Uploaded by Sajee Sparrow

302-1593431187502-HND BI W1 Introduction to BI

advertisement
Unit 14 business intelligence
1 Introduction to business intelligence
1
What is Business Intelligence (BI) ?
▪ What is Business
▪ What is Intelligent
2
What is Business Intelligence (BI) ?
▪ the process for understanding the past & predicting the future
based on the data available and using a broad category of
technologies that use for
• gather, store, access & analyze data to help business users to
make better decisions
• analyzing business performance through data-driven insight
▪ broad category of applications, which include the results of
• decision support systems
• query and reporting
• online analytical processing (OLAP)
• statistical analysis, forecasting, and data mining
3
BI systems can be
▪ Mission-critical and integral to an enterprise's
operations or use occasionally to meet a special
requirement
▪ Enterprise-wide or local to one division, department, or
project
▪ Centrally initiated or driven by user demand
4
Why We need BI system
▪ to help the knowledge worker (executive, manager,
analyst) make faster & better decisions
▪ Organizations need various kinds of information to
support decisions and BI systems bring all required
information to one location
▪ Decision-making speed is an important success factor
in the information economy BI system optimize this
process and provides right information to analyze it
5
Operational Databases Transactions Vs
Analytical Database Transactions
6
What is Operational Database?
Operational systems are generally designed for easy
and efficient data storage. Because of that most of
operational systems have:
▪ Data storage limited to few terabytes
▪ Optimized for fast data storage
▪ Have good referential integrity
▪ Minimize data duplication
7
Characteristic of Operational Database
▪ High volume of transactions.
▪ Small processing per transaction.
▪ Frequent updating of data.
▪ Data is always current.
▪ Transaction driven.
▪ Predictable query types.
▪ Static structure.
▪ Content varies.
▪ High accuracy.
▪ High availability.
8
What is Analytical Database (Data
Warehouse)?
▪ Data store that stored historical data of organization.
Specifically designed to support and enhance decision
making process
9
Characteristic of Analytical Database
(Data Warehouse)
▪ Small volume of transactions.
▪ Often huge processing per transaction.
▪ Data output level is summary.
▪ Data routinely added to the system, but hardly changed.
▪ Analysis driven
▪ Flexible results structure
▪ Fairly accurate' better than no result
▪ Medium availability
▪ Requires different database tools
10
Why We Need Data Warehouse?
▪ Use your knowledge and intelligent to provide answer to
the question “why we should not use operational system
for decision making”.
11
Why We Need Data Warehouse
▪ Data Warehouses offer the flexibility, that needed to cope with the
Management demands.
▪ A major issue is that often there are many different OLTP(operational
databases ) systems and other data storage in organization, and The
Data Warehouse offers the opportunity to gather these operational
databases together into one system with a unified structure.
▪ Because data is stored in a simplified aggregated format it allow reports
to be written by staff who have a lesser computing background.
▪ Also analysis queries are consume a lot of resources. For the reason
that running analysis queries on operational system will reduce it
performance and brining down operational worker performance with it
12
Bibliography
▪ Boyer, J. (2010) Business Intelligence Strategy. MC Press (US).
▪ Marr, B. (2015) Big Data: Using Smart Big Data, Analytics and
Metrics to Make Better Decisions and Improve Performance. 1st
Ed. John Wiley & Sons, Ltd.
▪ Kaufmann,M. (2011)Data Mining Concepts and Techniques 3rd Ed.
Elsevier
▪ Edureka, 2017. Data Warehouse Tutorial For Beginners. [video]
Available at:
https://www.youtube.com/watch?v=J326LIUrZM8[Accessed 1 May
2020].
▪ Data Warehousing Module Outline. Sheffield Hallam University
13
Next Week
▪ Complete business intelligent frame work
▪ Operational Data Sources
▪ Extraction, Transformation, and Loading
(ETL) Tools
▪ Data Warehouse and Data Marts
▪ Data Presentation
▪ Data , Information ,Knowledge and Intelligent
14
Download