5 September 2019
With the increase in open source data, issues with data quality and consistency have increased in prevalence. In this talk, I will discuss some of the issues that can arise when matching postal addresses from different datasets and how these can be resolved. I will also talk about how fuzzy matching can be used for data cleansing, aiming to provide some practical tips.
And the short bio: Dr Violeta Kovacheva is a Data Scientist for Nimbus Property, a company that develops a web platform for property related data. After obtaining a Maths degree from Oxford University, she went on to do a Masters and a PhD in Systems Biology from Warwick University. She worked as a Post-Doctoral Fellow in the Institute of Cancer Research looking into machine learning image processing methods to aid cancer diagnosis. She then moved on to work as a Data Scientist for Wealth Wizards, helping them in their mission to make financial advice more accessible and affordable.
For security reasons, we must have your full name so that you can gain access to the room. You will need some form of Photo ID and your name will be matched to the list.