Course Description
Data Analysis focuses on the knowledge, skills and tools required to collect, clean, analyse, visualise and interpret data to support informed decision-making.
The course provides participants with practical skills in data preparation, exploratory analysis, statistical concepts, data visualisation, reporting and business intelligence using industry-relevant tools such as Microsoft Excel, SQL, Power BI, Python and Tableau.
Participants learn how to transform raw data into meaningful insights, identify trends and patterns, create effective dashboards and reports, and communicate data-driven findings clearly to support business and organisational decisions.
Course Overview
Data Analysis provides participants with the practical knowledge and technical skills required to work with data and turn information into meaningful insights.
The Data Analysis training at Renzy Academy takes participants through the key stages of the data analysis process, including data collection, data cleaning, data transformation, exploratory analysis, visualisation, interpretation and reporting.
Participants will develop practical skills using widely used data analysis and business intelligence tools, including Microsoft Excel, SQL, Power BI, Python and Tableau.
The programme covers spreadsheet analysis, database querying, data cleaning, descriptive statistics, exploratory data analysis, data visualisation, dashboard development and data storytelling.
Participants will work with practical datasets and business scenarios to develop the ability to identify patterns, analyse trends, generate insights and communicate findings effectively.
Through hands-on exercises, case studies and a practical data analysis project, participants will build a portfolio of projects that demonstrates their ability to apply data analysis techniques to real-world problems.
The programme is suitable for beginners, graduates, professionals seeking to develop data skills and individuals transitioning into Data Analysis and related technology careers.
Who This Course Is For
The Data Analysis programme is designed for individuals and professionals who want to develop practical skills for working with data, generating insights and supporting data-driven decision-making.
It is suitable for
- Aspiring Data Analysts
- Graduates and career starters
- Professionals transitioning into Data Analysis
- Business Analysts
- Project Managers
- Product Managers
- Operations Professionals
- Finance and Accounting Professionals
- Marketing and Sales Professionals
- Business Owners and Entrepreneurs
- Researchers and Academics
- Administrative Professionals
- IT and Technology Professionals
- Professionals who work with spreadsheets, databases or business reports
- Anyone seeking practical Data Analysis skills
Key Learner Outcomes
By the end of the programme, participants should be able to
- Understand the fundamentals and principles of Data Analysis.
- Collect, organise and prepare data for analysis.
- Clean and transform datasets using appropriate techniques.
- Analyse data using Excel, SQL and Python.
- Create meaningful visualisations and interactive dashboards using Power BI and Tableau.
- Apply basic statistical techniques to understand data.
- Identify trends, patterns and relationships within datasets.
- Generate meaningful insights from data.
- Communicate findings through effective reports and data storytelling.
- Apply Data Analysis techniques to real-world business and organisational problems.
- Develop a portfolio of practical data analysis projects.
Learning Objectives
By the end of the course, participants will be able to
- Explain fundamental Data Analysis concepts and processes and understand how data supports informed decision-making.
- Collect, clean and prepare data using appropriate techniques and tools.
- Analyse and interpret datasets using Excel, SQL and Python to identify meaningful patterns and insights.
- Apply basic statistical techniques to summarise and understand data.
- Create effective data visualisations and interactive dashboards using Power BI and Tableau.
- Communicate data-driven insights effectively through reports, presentations and data storytelling.
- Apply Data Analysis tools and techniques to real-world problems and develop practical projects that demonstrate data analysis skills.
Course Modules
Module 1: 1. Introduction to Data Analysis
- Understanding Data Analysis
- Types of data
- Structured and unstructured data
- Data Analysis lifecycle
- Data sources
- Data quality
- Data-driven decision-making
- Role of a Data Analyst
Module 2: 2. Microsoft Excel for Data Analysis
- Excel fundamentals
- Data organisation
- Formulas and functions
- Logical and lookup functions
- Data validation
- Sorting and filtering
- Pivot Tables
- Pivot Charts
- Conditional formatting
- Excel dashboards
Module 3: 3. Data Cleaning and Preparation
- Understanding data quality
- Identifying errors and inconsistencies
- Handling missing data
- Removing duplicates
- Data formatting
- Data transformation
- Data validation
- Preparing datasets for analysis
Module 4: 4. Statistics for Data Analysis
- Descriptive statistics
- Mean, median and mode
- Range and standard deviation
- Percentages and ratios
- Distribution
- Correlation
- Sampling fundamentals
- Interpreting statistical results
Module 5: 5. SQL for Data Analysis
- Introduction to databases
- Relational databases
- Tables and relationships
- SQL syntax
- SELECT statements
- Filtering and sorting
- Aggregations
- GROUP BY and HAVING
- JOINs
- Subqueries
- Practical database analysis
Module 6: 6. Python for Data Analysis
- Introduction to Python
- Python fundamentals
- Variables and data types
- Lists, dictionaries and functions
- Introduction to Pandas
- Importing datasets
- Data cleaning with Python
- Data transformation
- Exploratory Data Analysis
- Basic data visualisation
Module 7: 7. Exploratory Data Analysis
- Understanding exploratory analysis
- Identifying trends and patterns
- Detecting outliers
- Analysing relationships
- Asking analytical questions
- Exploring datasets
- Drawing initial insights
- Communicating analytical findings
Module 8: 8. Data Visualisation
- Principles of effective data visualisation
- Selecting appropriate charts
- Bar charts
- Line charts
- Pie charts
- Scatter plots
- Data storytelling
- Visual design principles
- Presenting insights clearly
Module 9: 9. Power BI for Data Analysis
- Introduction to Power BI
- Importing data
- Power Query
- Data transformation
- Data modelling
- Relationships
- Measures and calculated columns
- DAX fundamentals
- Creating visualisations
- Interactive dashboards
- Publishing and sharing reports
Module 10: 10. Tableau for Data Visualisation
- Introduction to Tableau
- Connecting to data
- Data preparation
- Creating worksheets
- Charts and visualisations
- Filters and calculations
- Dashboards
- Interactive reports
- Data storytelling with Tableau
Module 11: 11. Data Reporting and Storytelling
- Turning analysis into insights
- Structuring analytical reports
- Identifying key findings
- Presenting recommendations
- Data storytelling
- Communicating with non-technical audiences
- Dashboard presentation
- Executive reporting
Module 12: 12. Data Analysis in Business Decision-Making
- Using data to solve business problems
- Business performance analysis
- Sales analysis
- Customer analysis
- Financial analysis
- Marketing analysis
- Operational analysis
- KPI analysis
- Data-driven recommendations
Practical Project
Participants will work with a realistic dataset and apply the Data Analysis concepts, tools and techniques covered throughout the programme.
Working individually or in teams, participants will take a dataset through the complete analysis process, from data preparation to analysis, visualisation, reporting and presentation.
The practical project will involve
- Defining a business or analytical problem
- Identifying the data required
- Collecting or sourcing a dataset
- Cleaning and preparing the data
- Performing exploratory data analysis
- Applying appropriate statistical techniques
- Using Excel and SQL to analyse data
- Using Python for data analysis where applicable
- Identifying trends, patterns and relationships
- Creating meaningful data visualisations
- Developing an interactive Power BI or Tableau dashboard
- Interpreting analytical findings
- Developing data-driven recommendations
- Preparing a data analysis report
- Presenting findings to an audience
- Practical Deliverables
- By the end of the project, participants will have developed a portfolio of practical Data Analysis deliverables, which may include:
- Data Collection Plan
- Cleaned Dataset
- Excel Analysis
- SQL Queries and Analysis
- Python Analysis Notebook
- Exploratory Data Analysis
- Data Visualisations
- Power BI Dashboard
- Tableau Dashboard
- Data Analysis Report
- Executive Summary
- Data-Driven Recommendations
- Final Presentation
The practical project is designed to help participants move from learning Data Analysis concepts to demonstrating their ability to analyse real-world data and communicate meaningful insights.
Duration & Format
Duration
8 Weeks
Delivery Format
The programme is available through
- Live Online Instructor-Led Training
- In-Person Classroom Training
- Instructor demonstrations
- Hands-on computer-based exercises
- Practical datasets
- Guided exercises and assignments
- Real-world business case studies
- Data analysis workshops
- Dashboard development sessions
- Individual and group projects
- Portfolio development
- Final project presentation and feedback
Entry Requirements
The Data Analysis programme is suitable for beginners and professionals who want to develop practical data skills.
Participants should have
- Basic computer literacy
- Basic understanding of using a computer and common software applications
- Basic familiarity with spreadsheets is helpful but not mandatory
- A willingness to learn and practise using data analysis tools
- No previous Data Analysis, programming or SQL experience is required.
- The programme starts with foundational concepts before progressing to more advanced tools and techniques.
Certification
- Participants who successfully complete the programme will receive a Renzy Academy Certificate of Completion in Data Analysis.
- The certificate recognises successful completion of the training programme and practical Data Analysis project.
Participants will also develop practical projects that can be included in a professional portfolio to demonstrate their skills to prospective employers or clients.
Career Opportunities
Data Analysis skills are applicable across virtually every industry where organisations collect and use data to support decision-making.
Potential roles include
- Data Analyst
- Junior Data Analyst
- Business Data Analyst
- Business Intelligence Analyst
- Reporting Analyst
- Data Reporting Specialist
- Operations Analyst
- Marketing Analyst
- Sales Analyst
- Financial Data Analyst
- Product Analyst
- Data Quality Analyst
- Research Analyst
- Business Analyst
- Data Visualization Specialist
- BI Developer
- Analytics Consultant
These skills are relevant across technology, banking and finance, telecommunications, healthcare, education, consulting, government, retail, manufacturing, energy, marketing and professional services.
Take the next step
Build Your Data Analysis Skills
Develop the practical skills needed to transform data into meaningful insights and support better business decisions.
At Renzy Academy, you will learn how to clean and analyse data, work with Excel and SQL, use Python for data analysis, create powerful visualisations and develop interactive dashboards using Power BI and Tableau.
Through hands-on exercises and a practical data analysis project, you will build real experience and develop a portfolio that demonstrates your ability to work with data and communicate meaningful findings.
Start developing the skills to analyse data, uncover insights and make better decisions.
Enrol today and take the next step in your Data Analysis career.