SQLBits runs from the 18-21 June 2025.
Data Transformation and Integration
Python - The Essential Swiss Army Knife for Your Data
Description
❓ Are you tired of relying on basic Python scripts and looking to take your data analysis to the next level?
❓ Do you want to unlock the full potential of Python for real-world data scenarios, from manipulation to advanced analysis?
In this full-day training, we take a hands-on approach to understanding Python’s core functions, libraries, and best practices. The focus is on equipping attendees with the knowledge and confidence to use Python across any library or framework, ensuring they can adapt to different data challenges with ease.
Overview
Python has become an essential tool for data professionals, providing unparalleled flexibility across the entire data lifecycle. Whether ingesting raw data, transforming it into structured insights, building predictive models, or visualising results, Python empowers users to unlock new possibilities in data management and analytics.
We will explore Python's capabilities across five key pillars:
The morning we will cover,
✅Ingestion – Extracting and loading data from multiple sources using Pandas, PySpark, and APIs.
✅Transformation – Cleaning, merging, and shaping datasets efficiently with Pandas and PySpark.
The afternoon we will cover
✅Modelling – Applying forecasting techniques with Prophet and an introduction to machine learning with Scikit-Learn.
✅Reporting – Automating report generation using Python scripts and OpenPyXL for Excel integration.
✅ Visualisation – Creating impactful charts with Matplotlib, Seaborn, and Plotly.
This session is designed to help attendees move beyond basic Python scripting and develop a comprehensive understanding of how Python can be applied to real-world data scenarios.
This is an interactive, hands-on training day using a Talk-Do-Repeat format to reinforce learning. Whether you're a beginner or a seasoned data professional, this training will expand your ability to manage, manipulate, and analyse data efficiently.
❓ Do you want to unlock the full potential of Python for real-world data scenarios, from manipulation to advanced analysis?
In this full-day training, we take a hands-on approach to understanding Python’s core functions, libraries, and best practices. The focus is on equipping attendees with the knowledge and confidence to use Python across any library or framework, ensuring they can adapt to different data challenges with ease.
Overview
Python has become an essential tool for data professionals, providing unparalleled flexibility across the entire data lifecycle. Whether ingesting raw data, transforming it into structured insights, building predictive models, or visualising results, Python empowers users to unlock new possibilities in data management and analytics.
We will explore Python's capabilities across five key pillars:
The morning we will cover,
✅Ingestion – Extracting and loading data from multiple sources using Pandas, PySpark, and APIs.
✅Transformation – Cleaning, merging, and shaping datasets efficiently with Pandas and PySpark.
The afternoon we will cover
✅Modelling – Applying forecasting techniques with Prophet and an introduction to machine learning with Scikit-Learn.
✅Reporting – Automating report generation using Python scripts and OpenPyXL for Excel integration.
✅ Visualisation – Creating impactful charts with Matplotlib, Seaborn, and Plotly.
This session is designed to help attendees move beyond basic Python scripting and develop a comprehensive understanding of how Python can be applied to real-world data scenarios.
This is an interactive, hands-on training day using a Talk-Do-Repeat format to reinforce learning. Whether you're a beginner or a seasoned data professional, this training will expand your ability to manage, manipulate, and analyse data efficiently.
Learning Objectives
By the end of this training, attendees will be able to:
✅Learn how to get data in, from anywhere – We'll focus on bringing in data from different sources like databases, Excel files, websites, and APIs — whether they’re in Azure or not — and how to handle security along the way.
✅Clean and prepare your data properly – You'll build your own functions and use Python libraries like Pandas and PySpark to tidy, shape, and combine data, ready for analysis.
✅Build confidence through hands-on practice – You'll work through real examples in a clear, repeatable way so you leave feeling more confident and ready to use Python in your day-to-day work.
Things I will need
Tech Covered
Python, Fabric, Data Transformation and Integration, Grounded in Reality