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268 Part Two Information Technology Infrastructure

Review Summary

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

2. What are the major capabilities of DBMS and why is a relational DBMS so powerful?
The principal capabilities of a DBMS includes a data definition capability, a data dictionary capabil-
ity, 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 manipulat-
ing the data in the database.
The relational database has been the primary method for organizing and maintaining data in
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.

3. What are some important database design principles?
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.

4. What are the principal tools and technologies for accessing information from databases to improve
business performance and decision making?
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 unstruc-
tured big data in vast quantities. 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 consist-
ing 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.

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