Chapter 3: Data and business intelligence Flashcards

1
Q

Database

A

an organized collection of structured information, or data, typically stored electronically in a computer system.
- collection of related data

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2
Q

Benefits of a database

A
  1. Improved data management
  2. Data redundancy is eliminated or minimized
  3. Storage space is used more efficiently
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3
Q

Feilds

A

columns

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4
Q

Records

A

rows

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5
Q

File Access methods

A
  1. Sequential access = records are organized sequentially. (used for archives and backups)
  2. Random access = not in any order. Faster for accessing few records
  3. Indexed sequential access = combination
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6
Q

Two ways information is viewed in a database

A
  1. Physical view = how data is stored and retrieved. (only one type of physical view)
    2.Logical view = how information appears to users. (can be more than one logical view)
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7
Q

Data models 3 components

A
  1. Data structure = describes how data is organized
    2.Operations = describes methods and calculations that can be preformed
  2. Integrity rules = defines boundaries of a database
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8
Q

Database design models (3)

A
  1. Hierarchical model = the relationship among records from a tree like structure
  2. Network model
  3. Relational model = 2 dimensional table of records and columns
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9
Q

Primary key

A

uniquely identifies each record in a relational database

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10
Q

Foreign key

A

A field in a relational table that matches the primary key field of another table. It is used to reference the tables and attach them.

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11
Q

Normalisation

A

Improves database efficiency by eliminating redundant data

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12
Q

DBMS = database management system

A

Software for creating , storing and maintaining and accessing database files

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13
Q

Database engine

A

the underlying software component that a database management system (DBMS) uses to create, read, update and delete (CRUD) data from a database.
- The heart of the DBMS

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14
Q

Data manipulation

A

the process of organizing or arranging data in order to make it easier to interpret. (adding, deleting, retrieving records from a database)

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15
Q

components of a DBMS

A
  1. Database engine
  2. Data definition
  3. Data manipulation
  4. Application generation
  5. Data administration
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16
Q

Distributed databases

A

Data is stored on more than one server throughout the company

17
Q

Object oriented databases

A

1.Both data and their relationships are contained in a single object.
2.An object consists of attributes and methods that can be performed on the object’s data.

18
Q

Data warehouse

A

Collection of data from different sources used to support decision-making applications and generate business intelligence

19
Q

Characteristics of data in a data warehouse (Functions)

A

1.Subject oriented – focus on specific area
2.Integrated – comes from variety of sources
3.Time variant – categorized based on time
4.Type of data – captures aggregated data
5.Purpose – used for analytical purposes

20
Q

Components of a data warehouse

A
  1. Input
  2. Extraction, transformation and loading (ETL)
    3.Storage
    4.Output
21
Q

Extraction as a component of a data warehouse

A

extraction = collecting data from a variety of sources
- converting data into the format that can be used in the transformation process

22
Q

Transformation processing as a component of data warehousing

A

makes sure data meet the data warehouse’s needs

23
Q

Ways information is organized in a data warehouse

A
  1. Raw data = original form
  2. Summary data
  3. Metadata = data about data”. Metadata is defined as the data providing information about one or more aspects of the data
24
Q

Output

A

Data warehouse supports different types of analysis and generates reports for decision making.

1.Online analytical processing
2.Data mining analysis
3.Decision making reports

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Data mart
a simple form of a data warehouse that is focused on a single subject or line of business, such as sales, finance, or marketing
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Types of business analytics
1. Descriptive 2. Predictive 3. Prescriptive
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Other types of analytics
1.Web analytics 2.Mobile analytics
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Big data
Massive volumes of data (to large data for normal computing tools)
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Big data : 5 V's
1. Volume = large number of transactions 2.Variety = different types of data 3. Velocity = speed at which things happen 4. Veracity = trustworthiness and accuracy 5. Value = what it can be used for
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