Information Management and BI 1(b) Flashcards

1
Q

What is “Data Modeling”?

A
  • Process of prescribing data format, must be standardized for efficient processing
  • Provides means for defining and analyzing data
  • Dev process incorporate business rules into data model
  • Data Modeling s/b foundation for reporting, lead to effective design of data to be captured, stored and reported
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2
Q

What is the difference btwn “Unstructured” vs “Structured” Data?

A

(1) Unstructured data:
- No prescribed format
- Capture, store and process in free form
(2) Structured data:
- Prescribed format
- Data organized and stored into files, records and fields w/ criteria for data entered into that format
- Ex: ERP transaction data
- Data must be Structured for computers to process data properly

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3
Q

Name 3 “Data Types”:

A

(1) Numbers - used for quantities, amts and
dollar amts
(2) Alphanumeric - Address( letters, numbers, characters used in data value)
(3) Dates - describe specific date format

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4
Q

What is “Data Normalization”?

A
  • Transactional flat file
  • Remove certain
    factors to eliminate data anomalies
  • Outcomes of normalized data is to maximize efficiency of data model, increases integrity associated w/ capturing and managing data
  • Eliminate data redundancy, leave any data field only once, except for duplication of key fields to establish relationships btwn files
  • Integrating data from diff systems more efficient if integration data model is normalized
  • Data files susceptible to data anomalies represents significant IT risk in that system
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5
Q

What are 3 types of “Conceptual Data Modeling” tools?

A

(1) Entity-relationship (ER) model
(2) Relational model
(3) Unified Modeling Language (UML)

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6
Q

What is the “ER Model” and what does it depict?

A
  • A Conceptual Data Modeling tools
  • Depicts relationship btwn files and records data files in a top-down fashion
  • Results = ER diagrams
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7
Q

What are “ER diagrams”?

A
  • Depicts file, type of interaction w/ another file and relationship btwn records in one file to the other
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8
Q

What is a “Relational Model”?

A
  • A Conceptual Data Modeling tool
  • Illustrates data files as tables w/ arrows from primary to foreign keys to illustrate relationship btwn data files
  • Advantage of a Relational Model is that files are depicted as a table, similar to electronic spreadsheet and fields are depicted as columns, records as rows
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9
Q

What is Unified Modeling Language (UML)?

A
  • Most recent Conceptual Data Modeling tool
  • Associated w/ object-oriented programming (OOP), newer programming languages like C sharp and Java
  • Both static and dynamic aspects can be depicted in a UML diagram
  • UML is more technical than
    ER and Relational Models
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10
Q

Name 2 “Data File” forms:

A

(1) Flat file
- All transactional data in a single record (row)
(2) Databases
- Transactional data in separate files using a structured process (outcome of data normalization)

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11
Q

What are 2 kinds of structure for data in a DW?

A
  1. Dimensional Data (“Star”)

2. Normalized Data (“Snowflake”)

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12
Q

What is the “Snowflake” Approach?

A
  • Normalization of Data
  • Tables grouped by subject areas (customers, products, employees, purchases)
  • Dozens of tables then linked by foreign/primary keys
  • Advantage: Adding data from systems to a Snowflake DW is straightforward
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13
Q

What are the Disadvantages of the “Snowflake” Approach?

A
  • Disadvantages:
    (1) Difficult to join data from different sources to obtain more meaningful info
    (2) Difficult to access info w/out thorough knowledge of data sources and DW structure
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14
Q

What is the “Star” Approach?

A
  • Dimensional Data
  • Transactional data designed and defined as facts (numeric data) or dimensions (ref info that adds meaning to the facts)
  • Includes various relevant data that describes the numeric data (dimensions)
  • Ex: Sale transaction has quantities sold and dollar amts (“facts”)
  • Includes sale date, region sold, sales rep, inv category
  • Advantage: Easier for users to understand than Snowflake Approach
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15
Q

What are Disadvantages of the “Star” Approach?

A
  • Disadvantages:
    (1) Load data from diff systems and databases complicated to get it into dimensional form
    (2) Difficult to modify DW structure if entity changes business processes or captures data
  • Struggle w/ “one way” dimension definitions
  • Must refer to and use city, state and zip code as CSZ, and must be 1 field, not 3
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