Overview of Databases and Data Modelling-1.pdf

Overview of Databases and Data Modelling
(Part – 1)
2/20/2024 Christalin Nelson | Systems Cluster | SoCS

At a Glance
• Introduction
• An Example
• Characteristics of the Database Approach
• Actors on the Scene
• Workers behind the Scene
• Advantages of Using the DBMS Approach
• A Brief History of Database Applications
• When Not to Use a DBMS
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DBMS: A daily necessity
• Essential Component of interaction through various applications
– Traditional database applications
• Store textual or numeric information
– Multimedia databases
• Store images, audio clips, and video streams digitally
– Geographic information systems (GIS)
• Store and analyze maps, weather data, and satellite images
– Data warehouses and OLAP systems
• Extract and analyze useful business information from very large databases
• Support decision making
– Real-time and active database technology
• Control industrial and manufacturing processes
– WWW
• Internet Search
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Introduction (1/5)
• Data
– Known facts that can be recorded
• Database (DB)
– Collection of related data that have implicit meaning
– Properties
• Built for a specific purpose – intended for a user group directly or via applications
• Logically coherent collection of data with inherent meaning
• Represents some aspect of the real world
Has some source from
which data is derived
Has some degree of interaction
with events in real world
Has an audience that is
actively interacting
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Introduction (2/5)
• DBMS
– A general-purpose software system (collection of programs) that facilitates
• Database Definition
– Specify data types, structures, and data constraints
• Database Construction
– Store data on some storage medium controlled by DBMS
• Database Manipulation
– Retrieve and update, report generation
• Database Sharing
– Permit multiple users and programs to access simultaneously
– Note
• The used DBMS can also be a special purpose system (manually generated)
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Introduction (3/5)
• Simplified DB system environment
– Application program
• Accesses DB by sending queries to DBMS
– Query
• Interaction with DB
• This causes some data to be retrieved/updated
– Transaction
• Causes data R/W into DB
– Meta-data
• Stored as DB catalog or dictionary
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Introduction (4/5)
• DBMS provides protection
– System Protection
• Against software and hardware malfunction or crash
– Security Protection
• Against unauthorized or malicious access
• DBMS can maintain the DB system
– Evolve as requirements change over time (life cycle of DB)
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Introduction (5/5)
• Example of a large commercial database?
– Amazon Aurora (RDB engine)
Amazon.com
Storage: 2TB worth
Stored on: 200 different servers
Visitors per day: about 15million
People reqd. to keep DB up-to-date: about 100
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Example: University DB (1/3)
• Purpose
– To maintain information concerning students, courses, and grades in a university
environment
• Data Records
– A record consists of data elements of different data types
– Stored in five files
– Records are related
• File (in Conceptual level)
– Collection of ordered/unordered data records of the same type
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Database Structure
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Example: University DB (3/3)
• Manipulation involves querying and updating
– Examples of queries:
• Retrieve the transcript
• List the names of students who took the section of the ‘Database’ course offered in fall
2008 and their grades in that section
• List the prerequisites of the ‘Database’ course
– Examples of updates:
• Change the class of ‘Smith’ to 2
• Create a new section for the ‘Database’ course for this semester
• Enter a grade of ‘A’ for ‘Smith’ in the ‘Database’ section of last semester
• Note:
– The above should be specified in Query language of DBMS before processing
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Phases of Database Design (1/2)
• Information System
– Consists of various computers, storage systems, application software, and DBs
• i.e. DB is considered as a part of a larger undertaking
– IT department within a company, designs and maintains an Information System
• Phases in designing new DB or Application with existing DB
Requirements specification and
analysis
Conceptual design
Logical design
Physical design
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Phases of Database Design (2/2)
In physical design, further specifications are provided for storing & accessing the DB. The design is implemented,
populated with actual data, and continuously maintained to reflect the state of the mini-world.
The conceptual design is then translated to a logical design.
[Expressed in a data model implemented in a commercial DBMS. E.g. Relational Data Model]
Requirements are documented in detail & transformed into a conceptual design. E.g. Entity-Relationship model
[Represented & manipulated using computerized tools  easily maintained, modified, & transformed into a DB]
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Traditional vs. Database Approach
• Traditional File processing
– Each user defines & implements the files needed for a specific software application as
part of programming the application
– Example: Consider 2 users (Grade reporting officer & Account Officer) interested in
student data
• Pros: Each user maintains separate files and programs to manipulate these files because
each requires some data not available from the other user’s files.
• Cons: Redundancy in defining and storing data results in wasted storage space and in
redundant efforts to maintain common up-to-date data.
• Database approach
– Maintain a single data repository that is defined once & accessed by various users
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Characteristics of Database approach (1/10)
• Main characteristics of database approach
– Self-describing nature of a DB system
– Insulation between programs and data, and data abstraction
– Support of multiple views of the data
– Sharing of data & multiuser transaction processing
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• Self-Describing Nature of a Database System
– Contains DB + Metadata (stored in Catalog)
• Meta-data: File structure, Type/Storage format of each data item, & data constraints
– Specified by the DB designer before creating the actual DB
– Database catalog used by
• DBMS software
– General purpose DBMS (not written for a specific application) refers to Catalog
» Works for any number of DB applications
• DB users (need information about DB structure)
– Vs. Traditional File Processing (TFP)
• DBMS software can access diverse DBs as long as the definition is stored in the Catalog
• TFP software can access only specific DBs. The definitions are coded in each program
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Database Catalog for the University DB
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• Insulation between Programs and Data
– Program-data independence
• Structure of data files is stored in DBMS catalog separately from access programs
• Vs. TFP: Any change to the structure should be reflected in the corresponding programs
– Program-operation independence
• In OODBMS & ORDBMS, users can define operations on data as part of DB definitions
• An operation (or functions) is specified in two parts
– Interface (or signature): includes Operation name
– Data type of its arguments (or parameters)
• Implementation of the operation is specified separately and can be changed without
affecting the interface
– i.e. User application programs can oregardless of how the operations are implementedperate on
data by invoking these operations through their names and arguments,
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• Data abstraction
– Allows program-data independence & program-operation independence
– DBMS provides users with a Conceptual data representation
• i.e Does not include details of how data is stored or how operations are implemented
• Internal implementation of a file may be defined by its
– Record length – no. of characters in each record (in bytes)
– Each data item may be specified by its starting byte within a record and its length (in bytes)
– Data model
• Type of data abstraction used to provide conceptual representation
Internal Storage format for a STUDENT Record based on DB Catalog
Abstract
Operation?
E.g. Calculate_GPA
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• Support of Multiple Views of the Data
– View
• Subset of the database
• Contains virtual data derived from the DB files but is not explicitly stored
– Multiuser DBMS
• Allow multiple users to access the database at the same time. This is essential if data for
multiple applications is to be integrated and maintained in a single database.
• Users have a variety of distinct applications
• Must provide facilities for defining multiple views
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Two views derived from the database
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• Sharing of Data & Multiuser Transaction Processing (1/3)
– Multiuser DBMS?
– Concurrency control software
• Ensure that several users trying to update the same data do so in a controlled manner so
that the result of the updates is correct
• Multiuser DBMS ensures that concurrent transactions operate correctly and efficiently
– Online transaction Processing (OLTP) application
• E.g. Several reservation agents try to assign a seat on an airline flight
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– Transaction
• Central to many database applications
• Executing program or process that includes one or more database
• ACID properties of Transaction
– Atomicity property
– Consistency property
– Isolation property
– Durability property
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– Atomicity property
• All changes to data are performed as if they are a single
operation. i.e. Perform all or none of the changes.
– Consistency property
• Data is in a consistent state when a transaction starts and
when it ends.
– Isolation property
• The intermediate state of a transaction is invisible to other
transactions. As a result, transactions that run concurrently
appear to be serialized.
– Durability property
• After a transaction completes, changes to data persist and
are not undone, even in the event of a system failure.
During fund transfer from one account to another,
the atomicity property ensures that, if a debit is
made successfully from one account, the
corresponding credit is made to the other account.
the consistency property ensures that the total value
of funds in both the accounts is the same at the start
and end of each transaction.
the isolation property ensures that another
transaction sees the transferred funds in one
account or the other, but not in both, nor in neither.
the durability property ensures that the changes
made to each account will not be reversed.
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Actors on the Scene (1/5)
• Database administrators (DBA)
– Authorize access to the database
– Coordinate & Monitor DB usage
– Acquire resources (software and hardware)
– Accountable for problems (such as security breaches and poor system response time)
– Note:
• In large organizations, the DBA is assisted by a staff that carries out these functions
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• Database designers
– Identify the data to be stored
– Choose appropriate structures to represent and store this data
– Communicate with all prospective DB users to understand their requirements & create
a design that meets these requirements
– Develop DB views that meet the data and processing requirements of user groups.
Each view is then analyzed and integrated with the views of other user groups
– Note:
• The designers are on the staff of the DBA and may be assigned other staff responsibilities
after the database design is completed.
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• End users (1/2)
– People whose jobs require DB access (querying, updating, and generating reports)
– Types
• Casual end users
– Occasional access to different information
– Use sophisticated query language to specify their requests
– Typically middle/high-level managers or other occasional browsers
• Naive or parametric end users
– Make up a sizable portion of DB end users who constantly query and update the DB
– Use standard types of queries and updates called canned transactions (transactions that were
carefully programmed and tested)
– E.g. Bank Tellers, Reservation agents
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• End users (2/2)
– Types (contd.)
• Sophisticated end users
– Thoroughly familiarize themselves with the facilities of the DBMS
– Implement own applications to meet their complex requirements
– E.g. Engineers, scientists, business analysts
• Standalone users
– Maintain personal DBs by using ready-made program packages that provide easy-to-use menu-
based or graphics-based interfaces
Are all proficient
to use all facilities
of the DBMS?
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• Software Developers or Engineers
– System analysts
• Determine requirements of end users (especially for naive or parametric users) and
develop specifications
– Application programmers
• Implement the specifications as programs, test, debug, document & maintain canned
transactions
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Workers behind the Scene (1/2)
• DBMS system designers and implementers
– Design and implement the DBMS modules and interfaces as a software package
• E.g. Implementing catalog, query language processing, interface processing, accessing and
buffering data, controlling concurrency, and handling data recovery and security
• Interface with System Software (OS, Compilers, etc.) for programming languages
• Tool developers
– Design and implement tools
• Tools are optional packages that are often purchased separately
– Include packages for database design, performance monitoring, natural language or graphical
interfaces, prototyping, simulation, and test data generation
• Note:
– In many cases, independent software vendors develop and market these tools
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Workers behind the Scene (2/2)
• Operators and maintenance personnel
– Responsible for running and maintenance of hardware and software environment for
database system
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Advantages of Using the DBMS Approach (1/9)
• Controlled redundancy
– How is it with TFP?
• Disadvantages
– Duplication of effort
– Wastage of storage space
– Inconsistency
– Data normalization
– Denormalization
• Combine data from multiple tables into single table that can be queried faster (Increased
performance)
Which one is
Consistent?
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• Restrict unauthorized access
– Access type should be controlled
• i.e. Few can retrieve, Few can retrieve & update
– Security and authorization subsystem
• DBA create accounts and specify account restrictions
• DBMS auto enforces these restrictions
– Privileged software
• Security and authorization subsystem used by DBA’s staff
• Canned transactions used by Parametric users
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• Provide persistent storage for program objects & data structures
– Data values & structures can be stored in files before being discarded – Retrieved &
formatted to program’s requirements
– Feature of OODBMS (compatible with C++, Java, etc.)
• Vs. traditional DBMS: Impedance mismatch problem (incompatible with programming
languages)
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• Provide storage structures & search techniques for efficient query processing
– DBMS provides specialized data structures that speed-up disk search
• Index: Auxiliary File based on tree or hash data structures & are suitably modified
– Choice of indices is part of physical DB design & tuning (one of DBA staff’s responsibility)
– Buffering or caching module
• DBMS performs its own data buffering (though OS is responsible)
• DB is stored in disks. Buffering stores a part of DB in main memory to process DB records
needed by a particular query
– Query processing & Optimization module
• Responsible for choosing an efficient query execution plan for each query based on the
existing storage structures
• Provide Backup and Recovery
– Backup & Recovery Subsystem
• Responsible for recovery from hardware/software failures
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• Provide multiuser Interfaces
– Example
• Query languages for casual users
• Forms and command codes for parametric users
• Programming language interfaces for application programmers
• Menu-driven & Natural language interfaces for standalone users
– Note: Forms-style & menu-driven interfaces are commonly known as GUIs
• Represent complex relationships among data
– Numerous varieties of data that are interrelated in many ways
• Example: Record for ‘Brown’ in STUDENT file is related to 4 records in GRADE_REPORT file
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• Enforce Integrity constraints for data (1/2)
– DBMS should define & enforce constraints
– Responsibility of DB designers to identify integrity constraints during DB design
– Derived from the meaning or semantics of data & of mini-world it represents
– Examples
• Specify data type for each data item
– Example: Value of Name must be a string of no more than 30 alphabetic characters
• Relate record in one file to records in other files (Referential integrity constraint)
– Example: Every section record must be related to a course record
• Specify uniqueness on data item values (Key or uniqueness constraint)
– Example: Every course record must have a unique value for Course_number
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• Enforce integrity constraints for data (2/2)
– Enforcement
• Specified to DBMS & auto enforced
• Checked at time of data entry or by update programs (Business rules)
• A data item may be entered erroneously & still satisfy specified integrity constraints. Such
data entry errors can only be discovered manually and corrected later by DB updation
– Example: If a student receives a grade of ‘A’ but a grade of ‘C’ is entered, the DBMS cannot
discover this error automatically because ‘C’ is a valid value for the Grade data type. A grade of
‘Z’ would be rejected automatically by DBMS because ‘Z’ is not a valid value for Grade data type
– Inherent rules of the data model describe the validity
• Example: In ER model, a relationship must involve at least two entities
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• Permitting inferencing and actions using rules
– Deductive DB systems
• Define deduction rules that inference new information from the stored DB facts
• Example
– Application have complex rules to find students on probation. These can be specified declaratively as
rules, which when compiled & maintained by DBMS can determine all students on probation
• Vs. traditional DBMS: Explicit procedural program code is required to support such applications
– Trigger
• Rule activated by updates to the table, which results in performing some additional operations
to some other tables, sending messages, and so on.
– Stored procedures
• More involved procedures which are part of DB definition to enforce rules. Invoked when
certain conditions are met.
– Active DBMS
• Provide active or ECA (Event-Condition-Action) rules that can automatically initiate actions
when certain events and conditions occur
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Rule Change!
(Change code or rules) –
Which one is easy?
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• Additional implications of using the database approach
– Potential for enforcing standards
• Vs. User group having control of its own files
– Reduced application development time
• 0.17 to 0.25 of time taken for traditional file system
– Flexibility
• Change in DB structure without affecting data & existing application programs
– Availability of up-to-date information
• Concurrency control & recovery subsystems
– Economies of scale
• Reduction in overall cost of operation & management
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A Brief History of Database Applications (1/5)
• Early database applications using hierarchical and network systems
– Large numbers of records of similar structure, many record types & interrelationships
– Implemented on large expensive Mainframe computers (mid 1960s to 1980s)
– Paradigms
• Hierarchical systems, Network model-based systems, Inverted File system
– Cons
• Laborious to reorganize DB when application’s requirements changed
• Provided only programming language (PL) interfaces
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• Providing data abstraction and application flexibility with relational databases
– Separates physical storage of data from its conceptual representation
– Provides a mathematical foundation for data representation and querying
– High level Query language instead of PL interface (late 1970s
• Flexibility to quick creation of new queries and DB reorganization
– Exist in almost all types of computers
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• Object-oriented applications and the need for more complex databases
– OO programming languages (1980s) & later OODB
– General data structures, store complex structured objects, incorporated OO concepts
– Used only in specialized applications
• E.g. Engineering design, multimedia publishing, and manufacturing systems
• Interchanging data on the Web for e-commerce using XML
– e-commerce applications (1980s) uses DBMS
– Web publishing language to create documents (like HTML)
• Documents are linked through hyperlinks
– Extended markup language (XML) - Primary standard for interchanging data among
various types of databases and Web pages
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• Extending database capabilities for new applications
– Unsuitability of the RDBs
• Requirement of new data types, more complex data structures,, new operations & query
language constructs required to manipulate new data types, new storage & indexing
structures
– Extensions to better support specialized requirements for applications
• Scientific applications, Storage and retrieval of images/videos, Data mining applications,
Spatial applications, Time series applications
– Web-enabled applications & DB backends (one/more DBs from different vendors &
different models)
• Enterprise resource planning (ERP)
• Customer relationship management (CRM)
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• Databases versus information retrieval
– Information retrieval (IR)
• Deals with books, manuscripts, and various forms of library-based articles
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When Not to Use a DBMS
• DBMS involves overhead costs (vs. TFP)
– High initial investment
– Security, Concurrency control, recovery & integrity functions
• More desirable to use regular files for
– Simple, well-defined DB applications not expected to change at all
– Stringent, real-time requirements that may not be met because of DBMS overhead
– Embedded systems with limited storage capacity
– No multiple-user access to data
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