What are the principal tools and technologies for accessing information from databases to improve business performance and decision making?
a. define a data warehouse, explaining how it works and how it benefits organizations.
b. define business intelligence and explain how it is related to database technology.
c. describe the capabilities of online analytical processing (olap).
d. define data mining, describing how it differs from olap and the types of information it provides.
e. explain how text mining and web mining differ from conventional data mining.
f. describe how users can access information from a company’s internal databases through the web

There are many principal tools and technologies for accessing information from databases that help make business performance and decision making better.

Data warehouse:

A data warehouse is a big database that houses all the data that is needed to make decisions throughout the whole organization.

How a data warehouse works:

The data warehouse first takes all the data from the company's operational systems and combines it with the data that is pulled from outside sources. This collection of data is reformatted into one database that is used for management reporting analysis.

How it benefits organizations:

A data warehouse benefits organizations by making data available for anyone to access as needed. This keeps the data information secure and can prevent redundancies or inconsistencies. It ultimately helps management make decisions that will help the company move forward.

Business intelligence:

Business intelligence is the term used to describe the data and software tools for organizing, analyzing, and providing access to data in order to help a company make better decisions. The tools give user the opportunity to analyze data in hopes of seeing new patterns and relationship that are useful for better decision making.

How it relates to database technology:

The tools for business intelligence consist of software that performs database querying and reporting, multidimensional data analysis, and data mining. The data can be analyzed by the company once it is made available in the data warehouse. Online analytical processing (OLAP): OLAP allows end users to view data in many ways through the support of multidimensional data analysis. Different information on a certain piece of data would be represented in a different dimension. Comment

OLAP capabilities:

A multidimensional model can be designed to represent products, regions, actual sales, and projected sales. A matrix of actual sales is put on top of a matrix of projected sales in order to form a cube consisting of six faces. Rotating the cube 90 degrees one way will show the product versus actual and projected sales. Rotating the cube 90 degrees again will show the region versus actual and projected sales. Rotating the cube 180 degrees from the original view will show the projected sales and product versus region.

Data mining:

Data mining is defined as a process that provides a business with insights into company data through the searching of patterns and relationships that will help better foresee future behavior. Data mining helps make better decisions and predicts the effects that may result from those said decisions.

How it is different from OLAP:

OLAP requires the user to have a good idea about the information for which they are looking. Data mining doesn't require the need to have a good idea about the information for which they are looking. Also, OLAP doesn't have the capabilities to search for hidden patterns and relationships in large databases.

The type of information that data mining provides:

Associations:

Occurrences that are connected to a single event. Patterns in sales can be analyzed to provide managers with better decision making.

Sequences:

Occurrences when events are connected over time.

Classifications:

The recognition of patterns and relationships that define the group to which an item belongs. Classification helps discover the characteristics of a customer so that managers will be able to come up with ways to keep those customers from leaving.

Clusters:

Similar to how classifications operate except for the fact that groups haven't been defined. Clusters make it possible to discover different groupings in the company data.

Forecasts:

Forecasts make predictions by using existing values to predict what other values will be. Forecasting provides a way for the company to predict the values of their sales figures.

Text mining:

Tools for analyzing data that work by obtaining important elements from unorganized data sets, finding patterns, and summarizes the data so that a company can make better decisions for the business.

Web mining:

Web mining is defined as the analysis of patterns and relationships from the World Wide Web.  

How they differ from conventional data mining:

Conventional data mining finds patterns and relationships in information that is structured.  

The way that users can access information from a company's internal databases through the Web:

A user can access information from a company's internal databases through the Web is by using Web browser software on their PC. The requests are done by using HTML commands to communicate with the Web server. The Web server passes the requests for data to software that translates HTML commands into structured query language (SQL) so that they can be processed by the DBMS working with the database. The DBMS receives the SQL requests and provides the needed data.