Think like a Data Analyst: Data Cleaning Framework

MENTORSHIP
Applications are now open for the Spring 2025 cohort of my mentorship program! Group info sessions with me are starting in the next few weeks - apply at theanalyticsaccelerator.com.
Excited to meet you soon!

THIS VIDEO
Data cleaning is more than just fixing errors—it's about applying a framework and mental model that can help you shine in job interviews and on the job. In this video, I’ll walk you through a high-level approach to cleaning datasets, including how to think through common challenges, prioritize your efforts, and document your process like a pro. Stick around to learn the best practices for how to deal with "unsolvable" issues, i.e. missing or nonsensical data - and be sure to apply these tips to your portfolio projects!

ABOUT ME
If we haven’t met yet - hi! I’m Christine, a former data director and hiring manager helping ambitious career transitioners and recent grads land their first job as a data analyst. I'll be sharing the insights and strategies that empowered over 70% of job-hunting students in the first cohort of my mentorship program landed their first data job within 6 months, in today's super-competitive job market.

If you want to become a standout data analyst through applied business skills, soft skills, and strategies for every part of the job hunt process - so that you can have confidence, professional leverage, and bring real impact to work - connect below for more insights and future workshops!

LINKS
Get more tips in my newsletter - bit.ly/3LodfYs
Apply to the next cohort - theanalyticsaccelerator.com/
Follow on LinkedIn - linkedin.com/in/christine-jiang
Instagram - instagram.com/cjiaang (my photography, because why not)

Timestamps:
0:00 - Introduction
0:36 - High Level Thought Process
1:00 - The Analytical Lifecycle
2:16 - Data Cleaning Framework
3:11 - Conceptualize the Dataset
5:49 - Locate Solvable Issues
7:46 - Evaluate Unsolvable Challenges
10:02 - Augmentation
10:58 - Note and Document
11:39 - Review

Video URL:    • Think like a Data Analyst: Data Cleaning F...…