Provide an executive overview that addresses the following: Discuss optimization

Question

Provide an executive overview that addresses the following: Discuss optimization techniques specific to data warehousing and data mining.

1.Summarize how database systems support enterprise and web-based applications

2.Summarize the difference between on-line transaction processing (OLTP) and online analytic processing (OLAP), and their relationship among business intelligence, data warehousing and data mining

3.Demonstrate the basic mechanisms for accessing relational databases from various types of application development environments

Explanation / Answer

By enterprise-wise, we are referring to software that provides centralized data storage and allows multiple users to access the system simultaneously. This type of software is typically more expensive and more complex to implement. It requires adequate server hardware, experienced IT personnel to configure and support the server(s), appropriate licensing for the underlying database (e.g., ORACLE or SQL Server), a secure and reliable connection to the server for each user, ongoing database maintenance and backups, and so on.

An enterprise-wide system is likely to be appropriate if you are dealing with process-oriented analyses that require input and review by multiple people, such as FMEA or FRACAS. In these cases, the organization will benefit from centralized data storage and the ability for multiple users to log in to the system from various locations and query or update the shared information. ReliaSoft's Xfmea Enterprise and XFRACAS products are examples of enterprise-wide software designed to support the FMEA and FRACAS needs of the entire organization, while providing consistency, a feedback loop for corrective actions, a searchable "knowledge base" of known issues, etc.

Another powerful application for an enterprise-wide system would be an automated data analysis and presentation system, such as ReliaSoft's Dashboard. This type of system is designed to collect data from a variety of sources (e.g. shipments, warranty claims, failure analyses, etc.), automatically analyze the data and present the analysis results throughout the organization. This approach is appropriate for analyses that can be performed without input from an experienced analyst (such as line charts showing trends over time or bar charts of issues ranked by quantity) and usually requires custom development to establish the data flow, analysis and presentation mechanisms that are appropriate for an organizations particular processes.

However, if you are working with individual statistical data analyses (such as fitting a distribution to life data or simulating the operation of a complex system over time), an enterprise-wide system is not required, even if you have many users across the enterprise. In this case, the analysis is typically (and appropriately) performed by one analyst at a time and usually requires the computing power and usability that a standalone software product such as ReliaSoft's Weibull++ or BlockSim can provide. Under this scenario, employing an enterprise-wide Web-based system would be both prohibitive and unnecessary.

Web-based or Client-Server?
With systems that are deployed via a Web browser, there is little or no software that needs to be installed or updated on each user's computer. This characteristic is understandably attractive to many IT departments! If a Web-based system can deliver the desired functionality, usability and performance then it may be preferred over a client-server approach, which requires software to be installed and updated for each user.

The technology available for developing Web-based systems has been improving and continues to improve all the time. However, for many types of tasks, users continue to expect a higher level of usability and performance than can currently be achieved in a Web-based interface. In those cases, your organization will need to carefully weigh the advantages and disadvantages of the relative convenience of the Web-based system versus the superior performance and usability of the client-server option%u2026 or consider a terminal server approach,

2)OLTP: helps and manages application based on transactions involving high volume of data

OLTP is based on client-server architecture and supports transactions across n/w,s

OLAP:business data analysis and complex calculations on low volumes of data are performed by olap.

diff b/w OLTP and OLAP

                                OLTP                                                                   OLAP

1) characteristics    processing operational                                         informational processing

2)orientation     customer-oriented transaction and query processing      market-oriented data analysis

3)users           clerks,clients,DBA                                                        knowledge worker(eg manager)

4)DB design   ER based,application oriented                                star/snowflake,subj oriented

5)data                current/guaranted-up-to-date                                        historical/accuracy maintained over time

6)view                   detailed/flat relational                                                 summerized/multidimentional

7)unit of work      short,simple transaction                                              complex query

8)access               read/write                                                                read only

9)focus                data in                                                                            inf out

10)DB size        100MB to GB                                                               100GB to TB

3) Basic mechanisms for accessing relational databases from various types of application development       environments:

access control

authorization

confidentiality

integrity

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