Database development life cycle unit 2 part 1Ram Paliwal
The document discusses the database development life cycle (DDLC), which is a six-phase process for designing, implementing, and maintaining a database system to meet an organization's information needs. The six phases are: 1) database initial study, 2) database design, 3) implementation and loading, 4) testing and evaluation, 5) operation, and 6) maintenance and evolution. Each phase is described in detail, from analyzing requirements in the initial study to ongoing maintenance activities once the database is operational.
This document provides an overview of data modeling concepts. It discusses the importance of data modeling, the basic building blocks of data models including entities, attributes, and relationships. It also covers different types of data models such as conceptual, logical, and physical models. The document discusses relational and non-relational data models as well as emerging models like object-oriented, XML, and big data models. Business rules and their role in database design are also summarized.
The document discusses database design and the design process. It explains that database design involves determining the logical structure of tables and relationships between data elements. The design process consists of steps like determining relationships between data, dividing information into tables, specifying primary keys, and applying normalization rules. The document also covers entity-relationship diagrams and designing inputs and outputs, including input controls and designing report formats.
This document defines database and DBMS, describes their advantages over file-based systems like data independence and integrity. It explains database system components and architecture including physical and logical data models. Key aspects covered are data definition language to create schemas, data manipulation language to query data, and transaction management to handle concurrent access and recovery. It also provides a brief history of database systems and discusses database users and the critical role of database administrators.
The PPT would provide the Database Normalization is to restructure the logical data model of a database to:
Eliminate Redundancy
Organize Data Efficiently
Reduce the potential for Data Anomalies.
Integrity constraints are rules used to maintain data quality and ensure accuracy in a relational database. The main types of integrity constraints are domain constraints, which define valid value sets for attributes; NOT NULL constraints, which enforce non-null values; UNIQUE constraints, which require unique values; and CHECK constraints, which specify value ranges. Referential integrity links data between tables through foreign keys, preventing orphaned records. Integrity constraints are enforced by the database to guard against accidental data damage.
The document provides an introduction to databases and SQL. It defines what a database is as a collection of related data containing information relevant to an enterprise. It then discusses the properties of databases, what a database management system (DBMS) is, the typical functionality of a DBMS including defining, constructing, manipulating databases, and providing security. It also summarizes the components of a database system including fields, records, queries, and reports. The document then introduces SQL and its uses for data manipulation, definition, and administration. It provides examples of SQL statements for creating tables, inserting, querying, updating, and deleting data.
Data & Information, Drawbacks of File system, What is Database Management Systems, What is the need of DBMS, Examples of DBMS, Database Types, Applications of DBMS, Advantage of DBMS over file system, Disadvantages of DBMS, DBMS vs. File System
Database development life cycle unit 2 part 1Ram Paliwal
The document discusses the database development life cycle (DDLC), which is a six-phase process for designing, implementing, and maintaining a database system to meet an organization's information needs. The six phases are: 1) database initial study, 2) database design, 3) implementation and loading, 4) testing and evaluation, 5) operation, and 6) maintenance and evolution. Each phase is described in detail, from analyzing requirements in the initial study to ongoing maintenance activities once the database is operational.
This document provides an overview of data modeling concepts. It discusses the importance of data modeling, the basic building blocks of data models including entities, attributes, and relationships. It also covers different types of data models such as conceptual, logical, and physical models. The document discusses relational and non-relational data models as well as emerging models like object-oriented, XML, and big data models. Business rules and their role in database design are also summarized.
The document discusses database design and the design process. It explains that database design involves determining the logical structure of tables and relationships between data elements. The design process consists of steps like determining relationships between data, dividing information into tables, specifying primary keys, and applying normalization rules. The document also covers entity-relationship diagrams and designing inputs and outputs, including input controls and designing report formats.
This document defines database and DBMS, describes their advantages over file-based systems like data independence and integrity. It explains database system components and architecture including physical and logical data models. Key aspects covered are data definition language to create schemas, data manipulation language to query data, and transaction management to handle concurrent access and recovery. It also provides a brief history of database systems and discusses database users and the critical role of database administrators.
The PPT would provide the Database Normalization is to restructure the logical data model of a database to:
Eliminate Redundancy
Organize Data Efficiently
Reduce the potential for Data Anomalies.
Integrity constraints are rules used to maintain data quality and ensure accuracy in a relational database. The main types of integrity constraints are domain constraints, which define valid value sets for attributes; NOT NULL constraints, which enforce non-null values; UNIQUE constraints, which require unique values; and CHECK constraints, which specify value ranges. Referential integrity links data between tables through foreign keys, preventing orphaned records. Integrity constraints are enforced by the database to guard against accidental data damage.
The document provides an introduction to databases and SQL. It defines what a database is as a collection of related data containing information relevant to an enterprise. It then discusses the properties of databases, what a database management system (DBMS) is, the typical functionality of a DBMS including defining, constructing, manipulating databases, and providing security. It also summarizes the components of a database system including fields, records, queries, and reports. The document then introduces SQL and its uses for data manipulation, definition, and administration. It provides examples of SQL statements for creating tables, inserting, querying, updating, and deleting data.
Data & Information, Drawbacks of File system, What is Database Management Systems, What is the need of DBMS, Examples of DBMS, Database Types, Applications of DBMS, Advantage of DBMS over file system, Disadvantages of DBMS, DBMS vs. File System
This document provides an overview of data modeling, including definitions of key concepts like data models and data modeling. It describes the evolution of popular data models from hierarchical to network to relational to entity-relationship to object-oriented models. For each model, it outlines the basic concepts, advantages, and disadvantages. The document emphasizes that newer data models aimed to address shortcomings of previous approaches and capture real-world data and relationships.
This document provides an overview of databases and database management systems (DBMS). It discusses how databases evolved from file systems to address flaws in data management. It describes what a DBMS is and its functions in managing the database structure and controlling data access. The document also summarizes different database models including hierarchical, network, relational, entity-relationship, and object-oriented models. It highlights advantages and disadvantages of each model.
Dbms architecture
Three level architecture is also called ANSI/SPARC architecture or three schema architecture
This framework is used for describing the structure of specific database systems (small systems may not support all aspects of the architecture)
In this architecture the database schemas can be defined at three levels explained in next slide
The document discusses three levels of data abstraction - view level, logical level, and physical level. It also discusses three schema architecture - external schema, conceptual schema, and internal schema. The levels and schemas describe how data is represented and accessed at different levels of abstraction, hiding low-level implementation details from users.
The document discusses data modeling, which involves creating a conceptual model of the data required for an information system. There are three types of data models - conceptual, logical, and physical. A conceptual data model describes what the system contains, a logical model describes how the system will be implemented regardless of the database, and a physical model describes the implementation using a specific database. Common elements of a data model include entities, attributes, and relationships. Data modeling is used to standardize and communicate an organization's data requirements and establish business rules.
A database management system (DBMS) is a collection of programs that enables users to create and maintain databases and control all access to them. The primary goal of a DBMS is to provide an environment that is both convenient and efficient for users to retrieve and store information.
Normalisation is a process that structures data in a relational database to minimize duplication and redundancy while preserving information. It aims to ensure data is structured efficiently and consistently through multiple forms. The stages of normalization include first normal form (1NF), second normal form (2NF), third normal form (3NF), Boyce-Codd normal form (BCNF), fourth normal form (4NF) and fifth normal form (5NF). Higher normal forms eliminate more types of dependencies to optimize the database structure.
The document provides an overview of the role and responsibilities of a database administrator (DBA). It discusses that a DBA supervises databases and database management systems to ensure availability. Key responsibilities include database security, monitoring, backup/recovery, and performance tuning. DBAs must have both technical skills and knowledge of database platforms. While important, the DBA role is challenging as it involves being available to resolve various technical issues at any time from different stakeholders. The document also provides salary data for DBA roles from an external source.
An object database is a database management system in which information is represented in the form of objects as used in object-oriented programming. Object databases are different from relational databases which are table-oriented. Object-relational databases are a hybrid of both approaches
The document discusses different database models including hierarchical, network, relational, entity-relationship, object-oriented, object-relational, and semi-structured models. It provides details on the characteristics, structures, advantages and disadvantages of each model. It also includes examples and diagrams to illustrate concepts like hierarchical structure, network structure, relational schema, entity relationship diagrams, object oriented diagrams, and XML schema. The document appears to be teaching materials for a database management course that provides an overview of various database models.
This document discusses Relational Database Management Systems (RDBMS). It provides an overview of early database systems like hierarchical and network models. It then describes the key concepts of RDBMS including relations, attributes, and using tables, rows, and columns. RDBMS uses Structured Query Language (SQL) and has advantages over early systems by allowing data to be spread across multiple tables and accessed simultaneously by users.
This document provides an introduction to databases. It defines what a database is, the steps to create one, and benefits such as fast querying and flexibility. It describes database models like hierarchical, network, entity-relationship, and relational. Key database concepts are explained, including entities, attributes, primary keys, and foreign keys. Finally, it outlines database management system components, common users, and introduces Microsoft Access.
A data model is a set of concepts that define the structure of data in a database. The three main types of data models are the hierarchical model, network model, and relational model. The hierarchical model uses a tree structure with parent-child relationships, while the network model allows many-to-many relationships but is more complex. The relational model - which underlies most modern databases - uses tables with rows and columns to represent data, and relationships are represented by values in columns.
SQL - Structured query language introductionSmriti Jain
SQL is a language used to define, manipulate, and control relational databases. It has four main components: DDL for defining schemas; DML for manipulating data within schemas; DCL for controlling access privileges; and DQL for querying data. Some key SQL concepts covered include data definition using CREATE, ALTER, DROP statements; data manipulation using SELECT, INSERT, UPDATE, DELETE; and joining data across tables using conditions. Advanced topics include views, aggregation, subqueries, and modifying databases.
A database administrator is responsible for installing, configuring, upgrading, administering, monitoring and maintaining databases. Key responsibilities include database design, performance and capacity issues, data replication, and table maintenance. DBAs ensure proper data organization and management through their skills in SQL, database design, and knowledge of database management systems and operating systems. There are several types of DBAs based on their specific roles like system DBA, database architect, and data warehouse administrator.
This document provides an overview of database concepts and terminology. It discusses different types of databases based on number of users (single, multi, workgroup, enterprise), number of computers used (centralized, distributed), and how up-to-date the data is (production, data warehouse). It also covers database categorizations, the relational model, entity types and occurrences, relationship types and occurrences, attributes, keys, and E.F. Codd's 12 rules for relational databases.
The document discusses database concepts including:
- What a database is and its components like data, hardware, software, and users.
- Database management systems (DBMS) that enable users to define, create and maintain databases.
- Data models like hierarchical, network, and relational models. Relational databases using SQL are now most common.
- Database design including logical design, physical implementation, and application development.
- Key concepts like data abstraction, instances and schemas, normalization, and integrity rules.
The document provides an overview of database management systems (DBMS). It defines DBMS as software that creates, organizes, and manages databases. It discusses key DBMS concepts like data models, schemas, instances, and database languages. Components of a database system including users, software, hardware, and data are described. Popular DBMS examples like Oracle, SQL Server, and MS Access are listed along with common applications of DBMS in various industries.
Structure of this Chapter
In Section 11.1Section 11.1 we discuss when a database developer might use
fact-finding techniques. (Throughout this book we use the term
“database developer” to refer to a person or group of people
responsible for the analysis, design, and implementation of a
database system.) In Section 11.2Section 11.2 we illustrate the types of facts that
should be collected and the documentation that should be produced
at each stage of the database system development lifecycle. In
Section 11.3Section 11.3 we describe the five most commonly used fact-finding
techniques and identify the advantages and disadvantages of each. In
Section 11.4Section 11.4 we demonstrate how fact-finding techniques can be
used to develop a database system for a case study called
DreamHome, a property management company. We begin this section
by providing an overview of the DreamHome case study. We then
examine the first three stages of the database system development
lifecycle, namely database planning, system definition, and
requirements collection and analysis. For each stage we demonstrate
327
328of each. We finally demonstrate how some of these techniques may be
used during the earlier stages of the database system development
lifecycle using a property management company called DreamHome.
The DreamHome case study is used throughout this book.
epub://rxsygq01kgnjqgui7xpe.1.vbk/OPS/loc_020.xhtml#eid29635
epub://rxsygq01kgnjqgui7xpe.1.vbk/OPS/loc_020.xhtml#eid29644
epub://rxsygq01kgnjqgui7xpe.1.vbk/OPS/loc_020.xhtml#eid29751
epub://rxsygq01kgnjqgui7xpe.1.vbk/OPS/loc_020.xhtml#eid30021
the process of collecting data using fact-finding techniques and
describe the documentation produced.
11.1 When Are Fact-Finding Techniques Used?
There are many occasions for fact-finding during the database system
development life cycle. However, fact-finding is particularly crucial to
the early stages of the lifecycle, including the database planning,
system definition, and requirements collection and analysis stages. It
is during these early stages that the database developer captures the
essential facts necessary to build the required database. Fact-finding is
also used during database design and the later stages of the lifecycle,
but to a lesser extent. For example, during physical database design,
fact-finding becomes technical as the database developer attempts to
learn more about the DBMS selected for the database system. Also,
during the final stage, operational maintenance, fact-finding is used to
determine whether a system requires tuning to improve performance
or further development to include new requirements.
Note that it is important to have a rough estimate of how much time
and effort is to be spent on fact-finding for a database project. As we
mentioned in Chapter 10Chapter 10, too much study too soon leads to paralysis
by analysis. However, too little thought can result in an unnecessary
waste of both time and.
This document discusses database management systems and the database development lifecycle. It defines DBMS as software that manages databases and provides functions like data definition, retrieval, updating and administration. It describes the characteristics of data in databases and advantages like redundancy control and data sharing. The document outlines the planning, analysis, design, implementation and maintenance phases of both the software development lifecycle and database development lifecycle. It also covers different database models like hierarchical, network and relational.
This document provides an overview of data modeling, including definitions of key concepts like data models and data modeling. It describes the evolution of popular data models from hierarchical to network to relational to entity-relationship to object-oriented models. For each model, it outlines the basic concepts, advantages, and disadvantages. The document emphasizes that newer data models aimed to address shortcomings of previous approaches and capture real-world data and relationships.
This document provides an overview of databases and database management systems (DBMS). It discusses how databases evolved from file systems to address flaws in data management. It describes what a DBMS is and its functions in managing the database structure and controlling data access. The document also summarizes different database models including hierarchical, network, relational, entity-relationship, and object-oriented models. It highlights advantages and disadvantages of each model.
Dbms architecture
Three level architecture is also called ANSI/SPARC architecture or three schema architecture
This framework is used for describing the structure of specific database systems (small systems may not support all aspects of the architecture)
In this architecture the database schemas can be defined at three levels explained in next slide
The document discusses three levels of data abstraction - view level, logical level, and physical level. It also discusses three schema architecture - external schema, conceptual schema, and internal schema. The levels and schemas describe how data is represented and accessed at different levels of abstraction, hiding low-level implementation details from users.
The document discusses data modeling, which involves creating a conceptual model of the data required for an information system. There are three types of data models - conceptual, logical, and physical. A conceptual data model describes what the system contains, a logical model describes how the system will be implemented regardless of the database, and a physical model describes the implementation using a specific database. Common elements of a data model include entities, attributes, and relationships. Data modeling is used to standardize and communicate an organization's data requirements and establish business rules.
A database management system (DBMS) is a collection of programs that enables users to create and maintain databases and control all access to them. The primary goal of a DBMS is to provide an environment that is both convenient and efficient for users to retrieve and store information.
Normalisation is a process that structures data in a relational database to minimize duplication and redundancy while preserving information. It aims to ensure data is structured efficiently and consistently through multiple forms. The stages of normalization include first normal form (1NF), second normal form (2NF), third normal form (3NF), Boyce-Codd normal form (BCNF), fourth normal form (4NF) and fifth normal form (5NF). Higher normal forms eliminate more types of dependencies to optimize the database structure.
The document provides an overview of the role and responsibilities of a database administrator (DBA). It discusses that a DBA supervises databases and database management systems to ensure availability. Key responsibilities include database security, monitoring, backup/recovery, and performance tuning. DBAs must have both technical skills and knowledge of database platforms. While important, the DBA role is challenging as it involves being available to resolve various technical issues at any time from different stakeholders. The document also provides salary data for DBA roles from an external source.
An object database is a database management system in which information is represented in the form of objects as used in object-oriented programming. Object databases are different from relational databases which are table-oriented. Object-relational databases are a hybrid of both approaches
The document discusses different database models including hierarchical, network, relational, entity-relationship, object-oriented, object-relational, and semi-structured models. It provides details on the characteristics, structures, advantages and disadvantages of each model. It also includes examples and diagrams to illustrate concepts like hierarchical structure, network structure, relational schema, entity relationship diagrams, object oriented diagrams, and XML schema. The document appears to be teaching materials for a database management course that provides an overview of various database models.
This document discusses Relational Database Management Systems (RDBMS). It provides an overview of early database systems like hierarchical and network models. It then describes the key concepts of RDBMS including relations, attributes, and using tables, rows, and columns. RDBMS uses Structured Query Language (SQL) and has advantages over early systems by allowing data to be spread across multiple tables and accessed simultaneously by users.
This document provides an introduction to databases. It defines what a database is, the steps to create one, and benefits such as fast querying and flexibility. It describes database models like hierarchical, network, entity-relationship, and relational. Key database concepts are explained, including entities, attributes, primary keys, and foreign keys. Finally, it outlines database management system components, common users, and introduces Microsoft Access.
A data model is a set of concepts that define the structure of data in a database. The three main types of data models are the hierarchical model, network model, and relational model. The hierarchical model uses a tree structure with parent-child relationships, while the network model allows many-to-many relationships but is more complex. The relational model - which underlies most modern databases - uses tables with rows and columns to represent data, and relationships are represented by values in columns.
SQL - Structured query language introductionSmriti Jain
SQL is a language used to define, manipulate, and control relational databases. It has four main components: DDL for defining schemas; DML for manipulating data within schemas; DCL for controlling access privileges; and DQL for querying data. Some key SQL concepts covered include data definition using CREATE, ALTER, DROP statements; data manipulation using SELECT, INSERT, UPDATE, DELETE; and joining data across tables using conditions. Advanced topics include views, aggregation, subqueries, and modifying databases.
A database administrator is responsible for installing, configuring, upgrading, administering, monitoring and maintaining databases. Key responsibilities include database design, performance and capacity issues, data replication, and table maintenance. DBAs ensure proper data organization and management through their skills in SQL, database design, and knowledge of database management systems and operating systems. There are several types of DBAs based on their specific roles like system DBA, database architect, and data warehouse administrator.
This document provides an overview of database concepts and terminology. It discusses different types of databases based on number of users (single, multi, workgroup, enterprise), number of computers used (centralized, distributed), and how up-to-date the data is (production, data warehouse). It also covers database categorizations, the relational model, entity types and occurrences, relationship types and occurrences, attributes, keys, and E.F. Codd's 12 rules for relational databases.
The document discusses database concepts including:
- What a database is and its components like data, hardware, software, and users.
- Database management systems (DBMS) that enable users to define, create and maintain databases.
- Data models like hierarchical, network, and relational models. Relational databases using SQL are now most common.
- Database design including logical design, physical implementation, and application development.
- Key concepts like data abstraction, instances and schemas, normalization, and integrity rules.
The document provides an overview of database management systems (DBMS). It defines DBMS as software that creates, organizes, and manages databases. It discusses key DBMS concepts like data models, schemas, instances, and database languages. Components of a database system including users, software, hardware, and data are described. Popular DBMS examples like Oracle, SQL Server, and MS Access are listed along with common applications of DBMS in various industries.
Structure of this Chapter
In Section 11.1Section 11.1 we discuss when a database developer might use
fact-finding techniques. (Throughout this book we use the term
“database developer” to refer to a person or group of people
responsible for the analysis, design, and implementation of a
database system.) In Section 11.2Section 11.2 we illustrate the types of facts that
should be collected and the documentation that should be produced
at each stage of the database system development lifecycle. In
Section 11.3Section 11.3 we describe the five most commonly used fact-finding
techniques and identify the advantages and disadvantages of each. In
Section 11.4Section 11.4 we demonstrate how fact-finding techniques can be
used to develop a database system for a case study called
DreamHome, a property management company. We begin this section
by providing an overview of the DreamHome case study. We then
examine the first three stages of the database system development
lifecycle, namely database planning, system definition, and
requirements collection and analysis. For each stage we demonstrate
327
328of each. We finally demonstrate how some of these techniques may be
used during the earlier stages of the database system development
lifecycle using a property management company called DreamHome.
The DreamHome case study is used throughout this book.
epub://rxsygq01kgnjqgui7xpe.1.vbk/OPS/loc_020.xhtml#eid29635
epub://rxsygq01kgnjqgui7xpe.1.vbk/OPS/loc_020.xhtml#eid29644
epub://rxsygq01kgnjqgui7xpe.1.vbk/OPS/loc_020.xhtml#eid29751
epub://rxsygq01kgnjqgui7xpe.1.vbk/OPS/loc_020.xhtml#eid30021
the process of collecting data using fact-finding techniques and
describe the documentation produced.
11.1 When Are Fact-Finding Techniques Used?
There are many occasions for fact-finding during the database system
development life cycle. However, fact-finding is particularly crucial to
the early stages of the lifecycle, including the database planning,
system definition, and requirements collection and analysis stages. It
is during these early stages that the database developer captures the
essential facts necessary to build the required database. Fact-finding is
also used during database design and the later stages of the lifecycle,
but to a lesser extent. For example, during physical database design,
fact-finding becomes technical as the database developer attempts to
learn more about the DBMS selected for the database system. Also,
during the final stage, operational maintenance, fact-finding is used to
determine whether a system requires tuning to improve performance
or further development to include new requirements.
Note that it is important to have a rough estimate of how much time
and effort is to be spent on fact-finding for a database project. As we
mentioned in Chapter 10Chapter 10, too much study too soon leads to paralysis
by analysis. However, too little thought can result in an unnecessary
waste of both time and.
This document discusses database management systems and the database development lifecycle. It defines DBMS as software that manages databases and provides functions like data definition, retrieval, updating and administration. It describes the characteristics of data in databases and advantages like redundancy control and data sharing. The document outlines the planning, analysis, design, implementation and maintenance phases of both the software development lifecycle and database development lifecycle. It also covers different database models like hierarchical, network and relational.
The document discusses the database development life cycle (DBLC), which follows a similar process to the systems development life cycle (SDLC). The DBLC involves gathering requirements, database analysis, design, implementation, testing and evaluation, and maintenance. It describes each stage in detail, including conceptual, logical, and physical data modeling during the design stage. The goal is to systematically plan and develop a database to meet requirements while ensuring completeness, integrity, flexibility, and usability.
Database Development Process: A core aspect of software engineering is the subdivision of the development process into a series of phases, or steps, each of which focuses on one part of the development.
-This lecture about the Details explanation about the Database Development life Cycle. This lecture show about the Software development Cycle in term of DB. This lecture Explain the architecture of the Database. This lecture explain about the Three-Level ANSI-SPARC Architecture.
This document discusses various techniques used in software project management including CRUD matrices, Gantt charts, PERT charts, feasibility analysis, and cost-benefit analysis. A CRUD matrix identifies the database tables involved in create, read, update, and delete operations for different user scenarios of a website. Gantt charts show project activities and timelines while PERT charts illustrate task dependencies in a project. Feasibility analysis evaluates the technical, economic, operational, and legal viability of a project. Cost-benefit analysis compares monetary costs and benefits to determine if a project's benefits outweigh its costs. These techniques help software project managers effectively plan, schedule, and control development projects.
The document discusses the database development life cycle (DDLC). It outlines the 6 phases of the DDLC: database planning, database design, implementation and downloading, testing and evaluation, operation, and maintenance and evolution. The database design phase is described as the most important, involving conceptual, logical, and physical design activities like data modeling, normalization, and validating the data model. The goals and key activities of each phase are summarized.
This document provides information about a student details management system (SDMS) software project created by a student. It includes an introduction describing the purpose of automating a student information system. It also includes sections on the objectives, theoretical background of databases, MySQL and Python, problem definition and analysis, and system design including database and code details. The overall aim is to develop a program with a graphical user interface to allow users to view and update student information stored in a centralized database.
Traditional operational views of capacity planning is not the same as BI Capacity planning. I created this presentation to help establish a BI Infrastructure Capacity planning process.
Database integration allows data from multiple applications to be stored in a central database so it can be easily accessed and used across different applications. This involves developing a plan so that all client applications are accounted for. Integrating a database with a website allows web visitors to add, remove, and update information in the database using a web browser and often search the database. Requirements analysis determines what type of database is needed based on factors like daily data volume and amount of master file data.
This document outlines the six steps of database design: requirements analysis, conceptual design, logical design, schema refinement, physical design, and application/security design. It describes each step in detail. Requirements analysis involves understanding user needs. Conceptual design models the data using an entity-relationship diagram. Logical design maps the conceptual model to a relational schema. Schema refinement improves normalization. Physical design optimizes performance. Application/security design specifies user roles and access permissions.
The document discusses the system development life cycle (SDLC), which includes various phases for developing and maintaining systems. The key phases are: system investigation, feasibility study, system analysis, system design, coding, testing, implementation, and maintenance. The feasibility study phase evaluates the technical, operational, economic, motivational, and schedule feasibility of a proposed system. The system analysis phase involves studying user requirements and the current system. System design then specifies how the new system will meet requirements through elements like data design, user interface design, and process design. This produces specifications for the system.
Data Warehouses & Deployment By Ankita dubeyAnkita Dubey
This document contains the notes about data warehouses and life cycle for data warehouse deployment project. This can be useful for students or working professionals to gain the basic knowledge about Data warehouses.
The document discusses database design and the waterfall approach to systems development. It describes the waterfall approach as involving a series of sequential phases from strategy and planning to maintenance. Some problems with the waterfall approach are that users may not properly communicate requirements or understand their own needs, and analysts can misunderstand requirements. The document also discusses conceptual, logical, and physical phases of database design, moving from requirements to implementing database technology.
This document describes the development of an employee management system. It discusses:
1) The programming tools used - Microsoft Access for the database and C# with .NET Framework for the application. Access allows constructing relational databases while C# provides an object-oriented interface.
2) The database design, which includes 6 tables - one main employee table and 5 child tables for additional employee details like work history, time records, and contact information. The tables are related through primary and foreign keys.
3) The development process, which first analyzed user needs, designed the database structure, then constructed the graphical user interface in the application to interact with the database according to its structure.
Project PlanFor our Project Plan, we are going to develop.docxwkyra78
The document outlines a project plan to develop a new payroll system for an organization using the waterfall development methodology. It estimates the project will take 33.3 person-months to complete based on industry standards of allocating 15% of effort to planning, 20% to analysis, 35% to design, and 30% to implementation. It also discusses developing a work plan, staffing the project, and coordinating project activities to manage the system development life cycle.
Journal of Physics Conference SeriesPAPER • OPEN ACCESS.docxLaticiaGrissomzz
Journal of Physics: Conference Series
PAPER • OPEN ACCESS
The methodology of database design in
organization management systems
To cite this article: I L Chudinov et al 2017 J. Phys.: Conf. Ser. 803 012030
View the article online for updates and enhancements.
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The methodology of database design in organization
management systems
I L Chudinov, V V Osipova, Y V Bobrova
Tomsk Polytechnic University, 30, Lenina ave., Tomsk, 634050, Russia
E-mail: [email protected]
Abstract. The paper describes the unified methodology of database design for management
information systems. Designing the conceptual information model for the domain area is the
most important and labor-intensive stage in database design. Basing on the proposed integrated
approach to design, the conceptual information model, the main principles of developing the
relation databases are provided and user’s information needs are considered. According to the
methodology, the process of designing the conceptual information model includes three basic
stages, which are defined in detail. Finally, the article describes the process of performing the
results of analyzing user’s information needs and the rationale for use of classifiers.
1. Introduction
Management information systems are among the most important components of information
technologies (IT), used in a company. They are usually classified by the functions into the following
systems: Manufacturing Execution Systems (MES), Human Resource Management (HRM), Enterprise
Content Management (ECM), Customer Relationship Management (CRM), etc. [1]. Such systems are
used a special structured database and are required for reengineering of the whole enterprise
management system, while the integration makes it difficult to use them. These systems are expensive
enough and particularly devel.
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Database development life cycle
1. DATABASE DEVELOPMENT LIFE CYCLE AFRASIYAB HAIDER
DATABASE DEVELOPMENT LIFE CYCLE
Database development life cycle
A database is usually a fundamental component of the information system, especially in
business oriented systems. Thus database design is part of system development. The following
picture shows how database design is involved in the system development lifecycle.
The phases in the middle of the picture (Database Design, Database Implementation) are the
phases that you concentrate on in the Database Design course. The other phases are briefly
described. They are part of the contents of the Systems Analysis and Design courses, for
example.
There are various methods of how the different phases of information systemdesign, analysis
and implementation can be done. Here the main tasks or goals are described but no method is
introduced.
2. DATABASE DEVELOPMENT LIFE CYCLE AFRASIYAB HAIDER
DATABASE DEVELOPMENT LIFE CYCLE
Database Planning
The database planning includes the activities that allow the stages of the database system
development lifecycle to be realized as efficiently and effectively as possible. This phase must
be integrated with the overall Information System strategy of the organization.
The very first step in database planning is to define the mission statement and objectives for
the database system. That is the definition of:
- the major aims of the database system
- the purpose of the database system
- the supported tasks of the database system
- the resources of the database system
Systems Definition
In the systems definition phase, the scope and boundaries of the database application are
described. This description includes:
- links with the other information systems of the organization
- what the planned systemis going to do now and in the future
- who the users are now and in the future.
The major user views are also described. i.e. what is required of a database systemfrom the
perspectives of particular job roles or enterprise application areas.
Requirements Collection and Analysis
During the requirements collection and analysis phase, the collection and analysis of the
information about the part of the enterprise to be served by the database are completed. The
results may include eg:
- the description of the data used or generated
- the details how the data is to be used or generated
- any additional requirements for the new database system
Database Design
The database design phase is divided into three steps:
- conceptual database design
- logical database design
- physical database design
3. DATABASE DEVELOPMENT LIFE CYCLE AFRASIYAB HAIDER
DATABASE DEVELOPMENT LIFE CYCLE
In the conceptual database design phase, the model of the data to be used independent of all
physical considerations is to be constructed. The model is based on the requirements
specification of the system.
In the logical database design phase, the model of the data to be used is based on a specific
data model, but independent of a particular database management system is constructed. This
is based on the target data model for the database e.g. relational data model.
In the physical database design phase, the description of the implementation of the database
on secondary storage is created. The base relations, indexes, integrity constraints, security, etc.
are defined using the SQL language.
Database Management System Selection
This in an optional phase. When there is a need for a new database management system
(DBMS), this phase is done. DBMS means a database system like Access, SQL Server, MySQL,
Oracle.
In this phase the criteria for the new DBMS are defined. Then several products are evaluated
according to the criteria. Finally the
recommendation for the selection is decided.
ApplicationDesign
In the application design phase, the design of the user interface and the application programs
that use and process the database are defined and designed.
Protyping
The purpose of a prototype is to allow the users to use the prototype to identify the features of
the system using the computer.
There are horizontal and vertical prototypes. A horizontal prototype has many features (e.g.
user interfaces) but they are not working. A vertical prototype has very few features but they
are working. See the following picture.
Implementation
During the implementation phase, the physical realization of the database and application
designs are to be done. This is the programming phase of the systems development.
Data Conversion and Loading
This phase is needed when a new database is replacing an old system. During this phase the
existing data will be transferred into the new database.
4. DATABASE DEVELOPMENT LIFE CYCLE AFRASIYAB HAIDER
DATABASE DEVELOPMENT LIFE CYCLE
Testing
Before the new systemis going to live, it should be thoroughly tested. The goal of testing is to
find errors! The goal is not to prove the software is working well.
Operational Maintenance
The operational maintenance is the process of monitoring and maintaining the database
system.
Monitoring means that the performance of the systemis observed. If the performance of the
system falls below an acceptable level, tuning or reorganization of the database may be
required.
Maintaining and upgrading the database systemmeans that, when new requirements arise, the
new development lifecycle will be done. Source: Connolly, Begg. 2005. Database Systems. A
Practical Approach to Design, Implementation, and Management. Addison Wesley. Chapter 9.
Database Planning, Design and Administration.