Certification in Business Data Analytics (IIBA-CBDA®) Training
Business data analytics is the discipline by which a specific set of techniques, competencies and practices are applied to perform the continuous exploration and investigation of business data. It focuses on effective business decision-making through data analysis, enabling organizations to make more informed decisions. This two-day session will prepare you for the Certification in Business Data Analytics (IIBA®-CBDA) exam and help you make the most of your post-class study time. This course was designed to help candidates focus on the critical areas to study and to provide insights into the exam. Upon passing the exam, you will earn the Certification in Business Data Analytics (IIBA®- CBDA) awarded by the International Institute of Business Analysis™ (IIBA®).
Study indicates that by 2022, 85 percent of companies will have adopted big data analytics. Want to make sure that you are ready for the opportunity with the Certification in Business Data Analyst™ (CBDA)? This comprehensive workshop will prepare you for the CBDA exam and help you make the most of the limited study time you have.
The Guide to Business Data Analytics provides a foundational understanding of business data analytics concepts and includes how to develop a framework; key techniques and application; how to identify, communicate and integrate results; and more. This guide acts as a reference for the practice of business data analytics and is a companion resource for the Certification in Business Data Analytics. The course not only covers all aspects of this guide, but goes beyond it to explain application using Microsoft Analytics tools.
What Will You Learn?
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Understand and learn the established business analysis practices in data analytics initiatives that are outlined in the Guide to Business Data Analytics
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Gain competence in the 6 Business Data Analytics Domains (Identify Research Questions, Source Data, Analyze Data, Interpret and Report Results, Use Results to Influence Business Decision Making, Guide Company-Level Strategy for Business Analytics) and the best practices outlined in the Guide to Business Data Analytics
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Master the terminologies used in the Guide to Business Data Analytics
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Acquire sound understanding of the role, competencies and skillsets required to become an effective and result-oriented business analyst in analytics initiatives
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Learn how to manage stakeholders effectively
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Gain practical insights into the principles and practices of business data analytics
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Learn how to identify and apply various tools, techniques and competencies in analytics initiatives for creating better business outcomes through evidence-driven business decisions
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Learn practical aspect of data analytics through Microsoft toolsets.
Who Should Attend This Course?
This certification is suitable for professionals with mid-level experience, possessing the skills to effectively perform business data analytics initiatives and can demonstrate experience in:
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Translating business problems into questions that analytics can answer
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Using analytics results to identify viable options
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Explaining technical results to non-technical stakeholders
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Visualizing data and translate results via data storytelling
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Building and demonstrating empathy for the customer
Training Options
Find a training that fits your needs and schedule.
Corporate Training
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Perfectly blended self-paced eLearning, instructor-led private training and refrence material.
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Customized to suit your needs
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Flexible enough to use your templates
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Enterprise grade Learning Management System
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Enterprise dashboards for individuals and teams
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24x7 learner assistance and support
WHAT PEOPLE SAY
Surya Sagar, HSBC
I could relate to all my work done at office. I will be able to apply the learning on my job. Thank you for such a wonderful training!
Rajeev Ponmanissery, Emirates
Excellent training! All areas were covered in great details and the instructor was able to clarify all doubts with real life examples.
Vijay Kumar Menedhal, Bosch
It gave a clear direction as to how we can study for the exams and how we can apply the learnings on our project.
Earn CBDA in 4 Steps & 6 Weeks
01
Attend a training class.
The comprehensive training makes you understand entire domain of data analytics.
Through a lively case study, you learn how to analyse data and answer the exam questions.
02
CBDA application
Get help from our experts, use our tool and get your application approved effortlessly in one shot.
03
Study with our material.
Use our concise yet comprehensive Study Material for just 30 minutes a day and you will be ready to crack the exam in 6 weeks!
04
Assess your preparation.
Use our preparation resources to assess your preparedness, focus on weaker areas pass with confidence.
CBDA Eligibility, Fee & Exam
Eligibility
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None
Exam Fee (US$)
About the Exam
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Exam provider: PCI
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Mode of exam: Online, remotely proctored with laptopn camera and microphone
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Scheduling: online
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CBAP Application: $125
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CBAP Exam: $575 (non-IIBA members) : $450 (IIBA members)
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Exam rewrite: $400 (non-IIBA members) : $325 (IIBA members)
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Membership: Fee vary based on your country. Visit iiba.org for the information.
Contents
1. FUNDAMENTALS OF BUSINESS DATA ANALYTICS
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Introduction to Business Data Analytics (BDA)
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Relationship between Business Analysis and Business Data Analytics
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Understanding terminology:
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BDA, Data Science, AI, Machine Learning, Big Data etc.
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Supervised and Unsupervised Machine Learning
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Types of Business Data Analytics methods
2. BUSINESS DATA ANALYTICS DOMAINS
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Understanding the Business Data Analytics Life Cycle
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Identify the Research Questions
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Defining the business problem(s)
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Articulating the business problem as an analytical problem
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Defining success KPIs
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Building hypothesis, and framing the research question(s)
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Type I and Type II errors
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Using DMN (Decision Model and Notation) to build a Decision
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Requirements Models
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Source Data
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Types of data
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Defining data requirements
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Developing a Data Collection Plan
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Identifying data sources
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Collecting data
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Understanding data modeling
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Analyze Data
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Machine Learning Fundamentals
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Supervised Learning Algorithms
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Unsupervised Learning Algorithms
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The Concept of “Overfitting”
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Bias Error and Variance Error
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Addressing “overfitting”
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Data Preparation: Pre-processing data
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Formatting data
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Cleaning data
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Sampling data
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Data Preparation: Transforming data (Feature Engineering)
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Testing and selecting algorithms
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Building models
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Evaluating models
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Interpret and Report Results
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Understanding the Stakeholder Engagement Life Cycle
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Data Visualization vs Data Storytelling
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Understanding commonly used charts and plots
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Understanding Data Storytelling
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Use Results to Influence Business Decision-Making
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Making recommendations
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Developing the Change Implementation Plan
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Performing business validation of the model
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Deploying the analytics solution
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Managing the business change
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Manage the model life cycle
3. INSTITUTIONALIZING BUSINESS DATA ANALYTICS
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Business Data Analytics challenges
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Building a Data Strategy
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Understanding techniques to build a Data Strategy
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Understanding Data Management