Chapter 6: Foundations of Business Intelligence: Databases and Information Management

Question 1

Analytic Platform

Answer 1

Preconfigured hardware-software system that is specifically designed high-speed analysis of large datasets.

Question 2

Attribute

Answer 2

A piece of information describing a particular entity.

Question 3

Big Data

Answer 3

Datasets with volumes so huge that they are beyond the ability of typical relational DBMS to capture, store, and analyze. The data are often unstructured or semi-structured.

Question 4

Bit

Answer 4

A binary digit representing the smallest unit of data in a computer system. It can only have one of two states, representing 1 or 2..

Question 5

Byte

Answer 5

A string of bits, usually eight, used to store one number or character in a computer system.

Question 6

Data Administration

Answer 6

A special organizational function for managing the organization’s data resources, concerned with information policy, data planning, maintenance of data dictionaries, and data quality standards.

Question 7

Data Cleansing

Answer 7

Activities for detecting and correcting data in a database or file that are incorrect, incomplete, improperly formatted, or redundant. Also known as data scrubbing.

Question 8

Data Definition

Answer 8

DBMS capability that specifies the structure and content of the database.

Question 9

Data Dictionary

Answer 9

An automated or manual tool for storing and organizing information about the data maintained in a database.

Question 10

Data Governance

Answer 10

Policies and processes for managing the availability, usability, integrity, and security of the firm’s data.

Question 11

Data Inconsistency

Answer 11

The presence of different values for same attribute when the same data are stored in multiple locations.

Question 12

Data Manipulation Language

Answer 12

A language associated with a database management system that end users and programmers use to manipulate data in the database.

Question 13

Data Mart

Answer 13

A small data warehouse containing only a portion of the organization’s data for a specified function or population of users.

Question 14

Data Mining

Answer 14

Analysis of large pools of data to find patterns and rules that can be used to guide decision making decision making and predict future behavior.

Question 15

Data Quality Audit

Answer 15

A survey and/or sample of files to determine accuracy and completeness of data in an information system.

Question 16

Data Redundancy

Answer 16

The presence of duplicate data in multiple data files.

Question 17

Data Warehouse

Answer 17

A database, with reporting and query tools, that stores current and historical data extracted from various operational systems and consolidated for management reporting and analysis.

Question 18

Database

Answer 18

A group of related files.
OR A collection of data organized to service many applications at the same time by storing and managing data so that they appear to be in one location.

Question 19

Database Administration

Answer 19

Refers to the more technical and operational aspects of managing data, including physical database design and maintenance.

Question 20

Database Management System (DBMS)

Answer 20

Special software to create and maintain a database and enable individual business applications to extract the data they need without having to create separate files or data definitions in their computer programs.

Question 21

Database Server

Answer 21

A computer in a client/server environment that is responsible for running a DBMS to process SQL statements and perform database management tasks.

Question 22

Entity

Answer 22

A person, place, thing, or event about which information must be kept.

Question 23

Entity-Relationship Diagram

Answer 23

A methodology for documenting databases illustrating the relationship between various entities in the database.

Question 24

Field

Answer 24

A grouping of characters into a word, a group of words, or a complete number, such as a person’s name or age.

Question 25

File

Answer 25

A group of records of the same type.

Question 26

Foreign Key

Answer 26

Field in a database table that enables users find related information in another database table.

Question 27

Hadoop

Answer 27

Open-source software framework that enables distributed parallel processing of huge amounts of data across many inexpensive computers.

Question 28

In-Memory Computing

Answer 28

Technology for very rapid analysis and processing of large quantities of data by storing the data in the computer’s main memory rather than in secondary storage.

Question 29

Information Policy

Answer 29

Formal rules governing the maintenance, distribution, and use of information in an organization.

Question 30

Key Field

Answer 30

A field in a record that uniquely identifies instances of that record so that it can be retrieved, updated, or sorted.

Question 31

Non-Relational Database Management Systems

Answer 31

Database management system for working with large quantities of structured and unstructured data that would be difficult to analyze with a relational model.

Question 32

Normalization

Answer 32

The process of creating small stable data structures from complex groups of data when designing a relational database.

Question 33

Online Analytical Processing (OLAP)

Answer 33

Capability for manipulating and analyzing large volumes of data from multiple perspectives.

Question 34

Primary Key

Answer 34

Unique identifier for all the information in any row of a database table.

Question 35

Program-Data Dependence

Answer 35

The close relationship between data stored in files and the software programs that update and maintain those files. Any change in data organization or format requires a change in all the programs associated with those files.

Question 36

Record

Answer 36

A group of related fields.

Question 37

Referential Integrity

Answer 37

Rules to ensure that relationships between coupled database tables remain consistent.

Question 38

Relational DBMS

Answer 38

A type of logical database model that treats data as if they were stored in two-dimensional tables. It can relate data stored in one table to data in another as long as the two tables share a common data element.

Question 39

Sentiment Analysis

Answer 39

Mining text comments in an e-mail message, blog, social media conversation, or survey form to detect favorable and unfavorable opinions about specific subjects.

Question 40

Structured Query Language (SQL)

Answer 40

The standard data manipulation language for relation database management systems.

Question 41

Text Mining

Answer 41

Discovery of patterns and relationships from large set of unstructured data.

Question 42

Tuple

Answer 42

A row or record in a relational database.

Question 43

Web Mining

Answer 43

Discovery and analysis of useful patterns and information from the World Wide Web.

Question 44

What are the problems of managing data resources in a traditional file environment and how are they solved by a database management system?

Answer 44

Traditional file management techniques make it difficult for organizations to keep track of all of the pieces of data they use in a systematic way and to organize these data so that they can be easily accessed. Different functional areas and groups were allowed to develop their own files independently. Over time, this traditional file management environment creates problems such as data redundancy and inconsistency, program-data dependence, inflexibility, poor security, and lack of data sharing and availability. A database management system (DBMS) solves these problems with software that permits centralization of data and data management so that businesses have a single consistent source for all their data needs. Using a DBMS minimizes redundant and inconsistent files.

Question 45

What are the major capabilities of DBMS and why is a relational DBMS so powerful?

Answer 45

The principle capabilities of a DBMS includes a data definition capability, a data dictionary capability, and a data manipulation language. The data definition capability specifies the structure and content of the database. The data dictionary is an automated or manual file that stores information about the data in the database, including names, definitions, formats, and descriptions of data elements. The data manipulation language, such as SQL, is a specialized language for accessing and manipulating the data in the database.
The relational database has been the primary method for organizing and maintaining data information systems because it is so flexible and accessible. It organizes data in two-dimensional tables called relations with rows and columns. Each table contains data about an entity and its attributes. Each row represents a record and each column represents an attribute or field. Each table also contains a key field to uniquely identify each record for retrieval or manipulation. Relational database tables can be combined easily to deliver data required by users, provided that any two tables share a common data element. Non-relational databases are becoming popular for managing types of data that can’t be handled easily by the relational data model. Both relational and non-relational database products are available as cloud computing services.

Question 46

What are some important database design principles?

Answer 46

Designing a database requires both a logical design and a physical design. The logical design models the database from a business perspective. The organization’s data model should reflect its key business processes and decision-making requirements. The process of creating small, stable, flexible, and adaptive data structures from complex groups of data when designing a relational database is termed normalization. A well-designed relational database will not have many-to-many relationships, and all attributes for a specific entity will only apply to that entity. It will try to enforce referential integrity rules to ensure that relationships between coupled tables remain consistent. An entity-relationship diagram graphically depicts the relationship between entities (tables) in a relational database.

Question 47

What are the principal tools and technologies for accessing information from databases to improve business performance and decision making?

Answer 47

Contemporary data management technology has an array of tools for obtaining useful information from all the different types of data used by businesses today, including semi-structured and unstructured big data in vast quanitites. These capabilities include data warehouses and data marts, Hadoop, in-memory computing, and analytical platforms. OLAP represents relationships among data as a multidimensional structure, which can be visualized as cubes of data and cubes within cubes of data, enabling more sophisticated data analysis. Data mining analyzes large pools of data, including the contents of data warehouses, to find patterns and rules that can be used to predict future behavior and guide decision making. Text mining tools help businesses analyze large unstructured data sets consisting of text. Web mining tools focus on analysis of useful patterns and information from the World Wide Web, examining the structure of Web sites and activities of Web site users as well as the contents of Web pages. Conventional databases can be linked via middleware to the Web or a Web interface to facilitate user access to an organization’s internal data.

Question 48

Why are information policy, data administration, and data quality assurance essential for managing the firm’s data resources?

Answer 48

Developing a database environment requires policies and procedures for managing organizational data as well as a good data model and database technology. A formal information policy governs the maintenance, distribution, and use of information in the organization. In large corporations, a formal data administration function is responsible for information policy, as well as for data planning, data dictionary development, and monitoring data usage in the firm.
Data that are inaccurate, incomplete, or inconsistent create serious operational and financial problems for businesses because they may create inaccuracies in produce pricing, customer accounts, and inventory data, and lead to inaccurate decisions about the actions that should be taken by the firm. Firms must take special steps to make sure they have a high level of data quality. These include using enterprise-wide data standards, database designed to minimize inconsistent and redundant data, data quality audits, and data cleansing software.