Business Analysis

• Traditional Classroom: 5-day Duration
• Virtual Instructor-led: Ten 3-hour sessions

Unlock the power of data to drive smarter decisions and uncover hidden opportunities. Insights from Data is a hands-on training course designed for professionals who want to transform raw data into meaningful insights. Whether you’re in business, education, healthcare, or tech, this course equips you with the analytical mindset and practical tools to make data work for you.

Target Audience

Individuals who will benefit from this course include analysts, managers, decision makers, and anyone curious about data-driven thinking.

Learning Objectives

• Understand data basics, types, and formats.
• Become familiar with the fundamentals of data analysis and interpretation.
• Identify trends, patterns, and outliers in business data.
• Use a variety of techniques to visualize data effectively.
• Practice data analysis, visualization, and communicating data using real-world case studies across multiple industries.

Course Outline

Module 1: Introduction to Data and Data Analysis

• Data Types and Sources: Identify different types of data and where to find them.
  • Types of Data
  • Data Sources
• Business Questions: Learn to frame questions that can be answered with data.
  • SMART Statements
  • Voice of Customer/Business
  • Determining Customer Requirements
• Audience and Context Analysis: Understanding your audience’s needs and motivations.
  • Understanding the Audience
  • Stakeholder Mapping
  • Stakeholder Communication Strategy
  • Types of Presentations

Module 2: Data Collection and Preparation

• Data Gathering: Collect relevant data from various sources.
  • Data Collection Process
  • Data Collection Plan
  • Using AI for Research
• Data Transformation: Organize and transform variables to prepare data for analysis.
  • Essentials of Excel
  • Excel Formulas
  • Pivot Tables
  • Conditional Formatting

Module 3: Exploratory Data Analysis

• Comparative Analysis: Categorical vs. numerical variable relationships.
  • Data Shapes and Distributions
  • Central Tendency
  • Variability
• Statistical Methods: Apply statistical techniques to summarize data and identify patterns.
  • Descriptive Statistics
  • Sampling Techniques
  • Exploratory Data Analysis
• Pattern & Relationship Identification: Uncover trends, correlations, and other insights within the data.
  • Trend Analysis
  • Correlation and Association
  • Contextual Interpretation

Module 4: Data Modeling and Predictive Analytics

• Introduction to Modeling: Understand how to build models from data.
  • Define the Problem Clearly
  • Choose the Right Model Type
  • Interpret the Results
• Regression Analysis: Predict future outcomes based on relationships.
  • Define the Objective
  • Chose the Right Regression Type
  • Prediction and Interpretation
• Statistical Modeling: Applying statistical methods for analysis and interpretation.
  • Understand the Data
  • Choose the Appropriate Model
  • Interpret the Results

Module 5: Data Visualization and Communication

• Visualization Tools: Use tools like Excel for visual analysis.
  • Common Charts
  • Selecting the Appropriate Visuals
  • Using White Space and Avoiding Clutter
• Storytelling with Data: Create compelling narratives to communicate insights effectively.
  • Presentation Planning
  • Tell Stories with Data Tailored to Audience
  • Structuring Talking Points Using 5 Whys
• Actionable Insights: Translate findings into clear recommendations for stakeholders.
• Present Insights with Clarity and Evidence
• Presentation Principles

Summary and Next Steps

BAV332 Course Code