Get Ready for IIBA Certification in Business Data Analytics (IIBA-CBDA)

Description:

This course is designed to prepare participants for the IIBA Certification in Business Data Analytics (IIBA-CBDA) exam. It focuses on the essential practices, techniques, and frameworks needed to execute data-driven analysis and decision-making effectively. The course emphasizes hands-on exercises and real-world scenarios to align analytics initiatives with business goals.

Participants will explore the six core domains of the IIBA-CBDA exam and understand how to apply data analytics within a business context. By the end of the course, they will be well-prepared to pass the certification exam and excel in data-centric roles.

For Certification based Assistance and Mock quizzes please visit: https://certify360.ai/

Duration: 3 Days

Course Code: BDT418

Learning Objectives:

After completing this course, participants will be able to:

• Understand the IIBA-CBDA certification structure and exam requirements.
• Identify and define business problems suitable for data analytics solutions.
• Explore, analyze, and interpret data to uncover actionable insights.
• Apply data analytics techniques in decision-making and strategic planning.
• Communicate data-driven insights effectively to stakeholders.
• Align data analytics initiatives with organizational objectives.

• Understanding of business analysis practices and principles
• Basic knowledge of data analytics concepts
• Familiarity with the IIBA Business Analysis Body of Knowledge (BABOK®).

• Business Professionals, Data Analysts, Managers, Business Analyst, Software Developers, IT Managers, Professionals aiming to specialize in business data analytics and earn the IIBA-CBDA certification.

Course Outline:

• Introduction to Business Data Analytics and IIBA-CBDA Overview
  • Introduction to Business Data Analytics
    1. Role of data analytics in modern business
    2. Overview of data analytics lifecycle.
  • IIBA-CBDA Exam Overview
    1. Certification process and exam structure
    2. Overview of the six core exam domains.

• Identifying the Business Problem and Planning Analytics Work
  • Identifying Research Questions
    1. Framing business problems as analytical questions
    2. Aligning analytics initiatives with organizational goals.
  • Planning the Analytics Approach
    1. Defining scope, resources, and stakeholders
    2. Selecting appropriate analytics methods and tools.

• Data Analysis and Interpretation
  • Data Exploration and Preparation
    1. Data collection, cleansing, and transformation
    2. Techniques for ensuring data quality and consistency.
  • Performing Analytics and Interpreting Results
    1. Exploratory data analysis (EDA)
    2. Statistical and predictive modelling basics

• Deriving meaningful insights from data.

• Presenting Insights and Driving Decisions
  • Communicating Results to Stakeholders
    1. Designing clear and impactful visualizations
    2. Best practices for storytelling with data.
  • Using Analytics to Influence Business Decisions
    1. Translating insights into actionable recommendations
    2. Ensuring alignment with business strategy.

• Certification Preparation
  • Review of Key Concepts
    1. Overview of the six IIBA-CBDA domains
    2. Common mistakes and how to avoid them.

• Key Topics and Objective for Certification exams.

• Certification Tips
  1. Time management and preparation strategies.
  2. Focus areas for success.

• Simulated exams for hands-on experience.

• Q&A Session
  1. Practice and Mock Tests

Training material provided: Yes (Digital format, including detailed notes, domain-specific study guides, and practice questions).

Any Additional Information

Participants will receive instructions to access mock exams, sample datasets, and analytics tools. A comprehensive study plan and access to reference materials aligned with the IIBA-CBDA framework will also be provided.

This course ensures participants are well-prepared for the certification exam and gain the practical skills necessary to lead data-driven business analysis initiatives.