SlideShare a Scribd company logo
INTRODUCTION TO
DATABASE
MANAGEMENT SYSTEM
Presented by
Group 5
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
PART ONE
DATA
01 Add your title
Add your text here. Add your text here.
Text
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
USAGE
IN
ENGLISH
01 Add your title
Add your text here. Add your text here.
Text
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.
01 Add your title
Add your text here. Add your text here.
Text
DATA & DATUM EXAMPLE
DATUM
Height Measurement
DATA
Weather Information
DATA, INFORMATION AND KNOWLEDGE
01 Add your title
Add your text here. Add your text here.
Text
DATA, INFORMATION AND KNOWLEGE
01 Add your title
Add your text here. Add your text here.
Text
DATA, INFORMATION AND KNOWLEGE
01 Add your title
Add your text here. Add your text here.
Text
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
PART TWO
DATA MANAGEMENT
OVERVIEW
02 Add your title
Add your text here. Add your text here.
Text
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."
CORPORATE DATA
QUALITY MANAGEMENT
02 Add your title
Add your text here. Add your text here.
Text
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.
02 Add your title
Add your text here. Add your text here.
Text
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.
PART THREE
DATABASE
TERMINOLOGY
AND
OVERVIEW
03 Add your title
Add your text here. Add your text here.
Text
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.
APPLICATIONS AND
ROLES
03 Add your title
Add your text here. Add your text here.
Text
APPLICATIONS AND ROLES
THANKS FOR YOUR
LISTENING!
Presenter

More Related Content

PPTX
CDMP SLIDE TRAINER .pptx
PPTX
Data Governance for Enterprises
PPTX
Enterprise Data Governance for Financial Institutions
PPTX
The Key Reason Why Your DG Program is Failing
 
PPTX
Data Governance without AI Course Week 2.pptx
PDF
Workable Enteprise Data Governance
PDF
2014 dqe handouts
PDF
Data-Ed Webinar: Data Quality Engineering
CDMP SLIDE TRAINER .pptx
Data Governance for Enterprises
Enterprise Data Governance for Financial Institutions
The Key Reason Why Your DG Program is Failing
 
Data Governance without AI Course Week 2.pptx
Workable Enteprise Data Governance
2014 dqe handouts
Data-Ed Webinar: Data Quality Engineering

Similar to INTRODUCTION TO DATABASE MANAGEMENT SYSTEM (20)

PPTX
Data Governance Course without AI_Week 3-4.pptx
PPTX
From DQ to DG
PPTX
Data Governance_Notes.pptx
PDF
Introduction to Data Governance
PDF
DG - general intro ENG
PPT
Data Governance challenges in a major Energy Company
PPT
Data Collection Process And Integrity
PPTX
Information architecture overview
PDF
Data Quality Strategy: A Step-by-Step Approach
PPT
Image Resampling Detection Based on Convolutional Neural Network Yaohua Liang...
PDF
Why data governance is the new buzz?
PPTX
Importance of Data Governance
PDF
DGIQ - Case Studies_ Applications of Data Governance in the Enterprise (Final...
PPT
Metadata Repositories in Health Care - Master Data Management Approach to Met...
PPTX
DGIQ 2013 Learned and Applied Concepts
PPTX
data collection, data integration, data management, data modeling.pptx
PDF
Article Week 20-August-2024-Radha-Data Engineering Services (1).pdf
PDF
Data Governance Maturity Levels
PPTX
Chief Data Officer
PDF
Data Quality in Data Warehouse and Business Intelligence Environments - Disc...
Data Governance Course without AI_Week 3-4.pptx
From DQ to DG
Data Governance_Notes.pptx
Introduction to Data Governance
DG - general intro ENG
Data Governance challenges in a major Energy Company
Data Collection Process And Integrity
Information architecture overview
Data Quality Strategy: A Step-by-Step Approach
Image Resampling Detection Based on Convolutional Neural Network Yaohua Liang...
Why data governance is the new buzz?
Importance of Data Governance
DGIQ - Case Studies_ Applications of Data Governance in the Enterprise (Final...
Metadata Repositories in Health Care - Master Data Management Approach to Met...
DGIQ 2013 Learned and Applied Concepts
data collection, data integration, data management, data modeling.pptx
Article Week 20-August-2024-Radha-Data Engineering Services (1).pdf
Data Governance Maturity Levels
Chief Data Officer
Data Quality in Data Warehouse and Business Intelligence Environments - Disc...
Ad

Recently uploaded (20)

PDF
A comparative analysis of optical character recognition models for extracting...
PDF
Unlocking AI with Model Context Protocol (MCP)
PDF
gpt5_lecture_notes_comprehensive_20250812015547.pdf
PDF
Accuracy of neural networks in brain wave diagnosis of schizophrenia
PPTX
SOPHOS-XG Firewall Administrator PPT.pptx
PPTX
OMC Textile Division Presentation 2021.pptx
PDF
DP Operators-handbook-extract for the Mautical Institute
PPTX
cloud_computing_Infrastucture_as_cloud_p
PPTX
Programs and apps: productivity, graphics, security and other tools
PDF
Building Integrated photovoltaic BIPV_UPV.pdf
PPTX
Digital-Transformation-Roadmap-for-Companies.pptx
PDF
7 ChatGPT Prompts to Help You Define Your Ideal Customer Profile.pdf
PDF
Microsoft Solutions Partner Drive Digital Transformation with D365.pdf
PDF
MIND Revenue Release Quarter 2 2025 Press Release
PPTX
A Presentation on Artificial Intelligence
PPTX
Chapter 5: Probability Theory and Statistics
PDF
Assigned Numbers - 2025 - Bluetooth® Document
PDF
Profit Center Accounting in SAP S/4HANA, S4F28 Col11
PPTX
A Presentation on Touch Screen Technology
PPTX
1. Introduction to Computer Programming.pptx
A comparative analysis of optical character recognition models for extracting...
Unlocking AI with Model Context Protocol (MCP)
gpt5_lecture_notes_comprehensive_20250812015547.pdf
Accuracy of neural networks in brain wave diagnosis of schizophrenia
SOPHOS-XG Firewall Administrator PPT.pptx
OMC Textile Division Presentation 2021.pptx
DP Operators-handbook-extract for the Mautical Institute
cloud_computing_Infrastucture_as_cloud_p
Programs and apps: productivity, graphics, security and other tools
Building Integrated photovoltaic BIPV_UPV.pdf
Digital-Transformation-Roadmap-for-Companies.pptx
7 ChatGPT Prompts to Help You Define Your Ideal Customer Profile.pdf
Microsoft Solutions Partner Drive Digital Transformation with D365.pdf
MIND Revenue Release Quarter 2 2025 Press Release
A Presentation on Artificial Intelligence
Chapter 5: Probability Theory and Statistics
Assigned Numbers - 2025 - Bluetooth® Document
Profit Center Accounting in SAP S/4HANA, S4F28 Col11
A Presentation on Touch Screen Technology
1. Introduction to Computer Programming.pptx
Ad

INTRODUCTION TO DATABASE MANAGEMENT SYSTEM

  • 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
  • 4. 01 Add your title Add your text here. Add your text here. Text 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
  • 6. 01 Add your title Add your text here. Add your text here. Text 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.
  • 7. 01 Add your title Add your text here. Add your text here. Text DATA & DATUM EXAMPLE DATUM Height Measurement DATA Weather Information
  • 9. 01 Add your title Add your text here. Add your text here. Text DATA, INFORMATION AND KNOWLEGE
  • 10. 01 Add your title Add your text here. Add your text here. Text DATA, INFORMATION AND KNOWLEGE
  • 11. 01 Add your title Add your text here. Add your text here. Text 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
  • 14. 02 Add your title Add your text here. Add your text here. Text 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."
  • 16. 02 Add your title Add your text here. Add your text here. Text 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.
  • 17. 02 Add your title Add your text here. Add your text here. Text 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.
  • 20. 03 Add your title Add your text here. Add your text here. Text 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.
  • 22. 03 Add your title Add your text here. Add your text here. Text APPLICATIONS AND ROLES