PANEL - Better Data Engineering: how to assess data procurement & obtain the best insight
Channel: Beryl Elites
Date: 2019-01-22

BERYL ELITES KNOWLEDGE CENTER

Better Data Engineering: how to assess alternative data procurement processes, how to reach the best insights the fastest

Panelists: ❖ Michael W. Mayhew - Integrity Research Associates ❖ Philip Brittan – Crux Informatics
❖ Greg Skibisky - Thasos Group ❖ Norman Niemer - UBS

- Michael W. Mayhew
"In order to take advantage of any of the promise of these technologies and these trends there really is a lot of hard work that has to be done upfront to be able to take advantage of the data." 

- Philip Brittan
"It is the amount of effort and work that goes into finding and then ingesting and wrangling data sources and operating them is highly overlooked. A lot of firms have gone out and hired teams of data scientists because they want to start doing big data, machine learning, getting value out of data. They spend eighty percent of their time reading file specs from vendor, doing very basic wire up kind of work, checking data, mapping identifiers .. before they can even get to the data science that they were hired to do. And then there is the operational part .. if you have a data feed, that's become an integral part of your research and investment process, that data has to show up every day and it has to be correct it can't be missing .. so there's tremendous operational load on watching these feeds and dealing with issues whether it's a network issue or data messed up issue .."

- Greg Skibisky 
"When you are analyzing geolocation data from mobile phones it's probably one of the most noisy difficult to work with error prone data sets that you can really find. Everybody keep changing it, nobody documents the changes."

- Norman Niemer
"Getting data from a vendor that's not machine readable .. but it's not great for us from engineering perspective. Doesn't have any sort of point in time data, too short data .. these are some of key challenges."

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