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IS 335 > Exam 2- Chapter 5 > Flashcards

Exam 2- Chapter 5 Flashcards

1
Q

Our IS world is divided into two major kinds of systems:

A

Our IS world is divided into two major kinds of systems:
Transactional (Line of Business) Systems
Reporting Systems

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2
Q

We separate these because we want to:

IS world is divided into two major kinds of systems

A

We separate these because we want to:
Avoid contention in transactional systems
Integrate data from numerous other systems
Improve reporting data extraction performance
Provide a “single source of truth”

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3
Q

The data warehouse is the

A

The data warehouse is the backbone of the reporting infrastructure

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4
Q

Extract

[2]

A

Extract
Pulling data from a source
We may need to get data from multiple sources

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5
Q

Transform

A

TransformModify data for standards and consistency

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6
Q

Load

A

LoadPush the transformed data into a data mart or warehouse

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7
Q

WHY TRANSFORM?

A 
Translating / Mapping coded values
Calculating new values
Integrating from different sources
Aggregating data
Splitting / joining data
Pivoting data
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8
Q

STAGING

A

STAGING
A holding area for data that has been extracted from a source
Used to pool data from multiple sources together

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9
Q

DATA WAREHOUSE STRUCTURE
Facts

A

DATA WAREHOUSE STRUCTURE

FactsAnswer questions about WHAT happenedContains aggregable metrics

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10
Q

DATA WAREHOUSE STRUCTURE
Dimensions

A

DATA WAREHOUSE STRUCTURE
Dimensions
Answer questions about when, for what, where, for whom, and by whom.
Used to slice through the facts in different ways

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11
Q

DATA WAREHOUSE STRUCTURE

A

DATA WAREHOUSE STRUCTURE

The basic structure is called a “Star Schema”

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12
Q

DATA WAREHOUSE STRUCTURE

A

DATA WAREHOUSE STRUCTURE

Each Star is a [Data Mart]

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13
Q 
DATA MART VS DATA WAREHOUSE
A data mart is a single star schema
     
    
    
A

DATA MART VS DATA WAREHOUSE
A data mart is a single star schema
Describes a single subject or activity
Usually has one fact table or set of related fact tables
Can share dimensions with other data marts

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14
Q

DATA MART VS DATA WAREHOUSE
A data warehouse is

A

DATA MART VS DATA WAREHOUSE
A data warehouse is
Enterprise level
Aggregation of all data marts

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15
Q

DATA MART VS DATA WAREHOUSE

Essentially, a data mart is a

A

DATA MART VS DATA WAREHOUSE

Essentially, a data mart is a subject-oriented segment of a data warehouse

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16
Q

OLAP CONCEPTS

 _______ _____ Processing

A

OLAP CONCEPTS

Online Analytical Processing

17
Q

OLAP CONCEPTS

 Data Cubes are

A

OLAP CONCEPTS

 Data Cubes are multidimensional structures separated from the data warehouse

18
Q

OLAP CONCEPTS
Cubes can contain

A

OLAP CONCEPTS
Cubes can contain
Base data
Aggregations

19
Q

OLAP CONCEPTS

 Always populated from the _____ ______

A

OLAP CONCEPTS

Always populated from the data warehouse

20
Q

OLAP CONCEPTS

 Allows extraction of _____ and ______ to be faster

A

OLAP CONCEPTS

Allows extraction of data and aggregations to be faster

21
Q

OLAP CONCEPTS

 Allows extraction of _____ and ______ to be faster

A

OLAP CONCEPTS

Allows extraction of data and aggregations to be faster

22
Q

OPERATIONAL DATA STORE (ODS)

Used to

A

OPERATIONAL DATA STORE (ODS)

Used to monitor activities outside of the data warehouse

23
Q

OPERATIONAL DATA STORE (ODS)

 ______ ____ than the data warehouse

A

OPERATIONAL DATA STORE (ODS)

Less latency than the data warehouse

24
Q

OPERATIONAL DATA STORE (ODS)
Examples of values monitored can be:

A

OPERATIONAL DATA STORE (ODS)
Examples of values monitored can be:
KPI
Event flags

25
Q

OPERATIONAL DATA STORE (ODS)

Often the source for _____

A

OPERATIONAL DATA STORE (ODS)

Often the source for Dashboards

26
Q

OPERATIONAL DATA STORE (ODS)

** Does NOT replace the _____ _______!!

A

OPERATIONAL DATA STORE (ODS)

** Does NOT replace the data warehouse!!

27
Q

THE METADATA REPOSITORY

 Metadata is “ __ __ __”

A

THE METADATA REPOSITORY

 Metadata is “data about data”

28
Q

THE METADATA REPOSITORY

 Searchable _____ with _____ about ____

A

THE METADATA REPOSITORY

 Searchable repository with descriptions about data

29
Q

THE METADATA REPOSITORY
 Contains

A

THE METADATA REPOSITORY
 Contains
 Documentation of data structures
 Data dictionary with information about the content of the data structures

30
Q

THE METADATA REPOSITORY
 Examples:

A

THE METADATA REPOSITORY
 Examples:
Revenue figures are stored in tables. How do we know if they are expressed in USD or some other currency?
Does the revenue figure include sales taxes charged?

31
Q

What is ETL?

A

Extract, Transform, Load

IS 335 (15 decks)

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