talk-data.com

Speaker: Sue Bayes Start Date: Thu, Aug 21st 2025 · 7:00 PM EEST (4:00 PM UTC) Language: ENGLISH (with Live Translated CCs) Location: Online (link visible for attendees)

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This session introduces attendees to the fundamentals of web scraping using Python’s Beautiful Soup library. Attendees will learn how to navigate the complexities of HTML structures to extract valuable data efficiently. Key skills and concepts covered include: Understanding HTML and CSS: Learn how web pages are structured to identify the data you need. Setting up Beautiful Soup: Install and initialize the library to parse web content. Scraping Techniques: Use tags, attributes, and classes to locate and extract specific elements from web pages. Handling Dynamic Content: Work with tools like requests to scrape static pages and integrate with libraries like Selenium for dynamic content. Saving Scraped Data: Export extracted data into structured formats like CSV or JSON for further analysis. The session also emphasizes ethical considerations and best practices for web scraping, including handling website terms of service and respecting rate limits. Through hands-on examples, attendees will scrape a sample website and transform raw HTML into actionable insights. By the end of the session, participants will have the confidence to build their own web scraping workflows and apply them to real-world projects.

=============================================================== Speaker: Sue Bayes Microsoft Data Platform MVP \| Power BI & Microsoft Fabric Specialist

Sue is an independent data consultant and Microsoft MVP with over 20 years’ experience in business intelligence, analytics, and IT education. She’s a Microsoft Certified Fabric Data Engineer, Analytics Engineer, Azure Enterprise Data Analyst, and Power BI Data Analyst Associate.

For the past 7+ years, Sue has worked across public and private sectors, developing impactful Power BI solutions that span planning, project management, finance, and service-specific reporting.

Her work combines robust data engineering with insightful dashboard design, often integrating advanced techniques like sentiment analysis, Python forecasting, and bespoke data cleansing.

Before founding her consultancy, Sue spent 15 years lecturing in Business and Computing—an experience that continues to shape her passion for data literacy and enabling others.

Her current focus includes Microsoft Fabric, semantic modelling, and automating analytics using Python and DAX. She regularly speaks at major data conferences including SQLBits, Microsoft-led events, and other industry gatherings.

Sue also runs her own weekly tech user group, co-hosts the fortnightly Unpivot podcast, and actively contributes to the data community by sharing practical insights that demystify complex tools and help others embrace data with clarity and confidence.

When she’s not building reports or wrangling data, Sue’s often found training for marathons, running long distances across the Devon coast, walking her dog, or championing women in tech spaces.

Speaker: Sue Bayes, Microsoft DataPlatform MVP

Web Scraping Made Simple: Unlocking Data with Beautiful Soup

This 50-minute session introduces attendees to the fundamentals of web scraping using Python’s Beautiful Soup library. Attendees will learn how to navigate the complexities of HTML structures to extract valuable data efficiently. Key skills and concepts covered include:

Understanding HTML and CSS: Learn how web pages are structured to identify the data you need.

Setting up Beautiful Soup: Install and initialize the library to parse web content.

Scraping Techniques: Use tags, attributes, and classes to locate and extract specific elements from web pages.

Handling Dynamic Content: Work with tools like requests to scrape static pages and integrate with libraries like Selenium for dynamic content.

Saving Scraped Data: Export extracted data into structured formats like CSV or JSON for further analysis.

The session also emphasizes ethical considerations and best practices for web scraping, including handling website terms of service and respecting rate limits. Through hands-on examples, attendees will scrape a sample website and transform raw HTML into actionable insights. By the end of the session, participants will have the confidence to build their own web scraping workflows and apply them to real-world projects.

"Getting Started with Beautiful Soup" is your practical guide to website scraping using Python. It teaches you how to use Beautiful Soup and the urllib2 module to extract data from websites efficiently and effectively. Through hands-on examples and clear explanations, you'll gain the skills to navigate, search, and modify HTML content. What this Book will help me do Navigate and scrape web pages using the Beautiful Soup Python library. Understand and implement the urllib2 module to access web content programmatically. Search and analyze HTML structures efficiently to extract the needed data. Modify and format extracted HTML and XML content effectively. Handle encoding and manage output formats for diverse scraping requirements. Author(s) Vineeth G. Nair is an experienced Python developer with a strong focus on web technologies, data extraction, and automation. His expertise in Python's Beautiful Soup library has helped countless learners and professionals tackle the challenges of web scraping. Vineeth combines a methodical approach to teaching with practical examples, making complex concepts accessible and actionable. Who is it for? This book is ideal for Python enthusiasts, data analysts, and budding developers looking to explore web scraping. Whether you're a beginner or have some programming experience, this book will guide you through the fundamental concepts of extracting web data. If you're aiming to delve into practical, real-world implementations of web scraping, this is the book for you.