Description
The participants will learn how to use OLAP tools for multidimensional reporting; pivoting tables; slicing and dicing of data; drill-downs and drill-ups; and other business analytic operations.
NICF – Business Intelligence Analytics
This course will introduce the participants to the essentials of business intelligence. It
is primarily targeted towards consumers of business intelligence (BI), such as business
managers, business executives, ?nancial analysts and market researchers, who are
interested in learning about BI concepts, process, tools and technologies and how to
leverage them in their organisations.
The participants will learn how to use OLAP tools for multidimensional reporting;
pivoting tables; slicing and dicing of data; drill-downs and drill-ups; and other business
analytic operations. They will also be exposed to popular data mining algorithms and learn
how to apply those algorithms for business applications such as sales forecasting, target
marketing, customer relationship management, market basket analysis and campaign
effectiveness.
They will receive hands-on training with BI tools for performing business analytics,
mining business data and measuring business performance. The course will include
several real-world cases of BI applications in domains such as marketing, ?nance and
travel.
For Whom
Data/Information Analysts,
Business Analysts, Marketing
Research Executives
Prerequisites
Knowledge of basic probability
and statistics, linear algebra and
programming is useful.
Duration
3 days
Subsidized Cost
S$963.00*
*Nett fee, after government funding
and inclusive of 7% GST.
Terms and conditions apply.
Venue
STMI@NUS
ICube, Level 3
21 Heng Mui Keng Terrace
Singapore 119613
[email protected]
Programme Bene?ts
• Understand the advantages of business intelligence
• Know various techniques for data analysis/business intelligence
• Be familiar with popular software for business intelligence
Dr. Atish Sinha is a Professor of MIS at the Lubar School of Business, University of Wisconsin-
Milwaukee, USA. He earned his Ph.D. in Arti?cial Intelligence from the Katz Graduate School of
Business, University of Pittsburgh, USA. His expertise is in the areas of object-oriented software
engineering, componentbased software development, business intelligence, data warehousing
and IT-enabled strategic management. He has taught a wide variety of MIS courses, and has
offered professional seminars in business intelligence, data warehousing, object-oriented
modelling and component-based development.
He has written book chapters on object-oriented modelling, object-oriented databases and
case-based reasoning.
Dr. Sinha has worked on several research grants and funded projects, in the areas of enterprise
strategy support system, statistical predictive modelling, data warehouse design, business
reengineering, expert agents and knowledgebased engineering design. His research has been
published in several wellknown scholarly journals in the ?eld, including Communications of
the ACM; Decision Support Systems; IEEE Transactions on Engineering Management; IEEE
Transactions on Software Engineering; IEEE Transactions on Systems, Man, And Cybernetics;
Information Systems Research; International Journal of Human-Computer Studies; and Journal
of Management Information Systems. Dr. Sinha has been the recipient of several awards,
including the Roger L. Fitzsimonds Distinguished Scholar Award, the Izzet Sahin Research
Award and the Teaching Excellence Award. He is a member of the ACM, AIS, and INFORMS
professional societies.
P
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STMI@NUS Business Intelligence Analytics
INTRODUCTION
• BI concepts and de?nitions
• Goals and objectives
• Evolution of BI
• Using BI for competitive advantage
• Critical success factor
BI PROCESS
• Drivers of BI
• Business issues and questions
• Information storage and retrieval
• Reporting
• Transforming data into actionable intelligence
ENABLING TOOLS AND TECHNOLOGIES
• OLAP
• Data warehousing
• Data mining
• Digital dashboards
DATA MINING ALGORITHMS
• Classi?cation and regression algorithms
• Supervised and unsupervised learning
• Decision tree, logistic regression, association rules and clustering
• Building and evaluating predictive data mining models
BI APPLICATIONS
• Business analytics
• Multidimensional reporting
• Forecasting
• Customer relationship management
• Target marketing
• Market basket analysis
• Lift analysis
• Credit scoring
• Performance measurement
BI CASE STUDIES
• Marketing
• Banking
• Travel
Lead Faculty
To request for an application form or more information please contact: Tel: +65 6516 2831 Email: [email protected]
doc_584505665.pdf
The participants will learn how to use OLAP tools for multidimensional reporting; pivoting tables; slicing and dicing of data; drill-downs and drill-ups; and other business analytic operations.
NICF – Business Intelligence Analytics
This course will introduce the participants to the essentials of business intelligence. It
is primarily targeted towards consumers of business intelligence (BI), such as business
managers, business executives, ?nancial analysts and market researchers, who are
interested in learning about BI concepts, process, tools and technologies and how to
leverage them in their organisations.
The participants will learn how to use OLAP tools for multidimensional reporting;
pivoting tables; slicing and dicing of data; drill-downs and drill-ups; and other business
analytic operations. They will also be exposed to popular data mining algorithms and learn
how to apply those algorithms for business applications such as sales forecasting, target
marketing, customer relationship management, market basket analysis and campaign
effectiveness.
They will receive hands-on training with BI tools for performing business analytics,
mining business data and measuring business performance. The course will include
several real-world cases of BI applications in domains such as marketing, ?nance and
travel.
For Whom
Data/Information Analysts,
Business Analysts, Marketing
Research Executives
Prerequisites
Knowledge of basic probability
and statistics, linear algebra and
programming is useful.
Duration
3 days
Subsidized Cost
S$963.00*
*Nett fee, after government funding
and inclusive of 7% GST.
Terms and conditions apply.
Venue
STMI@NUS
ICube, Level 3
21 Heng Mui Keng Terrace
Singapore 119613
[email protected]
Programme Bene?ts
• Understand the advantages of business intelligence
• Know various techniques for data analysis/business intelligence
• Be familiar with popular software for business intelligence
Dr. Atish Sinha is a Professor of MIS at the Lubar School of Business, University of Wisconsin-
Milwaukee, USA. He earned his Ph.D. in Arti?cial Intelligence from the Katz Graduate School of
Business, University of Pittsburgh, USA. His expertise is in the areas of object-oriented software
engineering, componentbased software development, business intelligence, data warehousing
and IT-enabled strategic management. He has taught a wide variety of MIS courses, and has
offered professional seminars in business intelligence, data warehousing, object-oriented
modelling and component-based development.
He has written book chapters on object-oriented modelling, object-oriented databases and
case-based reasoning.
Dr. Sinha has worked on several research grants and funded projects, in the areas of enterprise
strategy support system, statistical predictive modelling, data warehouse design, business
reengineering, expert agents and knowledgebased engineering design. His research has been
published in several wellknown scholarly journals in the ?eld, including Communications of
the ACM; Decision Support Systems; IEEE Transactions on Engineering Management; IEEE
Transactions on Software Engineering; IEEE Transactions on Systems, Man, And Cybernetics;
Information Systems Research; International Journal of Human-Computer Studies; and Journal
of Management Information Systems. Dr. Sinha has been the recipient of several awards,
including the Roger L. Fitzsimonds Distinguished Scholar Award, the Izzet Sahin Research
Award and the Teaching Excellence Award. He is a member of the ACM, AIS, and INFORMS
professional societies.
P
R
O
G
R
A
M
M
E
O
U
T
L
I
N
E
STMI@NUS Business Intelligence Analytics
INTRODUCTION
• BI concepts and de?nitions
• Goals and objectives
• Evolution of BI
• Using BI for competitive advantage
• Critical success factor
BI PROCESS
• Drivers of BI
• Business issues and questions
• Information storage and retrieval
• Reporting
• Transforming data into actionable intelligence
ENABLING TOOLS AND TECHNOLOGIES
• OLAP
• Data warehousing
• Data mining
• Digital dashboards
DATA MINING ALGORITHMS
• Classi?cation and regression algorithms
• Supervised and unsupervised learning
• Decision tree, logistic regression, association rules and clustering
• Building and evaluating predictive data mining models
BI APPLICATIONS
• Business analytics
• Multidimensional reporting
• Forecasting
• Customer relationship management
• Target marketing
• Market basket analysis
• Lift analysis
• Credit scoring
• Performance measurement
BI CASE STUDIES
• Marketing
• Banking
• Travel
Lead Faculty
To request for an application form or more information please contact: Tel: +65 6516 2831 Email: [email protected]
doc_584505665.pdf