ACCESSSING ORGANIZATIONAL INFORMATION - DATA WAREHOUSE

In this chapter we will continue about DATA WAREHOUSE which will further explain below:

HISTORY OF DATA WAREHOUSING

*In 1990s organization began to need more timely information about their business that traditional operational information system.

*Operational system including accounting,order entry and sales are not appropriate for business analysis for the following reasons :

• Information from other operational applications is not included.
• Operational systems are not integrated 
• Operational information is mainly current-does not include the history for better decision making
• Operational information frequently has quality issues(errors)-information need to be cleansed.
• Without information history, it is difficult to tell how and why things change over time.

DATA WAREHOUSE FUNDAMENTALS

DATA WAREHOUSE– a logical collection of information – gathered from many different operational databases – that supports business analysis activities and decision-making tasks.

~PURPOSE-to aggregate information throughout an organization into a single repository  in such a way that employees can make decision and undertake business analysis activities.

EXTRACTION,TRANSFORMATION AND LOADING(ETL) 

DATA WAREHOUSE MODEL

MULTIDIMENSIONAL ANALYSIS AND DATA MINING

Relational Database contain information in a series of two-dimensional tables.

In a data warehouse and data mart, information is multidimensional, it contains layers of columns and rows

• Dimension – a particular attribute of  information.

CUBE– common term for the representation of multidimensional information

DATA MINING

The process of analyzing data to extract information not offered by the raw data alone. Also begin at summary information level (coarse granularity) and progress through increasing levels of details (drilling down) or the reverse(drilling up) and to perform this uses need data-mining tools.

DATA-MINING TOOLS

Uses a variety of techniques to find patterns and relationships in large volumes of information. Eg: retailers can use knowledge of these patterns to improve the placement of items in the layout of a mail-order catalog page or Web page.

INFORMATION CLEANSING OR SCRUBBING

An organization must maintain high-quality data in the data warehouse

INFORMATION CLEANSING OR SCRUBBING– a process that weeds out and fixes or discards inconsistent, incorrect, or incomplete information

In data warehouse information cleansing occur during ETL process and second on the information once if is in the data warehouse.

Contact information in an operational system

Standardizing Customer name from Operational Systems

Information cleansing activities

Accurate and complete information

BUSINESS INTELLIGENCE

Refers to applications and technologies that are used to gather, provide access, analyze data, and information to support decision making effort.

These systems will illustrate business intelligence in the areas of customer profiling, customer support, market research, market segmentation, product profitability, statistical analysis, and inventory and distribution analysis to name a few

Eg: Excel, Access

ENABLING BUSINESS INTELLIGENCE

The principle BI enables are technology, people and culture:

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