Data Analysis Fundamentals

This DIXONTECH course introduces the essential principles and techniques of data analysis for professionals across industries. Participants learn to collect, clean, analyze, and visualize data effectively to support better decisionmaking. The course combines theoretical foundations with practical exercises using industrystandard tools, ensuring learners build a solid analytical mindset and data literacy for professional growth.

TRAINING TOPICS:

• Introduction to Data Analysis Concepts

• Data Collection and Preparation

• Descriptive and Exploratory Analysis

• Data Visualization and Communication

• Applying Data Insights in Business Contexts

BY THE END OF THIS TRAINING COURSE, DELEGATES WILL BE ABLE TO:

By the end of this DIXONTECH training, participants will:

• Understand the data analysis process from start to end

• Prepare and clean data for accurate analysis

• Use spreadsheets and analytical tools effectively

• Interpret and summarize key data findings

• Create visual reports and dashboards

• Apply insights to real business problems

• Communicate analytical results with confidence

TRAINING IS TAILORED TO:

This course is designed for:

• Business professionals and analysts

• Entrylevel data practitioners

• Project and operations managers

• HR and marketing specialists

• Financial and administrative officers

• Students and researchers handling data

• Anyone aiming to improve datadriven decisions

TRAINING METHODOLOGY:

DIXONTECH employs an engaging and practical training style, combining instructorled sessions, guided exercises, and live demonstrations. Participants work on casebased examples, using realworld datasets to apply the learned concepts. The methodology ensures learners can directly apply data analysis principles within their workplace environments.

DAY 1: Introduction to Data Analysis Concepts

• Understanding what data analysis means

• Role and value of data in organizations

• The data analysis life cycle overview

• Quantitative versus qualitative data types

• Identifying objectives for data projects

• Key analytical terminologies explained

• Overview of analytical tools and software

DAY 2: Data Collection and Preparation

• Sources and types of business data

• Data entry, validation, and organization

• Cleaning data and removing duplicates

• Handling missing and inaccurate values

• Structuring datasets for analysis

• Importing data into Excel or Power BI

• Documenting and storing data securely

DAY 3: Descriptive and Exploratory Analysis

• Introduction to descriptive statistics

• Measures of central tendency and variability

• Identifying data patterns and trends

• Building frequency tables and summaries

• Exploring correlations and relationships

• Practical exercises using datasets

• Interpreting results in business context

DAY 4: Data Visualization and Communication

• Principles of visual storytelling with data

• Choosing appropriate chart types

• Creating dashboards in Excel or Power BI

• Highlighting insights with color and design

• Avoiding misrepresentation of data

• Communicating results to nontechnical audiences

• Best practices in data presentation

DAY 5: Applying Data Insights in Business Contexts

• Translating analytics into decisionmaking

• Datadriven problem solving techniques

• Using KPIs to track business performance

• Scenariobased decision models

• Reporting insights to management teams

• Developing analytical thinking habits

• Final project and feedback session