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Summary Principles of Database Management: 18/20 eerste zit

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HIRB
3de bachelor
KU Leuven




Summary
Principles of database Management

,Table of Contents

,Chapter 1: Fundamental Concepts of Database
Management
Applications of Database Technology
- Storage and retrieval of numeric and alphanumeric data
- Multimedia
- Biometric applications
- Wearable applications
- Internet of Things (IoT)
- Big Data applications
- …

Key defi nitions
A database can be defined as a collection of related data items within a specific
business process or problem setting.
 Has a target group of users and applications
A Database Management System (DBMS) is the software package used to define,
create, use and maintain a database.
 Consists of several software modules
The combination of these two is often called a database system.

File versus Database Approach to Data Management
File Approach (= legacy file based system)
- Duplicate or redundant information will be
stored
- Danger of inconsistent data
- Strong coupling between data and
applications
o A structural change in the file,
means a change in all applications
- Hard to manage currency control
o Different applications for balance and transactions
- Hard to integrate applications aimed at providing cross-company services
Database Approach
- Superior to file approach in terms of
efficiency, consistency and maintenance
- Loose coupling between applications and
data
- Facilities provided for data querying and
retrieval
- E.g. SQL

,Database model versus instances
Database model or database schema provides the description of the data at
different levels of detail and specifies the various data items, their characteristics
and relationships, constraints, storage details, etc.
 Specified during database design, not expected to change frequently
 Stored in the catalog
o E.g. Student(number ,name ,address ,email)

Database state represents the data in the database at a particular moment.
- Also called the current set of
instance
- Typically changes on an ongoing
basis




Data Model
Data model is comprised of different data models, each describing the data from
different perspectives.
 Provides a clear and unambiguous description of the data items, their
relationships and various data constraints from a particular perspective
Conceptual data model:
= data model that provides a high-level description of the data items with their
characteristics and relationships
- Communication between information architect and business user
- Implementation independent, user-friendly, close to how business user
perceives data
- EER model, or OO model
Logical data model:
= translation or mapping of the conceptual data model towards a specific
implementation environment
- Hierarchical, CODASYL, relational, object-oriented, extended relational,
XML, NoSQL model
 Can be mapped to an internal data model that represents the data’s
physical storage details
o Describes what data is stored where, what format, which indexes are
provided,…
o Highly DBMS specific

External data model:
= contains various subsets of the data items in the logical model (= views)
tailored toward the needs of specific applications or groups of users

,Catalog
- Heart of the DBMS
- Contains the data definitions (metadata) of your database application
- Stores definitions of views, logical and internal data models, and
synchronizes these three data models to make sure consistency is
guaranteed

Database Users
Information Architect:
- Designs the conceptual data model
- Closely interacts with the business user
Database designer:
- Translates the conceptual data model into a logical and internal data model
Database administrator (DBA):
- Responsible for the implementation and monitoring of the database (KPIs)
Application developer:
- Develops database applications in a programming language such as Java
or Python
Business user:
- Will run applications to perform database operations



Database Languages
Data Definition Language (DDL):
- Used by DBA to express the database’s external, logical and internal data
models
o Definitions are stored in the catalog

, Data Manipulation Language (DML):
- Used to retrieve, insert, delete and modify data
o Statements can be embedded in a programming language, or
entered interactively through a front-end querying tool
Structured Query Language (SQL):
- Offers both DDL and DML statements for relational database systems

Advantages of Database Systems and Database
management
Data independence
- Changes in data have minimal impact on applications
- Physical data independence: the applications or the views or logical data
model don’t need to be changed when changes are made to the data
storage specifications in the internal data model
o DBMS should provide interfaces between logical and internal data
models
- Logical data independence: software applications are minimally affected by
changes in conceptual or logical data model
o Views act as protective shield
o DBMS must provide interfaces between Conceptual/logical and
external layer
Database modelling
- A model is an explicit representation of the data items with their
characteristics and relationships
- A conceptual data model should provide a formal and perfect mapping of
the data requirements of the business process and is made in collaboration
with business user
o Translated into logical and internal data model
- !assumptions and shortcomings must be documented!
Managing (Semi-) structured and unstructured data
- structured data
o described according to formal logical data model
o express integrity rules and enforce correctness of data
o facilitates searching, processing and analysing of data
- Unstructured data
o no finer grained components in a file or series of characters that can
be interpreted in a meaningful way by a DBMS or application
o E.g. document with biographies
- Semi-structured data
o Data which does have certain structure, but may be very irregular
o E.g. webpages on a social media platform,…

Managing Data Redundancy

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