CHAPTER 8:ACCESSING ORGANIZATIONAL INFORMATION- DATA WAREHOUSE

•          Data warehouse – a logical collection of information – gathered from many different operational databases – that supports business analysis activities and decision-making tasks

•          The primary purpose of a data warehouse is to aggregate information throughout an organization into a single repository for decision-making purposes

•          Extraction, transformation, and loading (ETL) – a process that extracts information from internal and external databases, transforms the information using a common set of enterprise definitions, and loads the information into a data warehouse

•          Data mart – contains a subset of data warehouse information

Multidimensional Analysis  and Data Mining

•          MultiDatabases 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

dimensional Analysis  and Data Mining

·         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

•          To perform data mining users need data-mining tools

–      Data-mining tool – uses a variety of techniques to find patterns and relationships in large volumes of information and infers rules that predict future behavior and guide decision making

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

•          Information cleansing activities

•          Accurate and complete information

Business intelligence

•          Business intelligence – information that people use to support their decision-making efforts

•          Principle BI enablers include:

–      Technology

–      People

–      Culture

Technology

–      Even the smallest company with BI software can do sophisticated analyses today that were unavailable to the largest organizations a generation ago.

–      The largest companies today can create enterprisewide BI systems that compute and monitor metrics on virtually every variable important for managing the company.

–      How is this possible? The answer is technology—the most significant enabler of business intelligence.

People

–      Understanding the role of people in BI allows organizations to systematically create insight and turn these insights into actions.

–      Organizations can improve their decision making by having the right people making the decisions.

–      This usually means a manager who is in the field and close to the customer rather than an analyst rich in data but poor in experience.

Culture

•          A key responsibility of executives is to shape and manage corporate culture.

•          The extent to which the BI attitude flourishes in an organization depends in large part on the organization’s culture.

•          Perhaps the most important step an organization can take to encourage BI is to measure the performance of the organization against a set of key indicators.