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Database Life Cycle
- 1. A & S Database Consulting Inc. Persistence Data Solutions A & S database Consulting Inc. 1823 kern loop Fremont California 94539 Phone : (510)657-9475 info@ ansdbc .com @ & $ DBC
- 2. © 2003-2004 A & S Database Consulting Inc. e-commerce e-business e-world Database Business Consulting
- 5. Analysis Business Data Process Rules Objects Pattern Statistics six-sigma Meta © 2003-2004 A & S Database Consulting Inc. Analysis
- 6. © 2003-2004 A & S Database Consulting Inc. Entity Relationship Diagrams (ERDs) Unified Modeling Language (UML) Modeling & Design
- 7. © 2003-2004 A & S Database Consulting Inc. The data model (a blueprint for a persistent data storage design) Implementation
- 8. © 2003-2004 A & S Database Consulting Inc. Viewing
- 11. © 2003-2004 A & S Database Consulting Inc. How do databases help your end clients?
- 13. © 2003-2004 A & S Database Consulting Inc. Harshendu Desai , Database Business Consultant A & S Database Consulting Inc. 1823 kern loop Fremont California 94539 Phone : (510)657-9475 info@ ansdbc .com Contact Us Today!
Hinweis der Redaktion
- The three most powerful e’s of the Internet (e-commerce, e-business and e-world) cannot thrive or progress without access to historical, current or future information related to the business enterprise. Our database consulting services are based entirely on using sound and structured processes to gather, analyze, understand and act upon business-critical information.
- If you are not familiar with how databases work or are developed we will show you the basics to the Database Development LifeCycle How databases can help your end clients when implementing an internet solution The services that ANSDB can offer you and how to contact us for more information and a free consultation
- The separation of any data entity into its component elements which is called Data Analysis (Analysis). This is followed by usage of common data modeling techniques to present the single or multiple subject areas of data in detail (Modeling & Design). The data storage implementation in any relational database follows the blueprint established in the data model (Implementation). The database implementation frequently provides different ways to present the stored information to a target audience, enabling them to make business decisions (Viewing). Additionally, data and database tune-ups are required to keep pace with continuous changes that occur in the business (Maintenance), leading back to the Data Analysis phase at the beginning of the life cycle again.
- The data in a database persists for varying periods of time. The data can be transient in nature, or it can persist for longer periods. It typically originates as input data which is initially entered into the database and then becomes persistent data. It can also be output data, which may be displayed in web-based formats or on printed reports. This output data may be derived from the persistent data, rather than being part of the database itself. Analysis takes two forms: a) Business Analysis -- Includes business process analysis, planning, requirements gathering, conducting surveys, user interaction, and presentation using standard templates and the Rational Rose Unified Modeling Language Tool. b) Data Analysis -- Includes data patterning using graphical methods , statistical data analysis, data mining, multivariate data analysis, the six-sigma and meta-analysis methods.
- Storing persistent data in a database is somewhat of an art. The database must be designed in such a way as to be flexible enough to accommodate changing business needs. Designing data storage involves defining the relationship between different data subject areas and their attributes. The organization of this persistent data is called the data model which is a blueprint for database implementation. The data model can be represented by using Entity Relationship Diagrams (ERDs) or Unified Modeling Language (UML). The data model can be developed based on reverse or forward engineering methods. Forward engineering is derived from business and requirements analysis. There are many tools available to create data models. Popular examples include ERWIN Data Modeler, Sybase Power Designer, Oracle Designer, Smart Draw, Visio and Rational Rose.
- The data model (a blueprint for a persistent data storage design) determines whether data will be stored in an operational or an informational way. Business enterprises may have various on-line transaction processing (OLTP) systems which create operational data like shipments, orders, financial data, etc by means of transactions that insert, delete or select data from databases. The informational approach to data storage organizes data around subject areas which are summaries of the transactional data. This leads business enterprises to develop on-line analytical processing (OLAP) systems.
- As soon as a database is ready, the end-user will expect to see information in a tailored way. The understandability of data is very important in accessing and extracting from databases. Persistent data can be viewed with various approaches :
- Databases are changing constantly to stay current with business needs. This may result in degradation of performance unless maintenance is performed. Periodic maintenance is required for any size of database. The following basic steps are included in a maintenance plan to extend the life of databases and to get the best performance from databases: