Business analytics uses data, statistical analysis, and other quantitative techniques to help understand and optimize business performance. It is becoming a major tool used by many large corporations. There are various tools and techniques for business analytics, including online analytical processing (OLAP), data visualization, data mining, predictive analysis, and geographic information systems (GIS). Real-time business intelligence and automated decision support are also increasingly important for analytics.

1. Business Analytics and Data
Visualization

2. Business Analytics
• Broad category of applications and techniques
• Help enterprise users to make better business
and strategic decisions
• Also known as analytical processing, BI tool, BI
applications or just BI.
• Is becoming a major tool for most medium
and large corporations.
• E.g. Pizza Hut has significantly boosted it’s
sales revenue by using BI tools.

3. Tools and techniques of BA

4. Vendors Classification
1.MicroStrategy’s classification of BA: The five
styles of BI
• Enterprise reporting
• Cube analysis
• Ad hoc querying and analysis
• Statistical analysis and data mining
• Report delivery and alerting

5. 2.SAP’S classification of strategic Enterprise
Management
• Operational level-supports transaction
processing on the operational level.
• Managerial level-Managers can use SAP R/3 to
access all reports, make queries and drill down
• Strategic level-company offers products under
title SAP SEM, which includes BA.

6. Capabilities of EIS/ESS
Capability Description
• Drill down
• Critical success
factors
• Key performance
• Status report
• Trend analysis
• Ad hoc analysis
• Exception
reporting
• Ability to go to additional details
• Can be organizational, industry,
departmental etc.
• Specific measure of each CSF
• Latest data available on KPI
• Short, medium and long term trend of
KPI
• At any time, with any desired factor
• Using reports that highlight
deviations larger than certain
thresholds.

7. Online Analytical Processing(OLAP)
• Activities performed by end users in online systems
– Specific, open-ended query generation
• SQL
– Ad hoc reports
– Statistical analysis
– Building DSS applications
• Modeling and visualization capabilities
• Special class of tools
– DSS/BI/BA front ends
– Data access front ends
– Database front ends
– Visual information access systems

8. Types of OLAP
• Multidimensional OLAP:OLAP implemented
through multidimensional database
• Relational OLAP: is implemented on the top of
relational database
• Database OLAP and Web OLAP: Database OLAP-RDBMES
designed to host OLAP structure.
Web OLAP-OLAP data accessible from a web browser
• Desk OLAP: Performs local multidimensional
analysis

9. Characteristics of OLAP
• Categorical Analysis: Based on historical data
• Exegetical Analysis: Based on historical data.
Adds the capability of drill-down analysis.
• Contemplative Analysis: allow user to change
a single value to determine it’s impact.
• Formulaic Analysis: permits change to
multiple changes.

10. Benefits of OLAP
• Multidimensional conceptual view for
formulating queries.
• Transparency to the user.
• Easy accessibility: Batch and online access
• Consistent reporting performance
• Client/Server architecture: the use of
distribution resources
• Generic dimensionality
Continue……

11. • Dynamic sparse matrix handling.
• Multi user support rather than support for
only a single user.
• Unrestricted cross-dimensional operations.
• Intuitive data manipulation
• Flexible reporting
• Unlimited dimensions and aggregation level.

12. Reports and Queries
Reports
• Must be uniform, flexible, adjustable
• Two types:
1.Routine Reports-
• Generated automatically and send periodically
• E.g. weekly sales figures, units produced each day,
Monthly hours worked.
2.Ad Hoc Reports-
• Created for specific user whenever needed
• For different time intervals or for only a subset of the
data

13. Queries
Ad Hoc Queries
• Query cannot be determine prior to the query
is issued.
• Allow user to request information from
computer which not include in reports.
• To generate new queries or modify old ones.
• Queries can be done on static data or dynamic
data.

14. Multidimensionality
• Efficient way to organized raw and summery data
for analysis and presentation.
• It enables data to be organized the way individual
managers.
• Factor considered
1.Dimensions:like products, salespeople, market
segment
2.Measures: like money, sales volume, inventory
3.Time: are daily, weekly, monthly, quarterly and
yearly

15. Multidimensional data cubes
• Used to represent data along some measure
of interest.
• It can be two dimensional, three dimensional
or higher-dimensional.
• Provide an opportunity to retrieve decision
support information in an efficient manner.
• Cube analysis: Allow to perform queries by
flipping through a series of report views.

16. Limitations of Dimensionality
• More computer storage.
• Multidimensional products cost significantly
more.
• Database loading consumes significant system
resources and time.
• Complex interfaces and maintenance

17. Advance Business Analytics
• Data Mining:
– Statistical methods
– Decision trees
– Case based reasoning
– Neural computing
– Intelligent agents
– Genetic algorithms
• Predictive Analysis:
– Helps to determine the probable future outcome for an
event
– Identify relationships and patterns

18. Data Visualization
• Technologies supporting visualization and
interpretation
– Digital imaging, GIS, GUI, tables, multi-dimensions,
graphs, VR, 3D, animation
– Identify relationships and trends
• Data manipulation allows real time look at
performance data.

19. Visualization Spreadsheets
• The major end user tools for programming
decision support applications.
• Widely adopted as an easy-to-use and powerful
tool for free-form data manipulation.
• Sophisticated and flexible tool for collecting,
analyzing and summarizing data from multiple
sources.
• Power of Excel can be leveraged with
visualization including enhancing effectiveness,
focusing communications, facilitating
comprehension, and empowering collaboration.

20. Geographic Information System(GIS)
• Computerized system for managing and
manipulating data with digitized maps
– Geographically oriented
– Geographic spreadsheet for models
– Software allows web access to maps
– Used for modeling and simulations
– Sophisticated and affordable
– Provide framework to support the process of
decision making and designing alternative
strategies.

22. GIS And Decision Making
• Provide extremely useful information in decision
making.
• Graphical format easy to visualize the data.
• Countless applications to improve decision
making like:
1.The dispatch of emergency vehicle
2.Transit management
3.Facility site selection
4.Drought risk management
5. Wildlife management

23. Real-Time Business Intelligence
• Increasingly demand to access real-time,
unstructured, or remote data, integrated with
data warehouse.
• Real time data updates and access are critical
for an organization’s success and survivals
• Need frequent updating of data warehouse
• Real-time requirement change the view of
database, data warehouse, OLAP and data
mining tool

24. Automated Decision Support(ADS)
• Ruled-based system provide solutions to
repetitive managerial problems.
• Rapidly builds rules-based applications to
automate or guide decision making
• Injects predictive analytics into rules-based
applications
• Combines business rules, predictive models, and
optimization strategies
• Accelerates the uptake of learning from decision
criteria into strategy design, execution, and
refinement.

25. ADS Applications
• Product or service configuration
• Yield(price) optimization
• Routing or segmentation decisions
• Corporate and regulatory compliance
• Fraud detection
• Dynamic forecasting
• Operational control

26. Implementing ADS
Software companies provide the following
components to ADS:
• Rule engines
• Mathematical and statistical algorithms
• Industry-specific packages
• Enterprise systems
• Workflow applications

27. Competitive Intelligence
• Monitoring the activities of their competitors
to acquire competitive intelligence.
• Drives business performance by increasing
market knowledge, rising the quality of
strategic planning.
• Can be facilitated with technologies such as
optical character recognition, intelligent
agents and internet
• Internet: Important tool in supporting
competitive intelligence.

28. Web Analytics
• Application of BA to websites
• Includes e-commerce
• Tools and methods are highly visuals
Clickstream analysis:
 Analysis of data present inside the web environment
 Provide trailer of user’s activities and shows the user’s
browsing patterns.
 By analyzing data one can find the effectiveness of
promotions
 Can determine which products and ads attract the most
attention.