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Business Intelligence
9
Business Intelligence !
Business
planning
Presented By
Nusrat Hriddy
Sumana Akter Tanjila
Nowrin Siddique
Nikita Sarker
Jannatul Ferdush
Introduction
Introduction
1
Definition
Business Intelligence comprises the strategies and technologies used by enterprises for the data analysis of Business Information.
2
History of BI
The earliest known use of the term
"Business Intelligence" is in Richard
Milar Devens in the ‘Cyclopaedia of
Commercial and Business Anecdotes’
From 1865. In a 1958 article, IBM
researcher Hans Peter Luhn used the
term business intelligence. In 1989,
Howard Dresner proposed "business
intelligence“. It was not until the late
1990s that this usage was widespread
3
Components of BI
- Multidimensional aggregation and allocation.
- Denormalization, tagging and standardization.
- Real time reporting with analytical alert.
- A method of interfacing with unstructured data sources.
- Group consolidation, budgeting and rolling forecasts
- Statistical inference and probabilistic simulation
- Key performance indicators optimization
- Version control and process management
- Open item management
Applications in Business Intelligence
Application
- Measurement
- Analytics
- Reporting/enterprise reporting
- Collaboration/collaboration platform.
- Knowledge management.
Business Intelligence portal
PORTAL
- Usable User: Usable User should easily find what they need in the BI tool.
- Content Rich: It should contain more functionality such as advice, help, support information and documentation.
- Clean: The portal should be designed so it is easily understandable.
- Current: The portal should be updated regularly.
- Interactive: The portal should be implemented in a way that makes it easy for the user to use its functionality and encourage them to use the portal.
- Value Oriented: It is important that the user has the feeling that the BI application is a valuable resource that is worth working on.
Business intelligence developers skills
SKILLS
- SQL and relational database
- SSRS/SSAS/SSIS, Report Builder
- Power BI
- Some coding skills like VB, C#, JavaScript etc.
User Satisfaction with the Business Intelligence Project Experience
sATISFACTIONS
Purpose of Business Intelligence
Purpose of Business Intelligence
The main purpose of Business Intelligence
in a business is to help corporate
executives, business managers and other
operational workers make better
and more informed business decisions.
Companies also use BI to cut costs,
identify new business opportunities, and
spot inefficient business processes
ripe for re-engineering.
Revenues of BI
Revenues of BI
Real Life Examples of BI
Real Life Examples of BI
Sisense: Sisense is a business intelligence platform that lets users join, analyze, and picture out information they require to make better and more intelligent business decisions.
Looker: Looker is a data platform with insights for every department. It’s a data-discovery app that provides an intuitive approach to data exploration.
Domo: Domo is one modern platform to run your entire business. It offers the widest data set and connector support among the tools we tested, and delivers a unique set of social collaboration features.
Cyfe: Cyfe is an all-in-one online business dashboard that helps users monitor and analyze data scattered across all their online services like Google Analytics and Sales force.
Latest trends of business intelligence
Latest trends of business intelligence
- The Integration of Data and Content.
- Operational Business Intelligence .
- Embedded and conversational Business Intelligence.
Benefits of Business Intelligence
Benefits of Business Intelligence
- Faster reporting, analysis or planning.
- More accurate reporting, analysis or planning.
- Better business decisions.
- Improved data quality.
- Improved employee satisfaction.
- Improved operational efficiency.
- Improved customer satisfaction.
- Increased competitive advantage.
- Reduced costs.
- Increased revenues.
- Saved headcount.
Disadvantages of Business Intelligence
Disadvantages of Business Intelligence
- Piling of Historical Data.
- Cost.
- Complexity.
- Muddling of commercial settings.
- Limited use.
- Time Consuming Implementation.