Business Data Analytics Bootcamp

Business Analytics Bootcamp: Data Skills for Professionals

Week 1: Introduction to Business Analytics

• Understanding Business Analytics and Its Importance: Explore the role of analytics in decision-making, competitive advantage, and operational efficiency. Learn how data-driven insights transform business strategies.
• Types of Analytics:
  • Descriptive Analytics: Summarize historical data to understand what has happened.
  • Predictive Analytics: Use statistical models and forecasts to determine future outcomes.
  • Prescriptive Analytics: Recommend actions based on data analysis to optimize outcomes.

Week 2: Data Collection and Preparation

• Types and Sources of Data: Examine structured vs. unstructured data, internal vs. external data sources such as CRM systems, social media, surveys, and databases.
• Data Cleaning and Basics of Excel: Learn techniques for handling missing values, duplicates, and inconsistencies. Introduction to Excel tools for data management, including sorting, filtering, and basic formulas.

Week 3: Excel for Business Analytics

• Essential Excel Functions and Formulas: Master functions like SUM, AVERAGE, VLOOKUP, INDEX, MATCH, and conditional formulas for analysis.
• Data Sorting, Filtering, and Pivot Tables: Organize large datasets efficiently, create Pivot Tables to summarize data, and generate quick insights.

Week 4: Introduction to SQL for Analytics

• Basic SQL Queries: Write simple queries using SELECT, FROM, WHERE, and ORDER BY to retrieve and filter data.
• Joining Tables: Combine data from multiple tables using JOIN operations to analyze complex datasets.

Week 5: Data Visualization with Power BI

• Creating Charts and Dashboards: Design visual representations of data to communicate insights effectively with bar charts, line graphs, and gauges.
• Using Filters and Interactive Visuals: Enhance dashboards with slicers and filters for dynamic analysis and storytelling.

Week 6: Basic Statistics for Business Analytics

• Measures of Central Tendency and Dispersion: Understand mean, median, mode, variance, and standard deviation to describe data distributions.
• Correlation and Basic Hypothesis Testing: Assess relationships between variables and test assumptions to validate findings.

Week 7: Case Studies and Real-World Applications

• Applying Analytics to Sales, Customer Segmentation, Finance, and Operations: Analyze real datasets to uncover trends, segment customers, forecast sales, and optimize operational processes.

Week 8: Communicating Analytics Results

• Reporting and Storytelling with Data: Develop compelling reports and presentations that highlight key insights and recommendations.
• Ethical Considerations and Clear Presentations: Discuss data privacy, ethical use of analytics, and best practices for transparent and effective communication.