes are static, meaning they must be created before they are used, so they cannot be created by an ad hoc query.

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5
Q

data mart

A

A small, single-subject data warehouse subset that provides decision support to a small group of people.

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6
Q

data visualization

A

Abstracting data to provide information in a visual format that enhances the user’s ability to effectively comprehend the meaning of the data.

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7
Q

data warehouse

A

An integrated, subject-oriented, time-variant, nonvolatile collection of data in a specialized database that stores historical and aggregated data in a format that provides support for decision making.

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8
Q

decision support system (DSS)

A

An arrangement of computerized tools used to assist managerial decision making within a business.

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9
Q

dimension tables

A

In a data warehouse, tables used to search, filter, or classify facts within a star schema.

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10
Q

drill down

A

To decompose data into more atomic components—that is, data at lower levels of aggregation. This approach is used primarily in a decision support system to focus on specific geographic areas, business types, and so on.

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11
Q

What is the acronym ETL?

A
  • Extraction
  • Transformation
  • Loading
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12
Q

ETL

A
  • In a data warehousing environment, the integrated processes of getting data from original sources into the data warehouse.
  • ETL includes retrieving data from original data sources (extraction), manipulating the data into an appropriate form (transformation), and storing the data in the data warehouse (loading).
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13
Q

governance

A

In business intelligence, the methods for controlling and monitoring business health and promoting consistent decision making.

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14
Q

key performance indicators (KPIs)

A

In business intelligence, quantifiable numeric or scale-based measurements that assess a company’s effectiveness or success in reaching strategic and operational goals. Examples of KPIs are product turnovers, sales by promotion, sales by employee, and earnings per share.

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15
Q

master data management (MDM)

A

In business intelligence, a collection of concepts, techniques, and processes for the proper identification, definition, and management of data elements within an organization.

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16
Q

multidimensional database management systems (MDBMSs)

A

A database management system that uses proprietary techniques to store data in matrixlike arrays of “n” dimensions known as cubes.

17
Q

multidimensional online analytical processing (MOLAP)

A

An extension of online analytical processing to multidimensional database management systems.

18
Q

portals

A

In terms of business intelligence, a unified, single point of entry for information distribution.

19
Q

relational online analytical processing (ROLAP)

A

Analytical processing functions that use relational databases and familiar relational query tools to store and analyze multidimensional data.

20
Q

roll up

A

1) To aggregate data into summarized components, that is, higher levels of aggregation.
2) In SQL, an OLAP extension used with the GROUP BY clause to aggregate data by different dimensions. Rolling up the data is the exact opposite of drilling down the data.

21
Q

slice and dice

A

The ability to focus on slices of a data cube (drill down or roll up) to perform a more detailed analysis.

22
Q

sparsity

A

In multidimensional data analysis, a measurement of the data density held in the data cube.

23
Q

very large databases (VLDBs)

A

Database that contains huge amounts of data—gigabyte, terabyte, and petabyte ranges are not unusual.

24
Q

A data store is used by data analysts to create queries that access the database. (T/F)

A

False

25
Q

________ ________ is a term used to describe a comprehensive, cohesive, and integrated set of tools and processes used to capture, collect, integrate, store, and analyze data with the purpose of generating and presenting information used to support business decision making.

A

Business Intelligence

26
Q

Business intelligence tools use the data warehouse data as the raw materials for data analytics to generate business knowledge. (T/F)

A

True

27
Q

_____ tools focus on the strategic and tactical use of information.

A

Business intelligence

28
Q

Business intelligence is a framework that allows a business to transform data into information, information into knowledge, and knowledge into wisdom. (T/F)

A

True

29
Q

Business intelligence (BI) architecture is composed of data, people, processes, technology, and the management of such components. (T/F)

A

True

30
Q

______ _______ functionality ranges from simple data gathering and transformation to very complex data analysis and presentation.

A

Business intelligence

31
Q

Explanatory analytics employs mathematical and statistical algorithms, neural networks, artificial intelligence, and other advanced modeling tools to create actionable predictive models based on available data. (T/F)

A

False

Data Management Foundations C175 (7 decks)

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