Data Warehousing

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7 Νοε 2013 (πριν από 3 χρόνια και 11 μήνες)

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Data Warehousing

Introduction

Text and Resources

The Data Warehouse Lifecycle Toolkit,
Kimball, Reeves, Ross, and Thornthwaite


Internet resources


Data Warehousing Institute


Teradata Institute


Intelligent Enterprise

Data Warehouse Approach

An old idea with a new interest:


Cheap Computing Power

Special Purpose Hardware

New Data Structures

Intelligent Software

Heightened Business Competition

Data Warehouse

“Queryable source of data in the enterprise”

Common source of consistent
organizational information

Identify problems and opportunities

User focused

Retrieval focused

Goals of the Course

Understand the Data Warehouse philosophy

Dimensional modeling

Tools for Warehouse management

Business intelligence

Business practice


What To Expect

Help develop course expectations for the
future


Two tests

Exercises and a semester project

Graduate Presentation

What is a data warehouse?

A database filled with
large volumes of
cross
-
indexed
historical business
information that users
can access with
various query tools.

The warehouse usually
resides on its own
server and is separate
from the transaction
-
processing or “run
-
the
-
business” systems.

Purpose of a data warehouse

Provides an architecture for the flow of data
from operational systems to decision
support systems


DW involves a many record analysis, during
which all data has to be locked

Used to discover trends and patterns


Present opportunities


Identify problems

ROI of data warehouses

New insights into


Customer habits


Developing new products


Selling more products

Cost savings and revenue
increases

Cross
-
selling of products

Less mainframe computer
storage

Identify and target most
profitable customers

Capital outlay and
development/training time
can be extraordinary.

Quality of system output

Levels of risk

Intangibles


Cio.com (middle ground)


Course Outline

Introduction and basic principles

Data extraction: SQL data definition code

Warehouse Architecture: Dimensional
Modeling

Data Cleansing: SAS Datastep coding

Data Presentation: MS Analysis Services