Why and What is a Data Warehouse: Size, Intelligence, and Stages, Slides of Data Warehousing

Download Why and What is a Data Warehouse: Size, Intelligence, and Stages and more Slides Data Warehousing in PDF only on Docsity! 1 Data Warehousing Lecture-2 Introduction and Background Docsity.com 2 Introduction and Background Docsity.com 5 Reason-1: Why a Data Warehouse?  Size of Data Sets are going up ↑.  Cost of data storage is coming down ↓.  The amount of data average business collects and stores is doubling every year  Total hardware and software cost to store and manage 1 Mbyte of data  1990: ~ $15  2002: ~ ¢15 (Down 100 times)  By 2007: < ¢1 (Down 150 times) Docsity.com 6 Reason-1: Why a Data Warehouse?  A Few Examples WalMart: 24 TB France Telecom: ~ 100 TB CERN: Up to 20 PB by 2006 Stanford Linear Accelerator Center (SLAC): 500TB Docsity.com 7 Caution! A Warehouse of Data is NOT a Data Warehouse Docsity.com 10 Reason-2: Why a Data Warehouse? List of all items that were sold last month? List of all items purchased by Tariq Majeed? The total sales of the last month grouped by branch? How many sales transactions occurred during the month of January? DBMS Approach Docsity.com 11 Reason-2: Why a Data Warehouse? Which items sell together? Which items to stock? Where and how to place the items? What discounts to offer? How best to target customers to increase sales at a branch? Which customers are most likely to respond to my next promotional campaign, and why? Intelligent Enterprise Docsity.com 12 Businesses want much more…  What happened?  Why it happened?  What will happen?  What is happening?  What do you want to happen? Reason-3: Why a Data Warehouse? Stages of Data Warehouse Docsity.com 15 What is a Data Warehouse? Transaction System  Management Information System (MIS)  Could be typed sheets (NOT transaction system) Ad-Hoc access  Dose not have a certain access pattern.  Queries not known in advance.  Difficult to write SQL in advance. Knowledge workers  Typically NOT IT literate (Executives, Analysts, Managers).  NOT clerical workers.  Decision makers. Docsity.com 16 Another View of a DWH Subject Oriented Integrated Time Variant Non Volatile Docsity.com