About the course
The ability to transform raw data into a narrative is a critical professional requirement. This intensive 1-day workshop moves beyond basic spreadsheet usage to explore the rigorous logic of the Data Analysis Lifecycle. We treat data not just as numbers in a grid, but as a strategic asset that requires cleaning, validation, and ethical stewardship.
We prioritize the integrity of the analytical process. You will learn to identify the dimensions of data quality, master the mechanical cleaning of datasets using professional Excel techniques, and apply descriptive statistics to summarize complex information. By the end of the day, you will move from simply "viewing" data to constructing interactive dashboards and communicating insights with clarity, while maintaining a firm grasp on the modern requirements of data privacy and ethics.
Instructor-led online and in-house face-to-face options are available - as part of a wider customised training programme, or as a standalone workshop, on-site at your offices or at one of many flexible meeting spaces in the UK and around the World.
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By the end of this course, attendees will be able to:
- Execute the Data Lifecycle: Manage the end-to-end process from initial data questioning to final insight delivery.
- Master Data Hygiene: Identify and resolve quality issues such as duplicates, inconsistent formats, and outliers using advanced Excel tools.
- Apply Statistical Logic: Utilize descriptive statistics and data aggregation functions to reveal the "story" within the numbers.
- Architect Interactive Reports: Build PivotTables and PivotCharts that allow for dynamic, multi-dimensional data exploration.
- Communicate with Impact: Design clear, ethical visualizations and single-sheet dashboards that adhere to best practices in data storytelling.
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Aspiring Data Analysts looking for a structured, hands-on introduction to the field.
Business Professionals & Administrators who need to move beyond "gut feeling" to evidence-based decision-making.
Project Managers who oversee data-driven teams and need to understand the fundamental mechanics of data quality and ethics.
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Basic Excel Literacy: Comfort with simple navigation and cell entry.
Analytical Curiosity: A desire to find patterns and solve problems using structured information.
No prior data analysis experience is required.
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This Data Analysis course is available for private / custom delivery for your team - as an in-house face-to-face workshop at your location of choice, or as online instructor-led training via MS Teams (or your own preferred platform).
Get in touch to find out how we can deliver tailored training which focuses on your project requirements and learning goals.
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The Data Foundation & Lifecycle
Defining Data: Understanding the impact of the modern data explosion; distinguishing between Qualitative vs. Quantitative and Structured vs. Unstructured data.
The Analytical Framework: An end-to-end overview of the lifecycle—asking the right questions, sourcing data, and driving action from insights.
The Business Case: Why correct data utilization is the primary differentiator for modern professional efficiency.
Data Quality & Preparation
Dimensions of Quality: Engineering for Accuracy, Completeness, Consistency, Timeliness, Validity, and Uniqueness.
Mechanical Cleaning: Using Excel’s professional toolset including "Text to Columns," "Remove Duplicates," and advanced Find & Replace logic.
Text Manipulation: Utilizing TRIM, CLEAN, and PROPER functions to standardize messy datasets.
Statistical Analysis & Aggregation
Descriptive Statistics: Mastering the calculation of mean, median, mode, and standard deviation via AVERAGE, MEDIAN, and STDEV.P.
High-Velocity Aggregation: Using SUM, COUNT, COUNTA, and the logical COUNTIF/COUNTIFS family.
PivotTable Architecture: Introducing PivotTables for summarization and grouping; implementing Slicers and Timelines for interactive filtering.
Visualization & Communication
The Principles of Visual Design: Why effective visualization is crucial for cognitive load management.
Strategic Chart Selection: Choosing the optimal visual (Bar, Line, or Scatter) based on the data narrative.
Dashboard Engineering: Building a functional, single-sheet dashboard that combines charts and interactive elements for stakeholder reporting.
Governance, Privacy & Ethics
The Governance Framework: Roles, responsibilities, and the importance of data policies.
Privacy & Regulation: A professional overview of GDPR and the importance of protecting sensitive information.
The Ethical Analyst: Identifying bias, ensuring fairness, and maintaining transparency in data interpretation.
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Microsoft Data Analysis Guide: Official documentation for Excel-based analytical tools.
The Data Visualization Catalogue: A comprehensive guide to choosing the right chart for your data type.
ICO Guide to Data Protection: Essential reading for understanding privacy and GDPR in the UK.
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