IIBA-CBDA.AQ1
Introduction to Business Data Analytics (CBDA)
Data is the new King! Learn how to perform data analysis that affects crucial business decisions.
- 8 Interactive Lessons and 63 topics mapped to the official exam objectives
- 136 Practice Test Questions
Beginner Self-paced · 1 year access 4.2/5 (349 Reviews)
01 / Skills you'll get
What you will be able to do
- Techniques for data cleaning and preparation (handling missing values, outliers, and more)
- Summarize and understand data characteristics for Exploratory Data Analysis (EDA)
- Conversion of raw data into a suitable format for analysis
- Using statistical methods to analyze data, including descriptive statistics, hypothesis testing, and correlation analysis
- Using visualization techniques to create various types of charts and graphs to communicate data insights
- Using different visualization methods to create stories that convey complex information in a clear and understandable manner
- Create conceptual, logical, and physical data models to represent the structure and relationships of data elements
- Ability to apply analytical techniques such as decision trees and regression analysis
- Find optimal solutions to complex problems, such as resource allocation or scheduling with mathematical techniques
- Implement policies and procedures to ensure data quality, security, and compliance with regulations
- Awareness of data warehousing and data marts to perform centralized data storage and analysis
- Execute ETL (Extract, Transfer, Load) process for extracting data from various sources, transforming it into a suitable format, and loading it
- Apply data mining techniques and algorithms to find patterns and trends in large datasets
- Using Machine Learning (ML) Algorithms to build predictive learning models
Target Career Roles
- Business Data Analyst
02 / Lessons & labs
See exactly what you will learn and practice
Lessons
8 Interactive Lessons · 63 topics01 Introduction to Business Data Analytics 5 topics +
- What is Business Data Analytics?
- The Business Data Analytics Cycle
- Business Data Analytics Objectives
- Business Analysis and Business Data Analytics
- Applications of Data Analytics
02 Identify the Research Questions 7 topics +
- Define Business Problem or Opportunity
- Identify and Understand the Stakeholders
- Assess Current State
- Define Future State
- Formulate Research Questions
- Plan Business Data Analytics Approach
- Techniques
03 Source Data 6 topics +
- Plan Data Collection
- Determine the Data Sets
- Collect Data
- Validate Data
- Techniques
- A Case Study for Source Data
04 Analyze Data 7 topics +
- Develop Data Analysis Plan
- Prepare Data
- Explore Data
- Perform Data Analysis
- Assess the Analytics and System Approach Taken
- Techniques
- A Case Study for Analyze Data
05 Interpret and Report Results 7 topics +
- Validate Understanding of Stakeholders
- Plan Stakeholder Communication
- Determine Communication Needs of Stakeholders
- Derive Insights from Data
- Document and Communicate Findings from Completed Analysis
- Techniques
- A Case Study for Interpret and Report Results
06 Use Results to Influence Business Decision-Making 5 topics +
- Recommend Actions
- Develop Implementation Plan
- Manage Change
- Techniques
- A Case Study for Use Results to Influence Business Decision-Making
07 Guide Organizational-Level Strategy for Business Data Analytics 6 topics +
- Organizational Strategy
- Talent Strategy
- Data Strategy
- Techniques
- Competencies
- A Case Study for Guide Organization-Level Strategy for Business Data Analytics
08 Appendix A: Techniques 20 topics +
- Business Simulation
- Business Visualizations
- Concept Modelling
- Data Dictionary
- Data Flow Diagrams
- Data Mapping
- Data Storytelling
- Decision Modelling and Analysis
- Descriptive and Inferential Statistics
- Extract, Transform, and Load (ETL)
- Exploratory Data Analysis
- Hypothesis Formulation and Testing
- Interface Analysis
- Optimization
- Problem Shaping and Reframing
- Stakeholder List, Map, or Personas
- Survey and Questionnaire
- Technical Visualizations
- The Big Idea
- 3-Minute Story
03 / Exam details
Introduction to Business Data Analytics (CBDA) Details
Get certified by the leading authority in business analysis, IIBA with the course Introduction to Business Data Analytics (CBDA). The course is for business analysts who want to improve their business decision-making by enabling new products and services and creating new markets, disrupting existing markets and unseating secure businesses, driving increased efficiency (for example, for retailers to enable them to tailor products for customers), identifying growth opportunities, driving innovation, operating more efficiently, and improving risk management.
Ready to take the exam?
Add your official IIBA-CBDA.AQ1 exam voucher to your order.
Official Voucher · Fast delivery · Retake bundle available04 / FAQs
Questions before you start
What is the Business Data Analytics (IIBA - CBDA) certification about? +
Are there any prerequisites for this certification exam? +
What important topics are covered in this Business Data Analytics course? +
What are the career benefits of doing this CBDA certification? +
How much salary does a CBDA Certified Data Analyst earn? +
What is the CBDA Business Analyst certification exam fee? +
What is the exam format?+
What is the CBDA exam duration?+
Is this data analytics course ideal for business professionals?+
Yes, it is an ideal course for job seekers as well as business professionals wanting to learn data analytics and make data-driven decisions.
What is the exam registration fee?+
How many questions are asked in the exam?+
What is the duration of the exam?+
What is the passing score?+
(on a scale of IIBA does not provide scores or scoring percentages for any of the certification exams.-IIBA does not provide scores or scoring percentages for any of the certification exams.)
What is the exam's retake policy?+
What is the validity of the certification?+
Where can I find more information about this exam?+
Gain Job-Relevant Data Analytics Skills
Learn how to Analyze Data for evidence based decision-making.