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"What do you do when the data won't fit in a spreadsheet?" In this session, Lead Tutor Sam breaks down Skill 55 (S55) for the Data Analyst pathway: Analysing in detail large data sets. If you are an apprentice on the ST0119 standard, this is your guide to the professional tools that define modern data analysis. We move beyond the "pond" of desktop tools to the "ocean" of big data using the 3 Vs and the Tool Ladder. IN THIS VIDEO: The Pond vs. Ocean Analogy: Why you need new tools for large data. The 3 Vs: How to define "Large Data" (Volume, Velocity, Variety). The Tool Ladder: When to use SQL, Python, and Cloud Platforms. The Principle: "Don't move the mountain to find the rock." Ben's Plan: A practical example of analysing 500GB of messy data. Portfolio Guide: Writing up S55 using the STARR method. ADDITIONAL DETAILS: Your problem, solved! Find the exact answers you need below: Slide 4: How do I know if my data is "Big Data"? Slide 5: When should I use a Database instead of a spreadsheet? Slide 6: When do I need Python? Slide 9: How do I prove S55 in my portfolio? ➡️ Download the full presentation slides and transcript from our EPA Hub: www.mentorinai.com/epahub/ Timestamps: 00:00 Introduction - Scaling Your Skills 01:10 Deconstructing the Skill - The Professional's Toolkit 02:20 The 'Why' - The Modern Analyst's Reality 03:30 Defining "Large": The 3 Vs Rule 04:45 The Tool Ladder, Rung 1: Databases (SQL) 06:00 The Tool Ladder, Rung 2: Programming (Python) 07:15 The Tool Ladder, Rung 3: Cloud Platforms 08:30 S55 in Action: The Large-Scale Analysis Plan 09:20 Portfolio Evidence - The STARR Method 10:15 Major Project Application & Conclusion EPA Checklist: What: Did I identify the characteristics (3 Vs) of the large dataset? How: Did I select and use the appropriate industry-standard tool? Why: Did I justify why a standard tool (like a spreadsheet) was insufficient? Affiliate Links: Enhance your Big Data skills with these recommended courses: Coursera: Google Data Analytics Professional Certificate Pluralsight: SQL for Data Science / Python for Data Analysis (We may earn a commission if you sign up through these links). Join our newsletter for weekly tips: www.mentorinai.com Need help? Book a Mock Interview or Portfolio Review today!