Duration

3.5 hours

Language of Delivery

Cantonese, English or Mandarin

Introduction

In today’s data-driven world, the ability to interpret and leverage data is a critical skill for professionals across all industries. This workshop provides a practical introduction to the fundamentals of data analytics and its applications in business decision-making.

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Course Details

Objectives
  • Understand the fundamental concepts of data analytics and its significance in business decision-making.
  • Become familiar with various data analytics tools and techniques.
  • Understand different ways of interpreting data and deriving actionable insights.
  • Apply data analytics concepts to real-world business scenarios.
Methodology

This workshop employs an engaging and hands-on approach that includes:

  • Case Study Analysis: Exploring successful data analytics applications in various industries.
  • Interactive Discussions: Defining data analytics and its importance in the business landscape.
  • Type Exploration: Differentiating Descriptive, Diagnostic, Predictive, and Prescriptive Analytics.
  • Tool & Technique Introduction: Discussing popular data analytics tools and data visualization best practices.
  • Hands-on Activity: Conducting a demonstration of a simple data analysis using Excel.
Key Takeaways
  • A clear understanding of the data analytics process, from data collection to visualization.
  • Familiarity with different types of data analytics and their applications in business.
  • A basic understanding of data analytics tools such as Excel, Tableau, R, and Python.
  • Practical experience with data visualization techniques and best practices.
  • Insights into the ethical considerations in data analytics.
Agenda
  • Introduction to Data Analytics
    • Definition of data analytics and its importance in the business landscape.
    • Overview of the data analytics process: data collection, processing, analysis, and visualization.
    • Discussion on the role of data analytics in strategic decision-making.
  • Types of Data Analytics
    • Descriptive Analytics: Understanding historical data and trends.
    • Diagnostic Analytics: Identifying causes of past outcomes.
    • Predictive Analytics: Forecasting future trends based on historical data.
    • Prescriptive Analytics: Recommending actions based on data analysis.
  • Data Analytics Tools and Techniques
    • Introduction to popular data analytics tools (e.g., Excel, Tableau, R, Python).
    • Overview of data visualization techniques and best practices.
    • Hands-on demonstration of a simple data analysis using Excel or a similar tool.
  • Applying Data Analytics in Business
    • Case studies showcasing successful data analytics applications in various industries.
    • Group discussion on how data analytics can address specific business challenges.
    • Introduction to ethical considerations in data analytics.
  • Wrap-Up and Q&A
Target Participants
  • Professionals who want to understand the power of data analytics in making informed decisions.
  • Managers and Team Leaders looking to leverage data for strategic planning.
  • Analysts seeking to expand their knowledge of data analytics tools and techniques.
  • Anyone interested in learning how to interpret data and derive actionable insights.