Data Analysis Workflow Design
In person
This workshop is designed to help you confidently plan your data analysis from the very start of your project. We will explore how to understand a project remit, identify the types of data you have or will collect, and make informed, constructive methodological choices.
You will learn how to design an effective analysis workflow, from preprocessing and tool selection to decision points, bottlenecks, alternatives, and interpretive stages. We will also cover practical aids for optimising, adapting, and aligning your workflow with your project goals.
By the end, you will be equipped with strategies to build clear, efficient, and rigorous data-analysis pathways tailored to your research needs.
This course will be taught by Somya Iqbal.
After taking part in this event, you may decide that you need some further help in applying what you have learnt to your research. If so, you can book a Data Surgery meeting with one of our training fellows.
More details about Data Surgeries.
Those who have registered to take part will receive an email with full details on how to get ready for this course.
If you’re new to this training event format, or to CDCS training events in general, read more on what to expect from CDCS training. Here you will also find details of our cancellation and no-show policy, which applies to this event.
Level
This is a beginner-friendly course. No previous knowledge on the topic is required/expected, and the trainer will cover the basics of the method.
Some basic familiarity with the type of data you will have or have collected and methodologies (statistical or otherwise) you plan/or are thinking to apply would be useful for making the most of the session.
Learning Outcomes
Understanding requisites for designing an analysis workflow for your data
How to integrate data pre-processing and required steps before considering analysis methods, and corroborating with your domain conventions
Familiarising with tools and methods suited for designing and applying a data analysis pipeline
Skills
Breaking down a data analysis pipeline into constituent parts for iterative design and application
Recognising requisites and skills for a given analysis pipeline
Integrating stops and checks across the data analysis workflow with proper handling and visualisation to aptly justify methodologies
- Optimally selecting methods for analyses based on the shape, distribution of your data and goals of your research
Explore More Training
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- Explainable Machine Learning (XAI)
- Foundations of Machine Learning
- Getting Started with Bayesian Statistics
- Getting Started with Data Analysis in Python
- Getting Started with Regression in R
- Linear Mixed Effects Modelling
Return to the Training Homepage to see other available events
Room 4.35, Edinburgh Futures Institute
This room is on Level 4, in the North East side of the building.
When you enter via the level 2 East entrance on Middle Meadow Walk, the room will be on the 4th floor straight ahead.
When you enter via the level 2 North entrance on Lauriston Place underneath the clock tower, the room will be on the 4th floor to your left.
When you enter via the level 0 South entrance on Porters Walk (opposite Tribe Yoga), the room will be on the 4th floor to your right.
