DATA AND PREDICTION ANALYSIS

INTRODUCTION FOR DATA AND PREDICTION ANALYSIS

This two-day training program is designed to equip participants with the skills necessary to analyze data effectively and make informed predictions using Excel and Power BI. The course covers fundamental data analysis techniques, predictive modeling, and visualization methods. Participants will gain hands-on experience working with real-world datasets, enabling them to apply their learning to practical business scenarios. By the end of the training, attendees will be able to manipulate data efficiently, create insightful reports, and use predictive analytics to support decision-making processes.

LEARNING OBJECTIVES

Here are the learning objectives for the two days training program; after completing this program, participants will be able to:

• Understand core concepts of data analysis and prediction.
• Gain hands-on experience with Excel’s data analysis and forecasting features.
• Learn to build interactive dashboards and reports in Power BI.
• Develop the skills to interpret data insights for predictive decision-making

LANGUAGE

• English
• Bahasa Malaysia

WHO SHOULD ATTEND

This program is ideal for professionals who need to analyze data, generate insights, and support strategic decision-making using Excel and Power BI. The training is suitable for:

• Senior Management Executives seeking to leverage data for business forecasting and planning.
• Data Analysts and Business Analysts aiming to enhance their predictive analytics skills.
• Department Heads and Team Leaders who need to interpret data for performance and operational improvement.
• Finance, Marketing, and Operations Executives involved in reporting and strategic planning.
• IT Professionals interested in integrating data analysis into business intelligence systems.
• Anyone responsible for making data-driven decisions and reporting in their organization.

COURSE CONTENTS

DAY 1

1) Data Preparation & Exploration

1. 1. Introduction & Overview
      1. Course introduction, objectives, and expected outcomes.
      2. Overview of data analysis and predictive analytics.
   2. Data Preparation in Excel
      1. Data types, formatting, and cleaning techniques.
      2. Importing and organizing data from various sources.
   3. Exploratory Data Analysis
      1. Using pivot tables and charts for exploratory data analysis.
      2. Introduction to descriptive statistics and summary metrics

2) Forecasting & Predictive methodolgy

1. 1. Time Series Forecasting
      1. Using Excel’s forecast functions and trendlines.
      2. Moving averages and exponential smoothing.
   2. Regression Analysis
      1. Linear regression for trend prediction.
      2. Scenario analysis and what-if analysis.
      3. Hands-on Exercise
         • Practical implementation of forecasting techniques.

3) Advanced Data Analysis Tools

1. 1. Data Analysis Add-ins
      1. Introduction to Excel’s Analysis ToolPak.
      2. Solver for optimization problems.
   2. Data Visualization Best Practices
      1. Creating meaningful charts and graphs.
      2. Formatting and enhancing readability.
      3. Analyzing a sample dataset and interpreting trends.

4) Application of regression and forcasting in data sets

1. 1. Reviewing a real-world business dataset.
   2. Applying forecasting techniques for prediction.
   3. Case Study : Participants work on a small project based on given data.

5) Power BI Essentials

1. 1. Introduction to Power BI
      1. Overview of Power BI interface, components, and ecosystem.
      2. Understanding the role of interactive dashboards
   2. Connecting and Transforming Data
      1. Importing data from Excel and other sources.
      2. Data transformation using Power Query (cleaning, shaping data).

6) Data Modeling & DAX Basics

1. 1. Building Relationships Between Tables
      1. Understanding star schema and relationships.
      2. Creating calculated columns and measures.
   2. Introduction to DAX (Data Analysis Expressions)
      1. Writing simple DAX formulas for calculations.
      2. Aggregation, filters, and time intelligence functions.

7) Building Interactive Reports

1. 1. Creating Visualizations
      1. Designing bar charts, line charts, and maps.
      2. Implementing slicers and filters.
   2. Best Practices for Dashboard Design
      1. Layout planning for user-friendly dashboards.
      2. Enhancing visuals for better storytelling.
      3. Building an interactive report using a sample dataset

8) Predictive Analytics

1. 1. Integrating Predictive Analytics
      1. Incorporating forecasting models into Power BI.
      2. Using AI visuals and custom analytics tools.
   2. Capstone Project
      1. Participants create a mini project using provided data.
      2. Building a dashboard that integrates predictive elements.

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