Podcast
24d ago
Dremio: Hadoop Migration and Moving to Frictionless Cloud
Susan Walsh
With over a decade of experience fixing your dirty data, Susan Walsh is the Classification Guru.
Susan is Founder and Managing Director of The Classification Guru Ltd, a specialist data classification, taxonomy customisation and data cleansing consultancy. She is an industry thought leader, TEDx speaker, DataIQ100 2022, and author of ‘Between the Spreadsheets: Classifying and Fixing Dirty Data’ and the “Fixing Dirty Data – The Basics of Data Cleaning” course. She’s also the creator of the COAT philosophy.
Susan has developed a methodology to accurately and efficiently classify, cleanse and check data for errors which will help prevent costly mistakes. This could save days of laborious cleansing and classifying and can help your business find cost savings through spend and time management - supporting better, more informed business decisions.
Susan brings clarity and accuracy to data and procurement; helps teams work more effectively and efficiently; and cuts through the jargon to address the issues of dirty data and its consequences in an entertaining and engaging way.
Susan is Founder and Managing Director of The Classification Guru Ltd, a specialist data classification, taxonomy customisation and data cleansing consultancy. She is an industry thought leader, TEDx speaker, DataIQ100 2022, and author of ‘Between the Spreadsheets: Classifying and Fixing Dirty Data’ and the “Fixing Dirty Data – The Basics of Data Cleaning” course. She’s also the creator of the COAT philosophy.
Susan has developed a methodology to accurately and efficiently classify, cleanse and check data for errors which will help prevent costly mistakes. This could save days of laborious cleansing and classifying and can help your business find cost savings through spend and time management - supporting better, more informed business decisions.
Susan brings clarity and accuracy to data and procurement; helps teams work more effectively and efficiently; and cuts through the jargon to address the issues of dirty data and its consequences in an entertaining and engaging way.
