Master Exploratory Data Analysis: Essential Tips & Strategies | Playbook Ep. 4 π
Learn how to effectively perform Exploratory Data Analysis with proven techniques in this comprehensive guide. Perfect for aspiring data analysts! Apply now for the Winter 2025 mentorship cohort: https://theanalyticsaccelerator.com/
Christine Jiang
18.4K views β’ Jun 25, 2025
About this video
MENTORSHIP - Applications for the Winter 2025 mentorship cohort are now open!
Apply here β https://theanalyticsaccelerator.com/
ABOUT THIS VIDEO
Struggling to make sense of your data after cleaning it? This episode of the Portfolio Playbook series shows you how to tackle the first layer of exploratory analysis with clarity and structure.
Youβll learn:
β’ The SCAN framework to guide early EDA
β’ How to structure your analysis around stakeholder-style questions
β’ Simple Excel techniques to spot trends and patterns faster
ABOUT ME
If we havenβt met yet - hi! Iβm 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
- Download the dataset by signing up for the newsletter - http://bit.ly/4epyC9p
- Apply to the next cohort - https://theanalyticsaccelerator.com/
- Follow on LinkedIn - https://linkedin.com/in/christine-jiang
- Instagram - https://instagram.com/cjiaang (my photography, because why not)
Timestamps:
0:00 - Introduction
0:52 - READY Framework
1:45 - Don't Skip this EDA Step
4:49 - EDA Framework
5:55 - SCAN in Action
6:40 - Stakeholder Goals
7:48 - Columns and Coverage
11:00 - Aggregates and Anomalies
19:00 - Notable Segments
Video URL: https://youtu.be/deS6lETubdU
Apply here β https://theanalyticsaccelerator.com/
ABOUT THIS VIDEO
Struggling to make sense of your data after cleaning it? This episode of the Portfolio Playbook series shows you how to tackle the first layer of exploratory analysis with clarity and structure.
Youβll learn:
β’ The SCAN framework to guide early EDA
β’ How to structure your analysis around stakeholder-style questions
β’ Simple Excel techniques to spot trends and patterns faster
ABOUT ME
If we havenβt met yet - hi! Iβm 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
- Download the dataset by signing up for the newsletter - http://bit.ly/4epyC9p
- Apply to the next cohort - https://theanalyticsaccelerator.com/
- Follow on LinkedIn - https://linkedin.com/in/christine-jiang
- Instagram - https://instagram.com/cjiaang (my photography, because why not)
Timestamps:
0:00 - Introduction
0:52 - READY Framework
1:45 - Don't Skip this EDA Step
4:49 - EDA Framework
5:55 - SCAN in Action
6:40 - Stakeholder Goals
7:48 - Columns and Coverage
11:00 - Aggregates and Anomalies
19:00 - Notable Segments
Video URL: https://youtu.be/deS6lETubdU
Video Information
Views
18.4K
Likes
793
Duration
19:40
Published
Jun 25, 2025
User Reviews
4.6
(3) Related Trending Topics
LIVE TRENDSRelated trending topics. Click any trend to explore more videos.