The Certified Business Data Analyst Course is designed to equip participants with the essential skills and knowledge required to excel in the field of data analysis. In an era where data drives business decisions, the ability to analyze and interpret data effectively is crucial for success.

This comprehensive course covers the fundamentals of data analysis, statistical techniques, data visualization, and the use of analytical tools such as Excel and SQL. Participants will engage in hands-on exercises, real-world case studies, and a capstone project that allows them to apply their skills in a practical setting. By the end of the course, participants will be well-prepared to take the certification exam and contribute effectively to their organizations through data-driven decision-making.

Course Objectives

• Understand the key concepts and techniques in business data analysis.
• Apply statistical analysis methods to interpret data and draw insights.
• Use Excel and SQL for data manipulation and analysis.
• Create compelling data visualizations and reports to communicate findings.
• Develop practical skills through case studies and a capstone project.

Target Group

• Aspiring Business Data Analysts looking to build a career in data analysis.
• Current Analysts and Professionals seeking to enhance their data analysis skills and obtain certification.
• Managers and Team Leaders who wish to leverage data analysis for better decision-making.
• Students and Graduates in business, finance, or related fields interested in data-driven careers.

This course is ideal for anyone looking to gain certification in business data analysis and enhance their analytical skills to drive business success.

• Introduction to Business Data Analysis

  • Understanding the role and responsibilities of a business data analyst
  • Overview of data analysis in the business context
  • Importance of data-driven decision-making

• Fundamentals of Data Analysis

  • Types of data: qualitative vs. quantitative
  • Data collection methods and sources
  • Data cleaning and preparation techniques

• Statistical Analysis for Business

  • Descriptive statistics: mean, median, mode, standard deviation
  • Inferential statistics: hypothesis testing, confidence intervals
  • Using statistical software for analysis (Excel, R, or Python)

• Data Visualization Techniques

  • Importance of data visualization in storytelling
  • Tools for data visualization (Tableau, Power BI)
  • Best practices for creating effective charts and dashboards

• Using Excel for Data Analysis

  • Advanced Excel functions and formulas
  • Pivot tables and data modeling
  • Analyzing data with Excel: case studies and practical exercises

• SQL for Data Management

  • Introduction to SQL and database management
  • Writing SQL queries to extract and manipulate data
  • Understanding database design and relationships

• Business Intelligence and Reporting

  • Concepts of business intelligence (BI) and its importance
  • Creating meaningful reports and dashboards
  • Presenting data insights to stakeholders effectively

• Capstone Project

  • Real-world case study analysis using learned skills
  • Participants will analyze a dataset, draw conclusions, and present findings
  • Peer review and feedback session