How To Identify And Clean Dirty Data | Mavens of Data

Data quality is the foundation of everything we do as Data Analysts and Data Scientists.
So why do so many organizations suffer from dirty data? And what can you do to clean it up?
In this episode, we’ll share some of the best data cleaning strategies and real actionable advice from The Classification Guru, Susan Walsh.
You’ll leave with a solid plan to start identifying problems with your data, and most importantly, to start fixing them on the path to clean data.
What You'll Learn:
1) Why dirty data is such a big problem, and the benefits of cleaning it up
2) The most common types of dirty data you should be on the lookout for
3) Where you should focus your data cleaning efforts to make the biggest impact
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About our guest:
⭐️ Susan Walsh ⭐️
Susan Walsh is a specialist in data classification, taxonomy customisation and data cleansing. She also created the COAT philosophy, which is at the core of The Classification Guru's work.
By bringing clarity and accuracy to data and procurement, Susan helps teams work more effectively and efficiently
More than a numbers gal, Susan’s also an industry thought leader, TEDx speaker and author of the published ‘Between the Spreadsheets: Classifying and Fixing Dirty Data’. She’s also spoken globally at events such as ProcureCon, Big Data LDN, Big Data & AI World and she cuts through the jargon to address the issues of dirty data and its consequences in an entertaining and engaging way.
Fix your dirty data now: www.theclassificationguru.co

[@ericaleverson9430]

I feel dirty data starts with how the data is collected. I find not enough data validations are not put in place in the applications that collect the data.

[@theclassificationguru]

It was such a great session, thanks!

[@saheedmorenikeji4020]

Love it,
It so helpful❤

[@mant3359]

Loved it! So inspiring! So helpfull!❤🙏👏👏

[@mattknee7561]

This was great!

[@vishwajeetrajput6985]

❤

[@peace-is-happy7046]

mm-dd-yyyy