Business Intelligence in Changing Market Trends.
Business Intelligence (BI) refers to skills, processes, technologies, applications and practices used to support decision making.
3. Business Intelligence is a broad category of applications and
technologies for gathering, storing, analysing, and providing
access to data to help clients make better business
decisions.
Business Intelligence (BI) refers to skills, processes,
technologies, applications and practices used to support
decision making.
Business Intelligence is an environment in which business
users receive information that is reliable, secure, consistent,
understandable, easily manipulated and timely...facilitating
more informed decision making.
What is Business Intelligence?
Definition:
6. Benefits of Business
Intelligence
• Improve Management Processes
– planning, controlling, measuring and/or changing
resulting in increased revenues and reduced costs
• Improve Operational Processes
– fraud detection, order processing, purchasing..
resulting in increased revenues and reduced costs
• Predict the Future
7. BI Golden Rules
• Data Quality & Accuracy
• Data Consistency
• Data Timeliness
“Get the right information to the right people at the
right time”
8. Mobile
Cloud Computing
Social Media
Advanced Analytics
Major BI Trends
9. BI Yesterday vs Today vs Tomorrow
• “BI yesterday was like reading the newspaper”
• BI today is focus more on real-time events
and predicting tomorrow’s headlines
10. An electronic
telecommunications
device, often referred
to as a cellular phone
or cellphone. Mobile
phones connect to a
wireless
communications
network through radio
wave or satellite
transmissions.
Mobile
11. the practice of using a network of remote servers hosted on the
Internet to store, manage, and process data, rather than a local
server or a personal computer.
Cloud Computing
19. Business intelligence will be available to everyone in the
enterprise, and will be embedded in many business systems.
Although many technologies are available to implement this
vision, many challenges remain to make this vision a reality.
We have outlined key challenges like automated analytics,
semantics based information fusion and process
automation, and presented some examples which support
the feasibility of our vision.
Conclusion