As part of the research project for the course Technical Foundations of Information Systems at the University of Illinois, our team worked on the topic, Business Intelligence. The presentation focuses on what is Business Intelligence, its various components, latest tools, the need of BI as well as applications of this technology. This project deals with the latest development of BI technologies (hardware or software) and includes comprehensive literature survey from Journals, and the Internet.
Business intelligence- Components, Tools, Need and Applications
1. BUSINESS
INTELLIGENCE
Title:
Group 2:
Surendar Sekar Gunasekar
Rishika Nemuri
Raj Singh Rathore
Sadhana Subramanian
Aditya Trivedi
2. Introduction
● The process of converting large amounts of raw data into information that has
meaning is known as Business Intelligence.
● It is a technology-driven process used to analyse businesses to implement
strategies which help in maintaining long-term stability and obtain competitive
market advantage.
● It is used to provide various views in operations of a business like the past,
present and future which help in making operational and strategic decisions.
● The external data which is gathered from the market where the company resides
and the internal data like operations and financial data are combined to give a
3. Functions of BI technologies
-reporting
-processing, predictive and online analytic processing analysis
-data, process and text mining
-complex event processing
-business performance management
-benchmarking
-predictive and prescriptive analytics.
4. Components of BI
The various components of BI strategies are OLAP, Advanced Analytics, Data
Warehousing, Data Source etc.
All these data sources can be grouped under these three main pillars of BI
tools:
● Components that aid information and knowledge discovery
These are categorized by the fact that they help in data extractions from
the pre-existing data. For example, Ad hoc queries, OLAP, Data Mining
and Analytics.
● Components that analyze data and improve decision making
These intelligence components are designed to provide automated
decision making capability. For example, Business Analytics, DSS,
Intelligence Systems.
● Components for visualizing complex data relationship
Graphically or visualizing the data analyzed is what the components under
this category manages with. For example, Dashboard, GIS, Visual
Analytics.
5. Knowledge and Information
Discovery
Reports: An account of work or a set of work which gives an information about
a certain event in a presentable format.
1. Scheduled
Report
2. Key- Indicator
Report
3. Drill-Down
Report
4. Exception
Report
6. Knowledge and Information
Discovery contd...
Ad Hoc Queries
● Query is issued at the moment.
● Get information when the need arises or to derive information for
unplanned requests.
● It supports a non routine decision.
● It is not scheduled to run again, just one time query.
Online Analytical Processing (OLAP)
● BI tools that performs multidimensional analysis the data in the database.
7. Knowledge and Information
Discovery contd...
● OLAP server acts as a interface between the database management
system and the user who queries for the analysis.
● OLAP server structures the data into cubes called OLAP cubes.
8. Knowledge and Information
Discovery contd...
OLAP Cube: its components and
process
● MEASURES
● DIMENSIONS
● SLiCING
● DICING
9. Knowledge and Information
Discovery contd...
DATA MINING: It is the process to discover the hidden predictive relationship
within the data.
● Association Discovery: A process
that finds correlation within data.
● Clustering: Grouping data which are
similar.
● Classification: Distributing data under
different classes
10. Knowledge and Information
Discovery contd...
Unstructured Data Analysis
● Text Mining: Mining and then analyzing information from textual
documents
● Web Content Mining: Extracting information from the web documents.
● Web Usage Mining: It analyzes the pattern of the users who search the
web page and builds a pattern of search that the customer will do or had
done.
11. Business Analytics in
Decision Making
Business Analytics: Used to analyze the trec or predict an outcome that helps
in forecasting.
Decision Support Systems: Capable of finding the root cause analysis for a
recurring problem
Intelligent Systems: A set of information technology combined together to
simulate human intelligence.
Ex, Expert Systems - Neural Systems - Intelligent Agent Systems
Knowledge management Systems Information is collected, formatted and
presented in a way useful to the users
12. Data Visualization
What is Data Visualization ?
● Data visualization is representation of data in pictorial or graphical format.
● Data visualization makes it easier to detect and recognize patterns,
trends, or correlations that might go undetected in text based data.
14. Tools For Data Visualization
● IBM Cognos Business Intelligence Software
IBM Cognos Business Intelligence turns data into past, present and future
views of your organization’s operations and performance so your decision
makers can capitalize on opportunities and minimize risks.
This software has Formatted and interactive Dashboards which feature highly
scalable distribution and scheduling capabilities, while custom visualizations
make the information easy to absorb.
15. Tools For Data Visualization
● Tableau Software
Tableau is highly scalable and has no limit with regards to performance, speed
or business size and can be flexed to suit a number of industries.
Tableau offers a "ShowMe" feature that draws views based on visualization
best practices for user-selected fields.Tableau has taken years of research and
built best practices right into the solution.
16. Tools For Data Visualization
SAP - Business Intelligence Software
SAP BusinessObjects gives organizations a full set of tools to manage and
optimize Business Intelligence. From a centralized portal, companies can
handle everything from ETL and data cleansing to predictive dashboards and a
variety of reports - Crystal Reports, OLAP, ad hoc and more.
The key advantage to SAP BusinessObjects is that the solution can grow with a
company, allowing organizations to employ additional tools as necessary and
eliminating the need to stitch together various disparate solutions that can
result in a bulky, user-unfriendly system.
17. The need for BI
● Business Intelligence is no longer a term only associated with large
organizations.
● As the price of hardware and storage drops, the Business Intelligence
technology is advancing with flexible deployment and licensing options that
are easily available- Rendering Business Intelligence in reach for almost
every organization.
Business Intelligence lays the foundation for Actionable Plans of an
organization
18. 5 Reasons why BI are top
priority for Organizations
● Business Intelligence is seen as an opportunity to empower users,
enlighten the organization and to convert IT from a cost centre to a source
of competitive advantage.
Business Intelligence has consistently ranked highly in polls of CIO priorities, and
there are signs that they are only growing in importance.
19. Data is
Big
Business
Why
Business
Intelligence
is Top
Priority
Users
crave
Information
Smart
Devices are
Everywhere
The
Advanceme
nt of
Analytics
Cloud
Enablemen
t
These reasons are compelling enough for organizations who still haven’t
thought of leveraging the power of Business Intelligence.
20. Data is Big Business
● Whether it is Facebook’s IPO
or news about how US retailer
Target uses Analytics, there
are signs everywhere that
value from data is the key
to success in modern
business.
● Organizations have started to
understand that corporate data can
be used to provide insights,
analysis and competitive advantage.
21. Users Crave Information
● Consuming detailed information in electronic is not just a pastime
anymore. Whether it is online news, social networking messages,
YouTube Videos, the consumption of information is phenomenal.
● This consumption is a gold mine for organizations trying to tap the pulse of
their consumers and directly reach out through communicating to them
through a medium they are comfortable with.
22. Smart Devices Enablement
● Computers have been a part of the modern household for decades now,
but it is only a recent development that consumers carry powerful, internet-enabled
computing devices with them everywhere they go.
● In the business context, the most significant impact is that they place BI
and Analytics in the hands of senior decision makers.
● Making BI and Analytics tools accessible via a tablet means they have an
audience at the executive table.
23. Cloud Enablement
● Cloud Computing is one of the key drivers for Business Intelligence.
● It offers organizations with tight budgets and over-burdened IT
infrastructure an opportunity to access cheap and flexible computing
resources.
● It also accelerates the IT infrastructure procurement processes allowing
the IT department to focus on business engagement and BI systems to
ensure that requirements are met.
24. The Advancement of
Analytics
● The roots of BI lie in producing regular reports on the data tracked or
recorded. However, businesses are increasingly applying more
sophisticated statistical techniques to make predictions, and to spot subtle
yet important trends in data.
● These advanced analytical techniques are more likely to confer
competitive advantage than simple retrospective reporting.
● Meanwhile the increase in the volume, velocity and variety of data
available to BI systems- so called ‘Big Data’- allows organizations to apply
statistical analysis to questions that were previously unanswerable
25. Application of BI
Some of the Business Intelligence applications are,
Performance measurement and Benchmarking: To assess the performance
of employees in an organization and also drive them towards business goals.
Strategic planning and Report: Designing and building an infrastructure to
strategize the function of business reports. Some of them are OLAP,
Data Visualization, Executive Information System.
Business Analysis: It is a process of acquiring an optimal decision from
various solutions using different analytics process. some of the analytics
process include Data mining, business process modeling, predictive analytics,
prescriptive analysis.
26. Application of BI
Brainstorming and Knowledge Management: The usage of different
strategies and practices to identify, create, represent, distribute and include
experience and insights of business knowledge.
Collaboration tools: Collaborating with different people to gain knowledge on
various factors both from inside and outside the business areas. It is
accomplished through data sharing and electronic data interchange.
27. The Future of BI
Some of the business intelligence trends are,
● ETL issues like throughput and volume are handled by Business
Intelligence products.
● Vendor services has been rendered obsolete due to the availability of
business intelligence open source softwares.
● The Concurrency, Response time and scaling has been increased a lot
due to the inclusion of various business intelligence components.
● IN-memory processing and various analytical applications are used by
organization to strategize their business goals by organizations.
● Bringing forth real time solution for various issues will be cornerstone for
future business applications.