Try asking your colleague what is the difference between business intelligence

and a data warehouse. I find that a lot of people, even those who work in BI projects

and BI industry, do not understand the difference. A lot of people use these

2 terms interchangeably. Some people even prefer to use 1 term instead of the

other because it simply "sounds better". Many people think that business

intelligence is not just a data warehouse, but there is more to it. But when

asked "what business intelligence systems are not data warehouse systems?"

or "what part of business intelligence systems are not data warehouses?",

most of them have difficulties explaining the answer.

These days, "business intelligence" is the norm used by most vendors

in the industry, rather than "data warehouse". Most of them call /

classify their tools as business intelligence software, not data warehouse software.

The name of Cognos

product is "Cognos 8 Business Intelligence". BusinessObjects

label themselves as "BI software company" and "global leader

in BI software". The name of one of Hyperion

products is "Hyperion System 9 BI+". SAS

Enterprise BI Server provides a fully integrated and comprehensive suite

of business intelligence software. Microsoft

promotes SQL Server 2005 as the end-to-end business intelligence platform. It

seems that only Kimball Group who

consistently use the term data warehouse. Bill

Inmon, as the inventor of this term, also uses the term data warehouse.

So, let's get into the details. This is an example of a data warehouse system:

It includes ETL from the source system, front end applications (those 10 boxes

on the right hand side), and everything in between. It has a control system,

an audit system and a data quality system (also known as data firewall). Not

all data warehouse systems have all the components pictured above, for example,

some data warehouse system may not have operational data stored (ODS), see this

article for details.

The 2 blue items are data warehouse databases. The cylinder is in relational

format (labelled as dimensional data store, DDS for short), the box is in multidimensional

format (labelled as cubes in the picture above). This blue cube is also known

as on line analytical processing cube, or OLAP cube for short.

The yellow items are business intelligence applications. Most business intelligence

applications take data from multidimensional format data warehouse, but some

do take data from the relational format. The whole diagram above is also known

as business intelligence system.

Some business intelligence applications take data directly from the source

system. For example, some dashboard systems may get sales summary data from the source

system and display it in gauge meter format. In this case, we can not call the

system a data warehouse system. It is still a business intelligence system,

but it is not a data warehouse system, because it does not have a data warehouse

database behind the gauge meter application.

Business intelligence systems, in the past also known as executive information

systems, or decision support systems, are a non transactional IT system used to

support business decision making and solve management problems, normally used

by top executives and managers. Many

varied definitions exist in the market place today about the business intelligence

system; one

from Dr. Jay Liebowitz is arguably one of the better ones. Most people agree

that OLAP and data warehouse systems are a major and important part of business

intelligence systems. Most business intelligence systems are in the form of a

data warehouse systems. Yes, there are business intelligence systems that do

not use OLAP or data warehouses, as illustrated in the example of gauge meter

application above, but they are more rare than the ones with OLAP or a data warehouse.

According to Ralph Kimball, in his book The

Data Warehouse ETL Toolkit, a data warehouse is a system that extracts,

cleans, conforms, and delivers source data into a dimensional data store and

then supports and implements querying and analysis for the purpose of decision

making. He stressed that a data warehouse is not a product, a language,

a project, a data model or a copy of transaction system. In an interview

with Professional Association for SQL Server (PASS) on 30th April 2004,

he explained about the relationship between data warehousing and business intelligence.

In their latest book, The

Microsoft Data Warehouse Toolkit, Joy Mundy and Warren Thornthwaite do not

differentiate data warehouse systems and business intelligence systems. They consistently

use the term DW/BI system throughout the book. This is understandable because,

as I describe above, most business intelligence systems are in the form of a

data warehouse system.

Bill Inmon, who invented the term

data warehouse, defines data warehouse as a source of data that is subject oriented,

integrated, nonvolatile and time variant for the purpose of management's decision

processes. He pointed that the term data warehouse was never trademarked or

copyrighted. As a result, anyone can call anything a data warehouse. He recently

defined a new term, DW 2.0, and this one is trademarked so nobody can change

the definition. He explained the architecture in his

article in dmreview, along with the differences between the first generation

of data warehouses and DW 2.0 and its advantages.

So, as a summary, back to the original question, what is the difference between

data warehouse and business intelligence? Most business intelligence systems

are based on data warehouse systems (the one with dimensional model, fact tables,

dimension, etc), but some business intelligence systems are not data warehousing,

i.e. taking data directly from the source system, like the example described

above. Business intelligence application (as opposed to business intelligence

system) is the yellow boxes on the diagram above, i.e. the front end applications.

The data warehouse database (or sometimes people dropped the word database, so it

becomes just 'data warehouse') is the blue cylinder and blue box on the diagram

above, i.e. the dimensional storage, whether in relational database format or

in multidimensional database format.

If people say 'data warehouse', be careful because it can mean either data

warehouse system (the whole diagram above) or data warehouse database (just

the blue items). If people say 'business intelligence', it can mean either business

intelligence system (the whole diagram above, or a BI system without data warehouse)

or business intelligence application (the yellow boxes).

I hope this article makes the terms clearer, but I am open to comments and

suggestions. As Ralph Kimball said, if you ask 10 different people what data

warehouse is you are likely to get 10 different answers.

Vincent Rainardi

1st May 2006