Summary:
Digitalization of the business place creates massive amounts
of data that must be properly managed to ensure efficiency. To do this,
Information systems must be able to provide its users with accurate and timely
information. This is why Data Management is so important. This chapter begins
with an explanation of how computer systems organize data into a hierarchy.
This hierarchy begins with a Bit,
the smallest unit of data a computer can handle, and progresses to a Database, a group of related files.
The traditional data management style can make it difficult
for companies to easily access data because of a tendency for functional systems
and groups to be allowed to grow independently. The main problem with this
system is data redundancy, inflexibility, poor security, and lack of
availability. Enter the Database Management System (DBMS). This is software
that permits an organization to centralize data, manage it efficiently, and
provide access through application programs. The DBMS manages to accomplish this
through the use of 3 capabilities. Data
definition specifies the structure of the content of the database. Data dictionary capability automates
the stored information about the data in the database. Data manipulation language, such as structured query language
(SQL), is the specialized language for accessing and manipulating the data.
Databases are not “one-size-fits-all” devices. Designing a
database to fit an organizations needs is paramount to success. This requires
both a logical and physical design. The logical aspect must reflect the business
processes of the organization and meet the decision-making requirements. The
physical aspect of its design illustrates how it is actually arranged on direct-access
storage devices. As a whole, for a database to maintain efficiency, it must
enforce referential integrity so the
relationship between data tables remains consistent.
Navigating through the vast amounts of information in a
database requires the use of powerful tools or software. One key tool is the Data Warehouse. A data warehouse
consolidates current and historical data from different operational systems to
a central database for analysis and decision-making. Another tool is Online
Analytical Processing (OLAP). This enables the user to view the same data in
different ways, using different dimensions such as price, cost, or time period.
Aside from managing database information, maintaining it
requires policies and quality assurance checks for the sharing and use of
gathered information. In most large corporations, a dedicated data
administration department is responsible for information policy, protection,
and enforcement. Inaccurate data creates serious implications for organizations
that rely on this information for the day-to-day operation of their business. By
conducting activities such as Data Cleansing,
errors in data can be corrected and enforce industry-wide standards that
prevent “bleed-over” into separate information systems.
No comments:
Post a Comment