This document provides an introduction to database management systems. It discusses data, including the meanings of data, information, and knowledge. It then covers data management, including an overview and corporate data quality management. Finally, it discusses databases, including terminology and an overview, as well as applications and roles of databases.

1. INTRODUCTION TO
DATABASE
MANAGEMENT SYSTEM
Presented by
Group 5

2. Content
1 DATA
• Usage in English
• Meaning of Data, Information and Knowledge
2 DATA MANAGEMENT
• Overview
• Corporate Data Quality Management
3 DATABASE
• Terminology and Overview
• Applications and Roles

3. PART ONE
DATA

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DATA TYPES
RAW DATA
FIELD DATA
EXPERIMENTAL
DATA
refers to a
collection of
numbers,
characters and
is a relative term.
refers to raw
data that is
collected in
uncontrolled in
situ environment.
refers to data that
is generted within
the context of a
scientific
investigation by
observation and
recording.
DATA

5. USAGE
IN
ENGLISH

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DATUM
DATUM & DATA
Datum means "an item given " . In categography, geography, nuclear magnetic resonance nd technical drawing it
often refers to a reference datum where from distance to all other data are measured. Any measurement or
result is a datum, though data point is now far more common. In one sense , datum is a count noun with the
plural datums that can be used with cardinal numbers ( e.g. 80 datums )
The IEEE Computer Society allows usage of data as either a mass noun or plural based an author preference. Some
professional organizations and style guides require that an authors treat data as a plural noun. Data is most often
used as singular mass noun in educated everyday usage.

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DATA & DATUM EXAMPLE
DATUM
Height Measurement
DATA
Weather Information

8. DATA, INFORMATION AND KNOWLEDGE

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DATA, INFORMATION AND KNOWLEGE

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DATA, INFORMATION AND KNOWLEGE

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DATA INFORMATION KNOWLEDGE
Is objective Should be objective Is subjective
Has no meaning Has a meaning Has meaning for a specific
purpose
Is unprocessed Is processed Is processed and
understood
Is quantifiable, there can be
data overloaded
Is quantifiable, there can be
information overloaded
Is not quantifiable, there
can be information
overloaded
CHARACTERISTICS OF DATA, INFORMATION AND KNOWLEDGE

12. PART TWO
DATA MANAGEMENT

13. OVERVIEW

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OVERVIEW
Data Resources Management is the development and execution of architectures, policies, practices, and
procedures that properly manage the full data lifecyle needs of an enterprise.
Alternatively, the definition provided in the DAMA Data Management Book of Knowledge ( DAMA-DMBOK ) is :
"Data management is the development, execution and supervision of plans, policies, programs and practicies that
control, protect, deliver and enhance the value of data and information assets."
The concept of the "Data Management" arose in the 1980s as technology moved from sequential processing to
random access processing. Since it was now technically possible to store a single fact in a single place and access
that using random access disk, those suggesting that "Data Management" was more important than "Process
Management" used arguments such as "a customer's home address is stored in 75 places in our computer
systems."

15. CORPORATE DATA
QUALITY MANAGEMENT

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Comporate Data Quality Management ( CDQM ) is, according to the European Foundation for Quality Management and the
Competence Centre Corporate Data Quality ( CCCDQ, University of St. Gallen ), the whole set of activities intended to
improve corporate data quality ( both reactive and preventive ). Main premise of CDQM is the business relevance of high-
quality corporate data.
CORPORATE DATA QUALITY MANAGEMENT
CDQM comprises with the following activities are:
• Strategy for Corporate Data Quality: As CDQM is affected by various business drivers and requires involvement of
multiple divisions in an organisation; it must be considered a company-wide endeavour.
• Corporate Data Quality Controlling: Effective CDQM requires compliance with standard, policies, and procedures.
Compliance is monitored according to previously defined metrics and performance indicators and reported to
stakeholders.
• Corporate Data Quality Organisation: CDQM requires clear roles and responsibilities for the use of corporate data. The
CDQM organisation defines task and privileges for decision making for CDQM.
• Corporate Data Quality processes and Methods: In order to handle corporate data properly and in a standardized way
across the entire organisation and to ensure corporate data quality, standard procedures and guidelines must be
embedded in company's daily processes.

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CORPORATE DATA QUALITY MANAGEMENT
• Data Architecture for Corporate Data Quality: The data architecture consists of the data object model which
comprises the unambiguous definition and the conceptual model of corporate data and the data storage and
distribution architecture.
• Application for Corporate Data Quality: Sofftware applications supports the activities of Corporate Data Quality
Management.Their use must be planned, monitored, managed and continuously improved.

18. PART THREE
DATABASE

19. TERMINOLOGY
AND
OVERVIEW

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TERMINOLOGY AND OVERVIEW
Formally, "database" refers to the data themselves and supporting data structures. Databases are created to operate
large quantities of information by inputting, storing, retrieving, and managing that information. Databases are set up so
that one set of software programs provides all users with access to all data.
The interactions catered for by most DBMS fall into four main groups:
• Data definitiion - Defining new data structures for a database, removing the data structures from the database,
modifying the structure of existing data.
• Update - Inserting, modifying, and deleting data.
• Retrieval - Obtaining information either for end user queries and reports or for processing by applications.
• Administration - Registering and monitoring users, enforcing data security, monitoring performance, maintaning the
data integrity, dealing with concurrency control, and recovery information if the systems fails.

21. APPLICATIONS AND
ROLES

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APPLICATIONS AND ROLES

23. THANKS FOR YOUR
LISTENING!
Presenter