This Presentation covers the basic concept of Business Intelligence, BI Technologies, BI Tools, Future of BI, Real time BI, Key Stages of BI, BI Industry & Decision Support Applications.

1. Business Intelligence
Dr. Kamal Gulati

2. Business Intelligence…examples
 A hotel franchise uses BI analytical applications to compile statistics on average
occupancy and average room rate to determine revenue generated per room. It also
gathers statistics on market share and data from customer surveys from each hotel to
determine its competitive position in various markets. Such trends can be analyzed
year by year, month by month and day by day, giving the corporation a picture of how
each individual hotel is faring.
 A bank bridges a legacy database with departmental databases, giving branch
managers and other users access to BI applications to determine who the most
profitable customers are or which customers they should try to cross-sell new products
to. The use of these tools frees information technology staff from the task of generating
analytical reports for the departments and it gives department personnel autonomous
access to a richer data source.
 A telecommunications company maintains a multiterabyte decision-support data
warehouse and uses business intelligence tools and utilities to let users access the data
they need without giving them carte blanche to access hundreds of thousands of
mission-critical records. The tools set boundaries around the data that users can access,
creating data "cubes" that contain only the information that's relevant to a particular
user or group of users.

3. BI Industry Scenario…
 Today's exciting BI market is ripe with opportunities to hit your strategic
business targets.
 Gaining market share, keeping customers and controlling costs remain key
objectives. Mid-market executives and big corporate department heads rush
to cost effectively meet these complex needs. How? Through improved use of
their existing database systems.
 CFOs require 'business intelligence' systems that display accurate SKU or
customer-level P&Ls, permitting reliable channel and store comparisons over
time. Improved forecasts are vital, too!
 Data warehousing and analytical skills are combined with an understanding
of industry issues, as we refine and implement your vision.
 According to Gartner survey of 1,400 CIOs, business intelligence was ranked
the top technology priority surpassing security.
 The BI and analytics market is currently valued at $8.5 Billion and is
expected to grow to $13 Billion over the next five years

4. Business Intelligence (BI)
BI refers to
application and
technology,
which is used
to gather, provide access
to, and analyze
data and information
about the company
operations

5. Business Intelligence Definition
BI is neither a product
nor a system.
It is an architecture and
a collection of
integrated operational
as well as decision-support
applications and databases
that provide the business
community
easy access to business data.

6. BI Popularized…
In 1989
Howard Dresner
a Research Fellow
at Gartner Group
popularized "BI"
as an umbrella term
to describe a set of concepts
and methods to improve
business decision-making
by using fact-based
support systems

7. Why BI solutions ?

8. More data and data sources…

9. Evolution from Static Report to BI…

10. Evolution of financial Systems…

11. Categories of Report Writers

12. Sources of Information for Vendor
& Product Research

13. Key Stages of BI
Data Sourcing
Data Analysis
Situation Awareness
Risk Analysis
Decision Support

14. BI applications and technologies
can help companies analyze:
changing trends in market share
changes in customer behavior
and spending patterns
customers' preferences
company capabilities
market conditions

15. Significance of BI…
To know about Customers
Having access to timely and accurate information
is an important resource for a company,
which can expedite decision-making
and improve customers' experience.
In the competitive customer-service sector,
companies need to have accurate, up-to-date information
on customer preferences,
so that the company can quickly adapt to their changing demands.
BI enables companies to gather information
on the trends in the marketplace and
come up with innovative products or services
in anticipation of customer's changing demands.

16. Significance of BI…
To know about Competitors…Market…
BI applications can also help managers
to be better informed about actions that a company's
competitors are taking.
BI systems can also be designed to provide managers
with information on the state of economic trends
or marketplace factors, or to provide managers
with in depth knowledge about the internal
operations of a business.

17. Significance of BI…
For avoiding Guesswork…
BI can be used to help analysts and managers
determine which adjustments are most likely
to respond to changing trends.
BI systems can help companies develop a more
consistent, data-based decision making process
for business decisions, which can produce better
results than making business decisions by
"guesswork."

18. Significance of BI…
For sharing of information…
BI can help companies share selected strategic information
with business partners.
Some businesses use BI systems
to share information with their suppliers like…..
inventory levels
performance metrics
other supply chain data

19. Significance of BI…
For improving performance…
BI applications can enhance communication among
departments, coordinate activities, and enable
companies to respond more quickly to changes
(e.g., in financial conditions, customer
preferences, supply chain operations, etc.).
When a BI system is well-designed and properly
integrated into a company's processes and
decision-making process, it may be able to
improve a company's performance.

20. BI Technologies
need to have a secure computer system
which can specify different levels of user
access to the data 'warehouse',
need to have sufficient data capacity,
a plan for how long data will be stored
(data retention).
BI analysts have developed software tools
to gather and analyze
large quantities of unstructured data such as
production metrics,
sales statistics,
attendance reports,
customer attrition figures.

21. BI Tools
AQL – Associatede Query Logic
Balanced Scorecard
Business Activity Monitoring
Business Performance Management
Business Planning
Business Process Re-engineering
Competitive Analysis
User/End-User Query and Reporting
Enterprise Management System
Executive Information System
SCM – Supply Chain Management
Demand Chain Management
and
Finance and Budgeting tools.

22. Other BI applications are used
to store and analyze data
Data Mining, Framing & Warehousing
(DSS) and Forecasting
Document Warehouse & Manage,ment
Knowledge Management
Mapping,
Information Visualisation and Dashboarding;
Management Information System (MIS);
Geographic Information System (GIS);
Trend Analysis;
Software As A Service (SaaS)
Business Intelligence offerings (On Demand)
Online Analytical Processing (OLAP) and
Multidimensional analysis
sometimes called "Analytics"
(based on the "hypercube" or "cube");
Real Time Business Intelligence
Statastics and Technical Data Analysis
Web Mining, Text Mining and
Systems Intelligence

23. Other BI applications are used
to analyze or manage the
"human" side of businesses,
Customer Relationship
Management (CRM)
Marketing Tools
Human Resources
applications.
Web Personalisatiuon

24. Some common factors of
ill-equipped organizations to implement BI…
 Lack of understanding of the complexity of BI decision-
support projects
 Lack of recognizing BI decision-support projects as
cross-organizational business initiatives and not
understanding that cross-organizational initiatives are
different from stand-alone solutions
 Unavailable or unwilling business representatives
 Unengaged business sponsors or business sponsors who
have little or no authority due to their low-level positions
within the organization

25. Some common factors of
ill-equipped organizations to implement BI…
 Lack of skilled and available staff as well as suboptimum staff
utilization
 Inappropriate project team structure and dynamics
 No software release concept (no iterative development method)
 No work breakdown structure (no methodology)
 Ineffective project management (only project administration)
 No business analysis and no standardization activities
 No appreciation of the impact of dirty data on business profitability
 No understanding of the necessity for and the usage of meta data
 Too much reliance on disparate methods and tools (the "silver bullet"
syndrome)

26. Designing and implementing a
Business Intelligence Program
Factors need to be considered
Goal Alignment queries
Baseline queries
Cost and risk queries
Customer and Stakeholder queries
Metrics-related queries
Measurement Methodology-
related queries
Results-related queries

27. The Future of BI…
BI users are beginning to demand
[Real time BI] or near real time
analysis relating to their business,
particularly in front line operations.
They will come to expect up to date and fresh
information in the same fashion as they
monitor stock quotes online.
Monthly and even weekly analysis
will not suffice

28. The Future of BI…
"Business users
don't want to wait for information.
Information needs to be always on
and never out of date.
This is the way we live our lives today.
Why should Business Intelligence be any
different?"
Charles Nicholls,
CEO of SeeWhy, a Software company,
Windsor UK

29. The Future of BI…
In the not too distant future companies
will become dependent on real time
business information in much the
same fashion as people come to
expect to get information on the
internet in just one or two clicks.
"This instant "Internet experience"
will create the new framework for
business intelligence, but business
processes will have to change to
accommodate and exploit the real-
time flows of business data."
Nigel Stokes, CEO, DataMirror Corp.

30. BI 2.0
“BI 2.0" is the recently-coined
term which is part of the
continually developing BI
industry and heralds the next
step for BI.
“BI 2.0" is used to describe
the acquisition, provision
and analysis of
"real time" data.

31. "Real Time BI - Get Real"
"The mismatch between fantasy and reality
is driven by two factors.
The first is that business rules and structures
(general ledgers, product classification,
asset hierarchies, etc.) are not in fact
uniform, but are spread out among many
disparate transaction system
implementations...
The second problem is that the landscape of
business structures is itself in constant
flux, as groups reorganize, subsidiaries
are sold or new companies acquired".
…Veteran Analyst… Andy Hayler…

32. "Real Time BI…a pipe dream”
As long as Business Intelligence relies upon
some kind of data warehouse structure
(including web-based virtual data
"warehouses"), data will have to be
converted into "a lowest common
denominator consistent set."
When it comes to dealing with multiple,
disparate data sources and the
constantly changing, often volatile,
business environment which requires
tweaking and restructuring of IT
systems, getting BI data in a genuinely
true, "real time" format remains,
"a pipe dream.....Hayler