DATABASES AND DATA WAREHOUSES Building Business Intelligence

INTRODUCTION Businesses need business intelligence (BI) Business intelligence – knowledge about your customers, competitors, business partners, environment, and internal operations Enables effective decision making Information on steroids McGraw-Hill © 2007 The McGraw-Hill Companies, Inc. All rights reserved.

INTRODUCTION IT tools help process information to create business intelligence according to… OLTP (online transaction processing) OLAP (online analytical processing) McGraw-Hill © 2007 The McGraw-Hill Companies, Inc. All rights reserved.

INTRODUCTION OLTP – gathering and processing transaction information and updating existing information to reflect transaction Databases support OLTP Operational database – database that supports OLTP McGraw-Hill © 2007 The McGraw-Hill Companies, Inc. All rights reserved.

INTRODUCTION OLAP – manipulation of information to support decision making Databases can help some Data warehouses support only OLAP, not OLTP Data warehouses – special forms of databases that support decision making McGraw-Hill © 2007 The McGraw-Hill Companies, Inc. All rights reserved.

DATA WAREHOUSES & DATA MINING Data warehouses support OLAP and decision making Data warehouses do not support OLTP Data-mining tools are tools for working with data warehouse information DBMS software = database Data-mining tools = data warehouse McGraw-Hill © 2007 The McGraw-Hill Companies, Inc. All rights reserved.

What Is a Data Warehouse? Data warehouse – logical collection of information – gathered from operational databases – used to create business intelligence that supports business analysis activities and decision-making tasks McGraw-Hill © 2007 The McGraw-Hill Companies, Inc. All rights reserved.

What Is a Data Warehouse? McGraw-Hill © 2007 The McGraw-Hill Companies, Inc. All rights reserved.

What Is a Data Warehouse? Multidimensional Rows and columns Also layers Many times called hypercubes McGraw-Hill © 2007 The McGraw-Hill Companies, Inc. All rights reserved.

What Are Data-Mining Tools? Data-mining tools – software tools that you use to query information in a data warehouse Query-and-reporting tools Intelligent agents Multidimensional analysis tools Statistical tools McGraw-Hill © 2007 The McGraw-Hill Companies, Inc. All rights reserved.

What Are Data-Mining Tools? McGraw-Hill © 2007 The McGraw-Hill Companies, Inc. All rights reserved.

Query-and-Reporting Tools Query-and-reporting tools – similar to QBE tools, SQL, and report generators in the typical database environment Also similar to pivot tables in Excel McGraw-Hill © 2007 The McGraw-Hill Companies, Inc. All rights reserved.

Intelligent Agents Use various Artificial Intelligence tools such as neural networks and fuzzy logic to form the basis for “information discovery” and building BI Help you find hidden patterns in information McGraw-Hill © 2007 The McGraw-Hill Companies, Inc. All rights reserved.

Multidimensional Analysis Tools Multidimensional analysis (MDA) tools – slice-and-dice techniques that allow you to view multidimensional information from different perspectives Bring new layers to the front Reorganize rows and columns McGraw-Hill © 2007 The McGraw-Hill Companies, Inc. All rights reserved.

Statistical Tools Help you apply various mathematical models to the information stored in a data warehouse to discover new information Regression Analysis of variance And so on McGraw-Hill © 2007 The McGraw-Hill Companies, Inc. All rights reserved.

Data Marts Data warehouses are organizationwide Data marts have subsets of an organizationwide data warehouse Data mart – subset of a data warehouse in which only a focused portion of the data warehouse information is kept McGraw-Hill © 2007 The McGraw-Hill Companies, Inc. All rights reserved.

Data Marts McGraw-Hill © 2007 The McGraw-Hill Companies, Inc. All rights reserved.

Data Mining as a Career Opportunity Knowledge of data mining can be a substantial career opportunity for you Business Objects SAS Cognos Informatica Many others McGraw-Hill © 2007 The McGraw-Hill Companies, Inc. All rights reserved.

Considerations in Using a Data Warehouse Do you need a data warehouse? DBMS may offer all you need Do all employees need the entire data warehouse? Consider a data mart How up-to-date must information be? “Snapshot” concept What data-mining tools do you need? Training can be expensive McGraw-Hill © 2007 The McGraw-Hill Companies, Inc. All rights reserved.

INFORMATION OWNERSHIP Strategic management support The sharing of information with responsibility Information cleanliness McGraw-Hill © 2007 The McGraw-Hill Companies, Inc. All rights reserved.

The Sharing of Information with Responsibility If you create it, you “own” it You will also share it with others Because you “own” it, you are responsible for its quality McGraw-Hill © 2007 The McGraw-Hill Companies, Inc. All rights reserved.

Information Cleanliness Database and data warehouse information must be “clean” No errors No duplicates McGraw-Hill © 2007 The McGraw-Hill Companies, Inc. All rights reserved.

Information Cleanliness Extraction, transformation, and loading (ETL) – what information you want from each database, how the information is associated, and what rules to follow in consolidating the information to ensure its cleanliness in a data warehouse McGraw-Hill © 2007 The McGraw-Hill Companies, Inc. All rights reserved.