Understanding Business Intelligence: Concepts, Significance, and Components, Lecture notes of Chemistry

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Reference: Management Information Systems 8/e Chapter 1 Managing the Digital Firm Internet sources 1 10/29/

Unit: Business Intelligence

What is Business Intelligence (BI)

Why Business Intelligence?

Significance of BI

Characteristics of an Intelligent system

Business management Issues

Components of BI

After studying, you will be able to understand the following 2 10/29/



Business Intelligence is the

processes, technologies, and tools that help us

change data into information, information into

knowledge and knowledge into plans that guide

organization

What is Business Intelligence?

3

• (^) What happened?
• (^) What is happening?
• (^) Why did it happen?
• (^) What will happen?
• (^) What do I want to happen? Past Present Future

7

 (^) Companies need to have accurate, up-to-date information on customer preferences , So that company can quickly adapt to their changing demands  (^) BI applications can also help managers to be better informed about actions that a company’s competitors are taking  (^) It help analysts and managers to determine which adjustments are mostly likely to respond to changing trends  (^) IT can help companies develop a more consistent,data- based decision,which can produce better results than making business decisions by “guesswork” Significance of BI

Data

Sourcing

Data

Analysis

Situation

Awareness Risk

Analysis

Decision

Key Stages of BI

changing trends in market share changes in customer behavior and spending patterns customers' preferences company capabilities market conditions 11 10/29/

BI applications and technologies can help

companies analyze

Dashboards

Key Performance Indicators

Data Warehouse

Data Mining

OLTP – Online Transaction Processing

OLAP – Online Analytical Processing

Forecasting

Graphical Reporting Components of BI



BI dashboards can provide a customized

snapshot of daily operations, and assist the user

in identifying problems and the source of those

problems, as well as providing valuable, up-to-

date information about financial results, sales

and other critical information – all in one place

Dashboards

Key Performance Indicators:  (^) BI provides simplified KPI management and tracking with powerful features, formulae and expressions, and flexible frequency, and threshold levels.  (^) This module enables clear, concise definition and tracking of performance indicators for a period, and measures performance as compared to a previous period. Intuitive, color highlighters ensure that users can see these indicators in a clear manner and accurately present information to management and team members.  (^) Users can further analyse performance with easy-to-use features like drill down, drill through, slice and dice and graphical data mining

Data Mining & it’s Process

• (^) Data Mining is the computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems. - (^) Before data mining algorithms can be used, a target data set must be assembled Pre Processing - (^) Involves Anomaly Detection - (^) Clustering - (^) Classification - (^) Regression - (^) Summarization Data Mining - (^) The final step of knowledge discovery from data is to verify that the patterns produced by the data mining algorithms occur in the wider data set Result Validatio n

OLAP – Online Analytical Processing

• (^) Online analytical processing, or OLAP is an approach to answering multi- dimensional analytical (MDA) queries swiftly
• (^) OLAP tools enable users to analyse multidimensional data interactively from multiple perspectives. OLAP consists of three basic analytical operations: consolidation (roll-up), drill-down, and slicing and dicing.
• (^) Consolidation involves the aggregation of data that can be accumulated and computed in one or more dimensions. Types of OLAP Multidimensional (^) Relation al Hybri d

OLAP Vs. OLTP OLTP OLAP User (^) Clerk/IT professional Knowledge Worker Function (^) Day to Day Operations Decision Support Database Design (^) Application Oriented Subject Oriented Data (^) Current, Isolated Historical, Consolidated View Detailed, Flat Relational Summarized, Multidimensional Usage (^) Structured, Repetitive Ad Hoc Access (^) Read/Write Read