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Business Intelligence
Zamaneh Jahed
What is Business Intelligence?
Business Intelligence (BI) is a broad category
of applications and technologies for gathering,
storing, analyzing and providing access to data
to help enterprise users make better decisions.
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A Brief History of BI
 BI has its root in the MIS reporting system of
the 1970.
 This term was introduced by Gartner Group
in the middle 90s.
 Until 2005, BI systems had Artificial
intelligence capabilities.
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BI Architecture
Data storage, retrieval Layer
Data source layer
Nightly
Replication
Analytical Layer
Presentation
Web Portal
Fact Tables
Portal
Portal
Portal
Portal
Semantic
Security
Conformed
Dimensions
SAS
Information
Maps
Excel
Flash
Dashboard
Data Transformation
HTML
Metadata Web Services
Metadata Registry
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Operational Data Source:
Business Intelligence system collects data from
various sources including operation database,
OLTP, ERP, external database and etc.
ETL tools (Extract, Transform, Load):
They are used to pull data from source database,
transform the data so that it is compatible with
the data warehouse and then load it into data
warehouse.
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ETL Process
Customer
Accounting
Inventory
Orders
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BI Target
Database
Data Warehouse
Data warehouse is a database that stores current and
historical data. It consolidates and standardizes
information from different operational database so that
the information can be used across the enterprise for
management analysis and decision making.
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Data Mart
Data Mart is a subset of a data warehouse in
which a summarized or highly focused portion of
the organization’s data is placed in a separate
database for a specific population of users.
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Cube
The basic unit of storage and analysis in Analysis
Services is the cube. A cube is a collection of data
that’s been aggregated to allow queries to return
data quickly.
Dimension
Each cube has one or more dimensions, each
based on one or more dimension tables. A
dimension represents a category for analyzing
business data
Fact table
A fact table contains the basic information that you
wish to summarize. This might be order detail
information, payroll records, or anything else
that’s amenable to summing and averaging.
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OLTP and OLAP
OLTP (On-line Transaction Processing)
Major task of traditional relational DBMS.
Day to day operations: purchasing, inventory,
banking, manufacturing, payroll, registration,
accounting, etc.
Aims at reliable and efficient processing of a
large number of transaction and ensuring data
consistency.
OLAP (On-line Analytical Processing)
Major task of data warehouse system.
Data analysis and decision making.
Aims at efficient multidimensional processing of
large data volumes.
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Revenue:
2,000,000.
Time
Measure
Customer
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OLAP or
multidimensional
analysis: Means
you can analyze
‘measures’ at the
intersection of any
combination of
dimensions:
“Show me the Revenue
we made from Customer
A for Product 1 in
January 2007”
References
 Butuza- A. 2011.Increasing the Business Performances
using Business Intelligence
 Microsoft SQL Server 2008 Analysis Services Step by Step.
 Kenneth C. Laudon and Jane P. Laudon, Management
Information systems.
 Larissa T. Moss, Shaku Atre, Business Intelligence
Roadmap: The complete Project Lifecycle for Decision
Support Applications.
 Turban, Efraim.Business Intelligence: managerial approach.
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