Certified Business Analytics Specialist (CBAS)
Introduction and Overview
Business Analytics is the emerging and fastest growing technology which every organization is embracing. As per Gartner’s prediction by 2014, 30% of analytic applications will use proactive, predictive and forecasting capabilities, and the software market for business intelligence, analytics and corporate performance management grew by 13.4% in 2010 to $10.5 billion and would continue to grow.
This specialized course covers the concept of Business Analytics and its strategic importance to any organization. The course deals with basic principles, concepts, techniques and tools used in business analytics landscape which includes data mining, data warehouse, data mart, business intelligence, business analytics. Also, this course covers different types of business analytics with real life use cases including text analytics and web analytics. Participants will get good picture of all these concepts and how they all are interconnected to each other in organizational context.
Through this course participants will acquire knowledge on how to use business analytics strategically in organization and to get the most benefit out of it. Also, they will learn to select appropriate type of business analytics based on organizational needs. Participants will actively step through the industry standard process for data mining and realize why an advanced degree in statistics, mathematics or computer science is no longer needed to implement predictive analytics. Live working sessions reveal real-world obstacles and breakthroughs from which to interpret, learn and apply.
As part of the course, participant will be given a case study and it would cover all the aspects of the Business Analytics, right from making a Data/Information Architecture for the case study to the cycle of CRISP-DM and finally converting all the requirements into predictive models using Rapid Miner tool.
Pre-requisites
Participants are preferred to have minimum 2 years of experience in software development, business domain or data/business analysis.
Course Outline
- Unit 1: Introduction to Business Analytics
- Unit 2: Types of Analytics
- Unit 3: Predictive Analytics
- Unit 4: Data Mining and Analytics
- Unit 5: Data Mining Tool – RapidMiner
- Unit 6: Data Preparation and Cleaning
- Unit 7: Data Mining Techniques
- Unit 8: Introduction to Predictive Modeling with Regression
- Unit 9: Introduction to Predictive Modeling with Rule Induction
- Unit 10: Introduction to Predictive Modeling with Decision Tree
- Unit 11: Introduction to Predictive Modeling with Neural Network
Who Should Attend
- Data Analyst - Statistics and Mining
- Data Analyst - Text Analytics
- Operations Research Analyst
- Senior Data Analyst- Statistics and Mining
Course Outcome
- Business analytics and its impact on enterprises
- Understand the role of predictive analytics and its importance in industry
- Learn to apply data loading, data preparation and cleaning techniques
- Learn to apply the data mining techniques using an open source tool
- Acquire knowledge on predictive modeling with regression, rule induction,
decision tree and neural network
Program Structure
This is a 3-day intensive training program with the following assessment components.
- Component 1. Written Examination (MCQ)
- Component 2. Project Work Component (PWC)
These components are individual based. Participants will need to obtain 70% in both the components in order to qualify for this certification. If the participant fails one of the components, they will not pass the course and have to re-take that particular failed component. If they fail both components, they will have to re-take the assessment.