WFIC Vancouver 2019

Earlier this month, TickSmith traveled to Vancouver to participate in the World Financial Information Conference (WFIC) in Vancouver BC.  We joined exchanges, data vendors, data consumers, and technology providers to discuss various issues, changes, and standards & best practices for data within the Financial Services space.

TickSmith Presentations

On Tuesday morning, our Partners at AWS invited us to their booth to showcase the numerous AWS services that are being utilized within our GOLD Platform.  Our Product Manager, Nic Doyen, spoke on services including EC2 Instances, S3, S3 Glacier, Cloudwatch, SQS, SNS, Lambda, AmazonMQ, RDS, Route 53, Direct Connect, CloudTrail, and IAM and described how these services help us solve problems and add value when deploying our Big Data Management Platform.  Nic then went on to show the audience how customers can utilize modules within the platform to create and add new content to the platform and demonstrated the power and flexibility of our GOLD ETL to help transform data. 

Later on Tuesday, our CEO Francis Wenzel spoke on a panel Which Road through the Wild West? Alternative Data Delivery Platforms, with Emmett Kilduff, Michael Patton, Steve Weinstein, and moderator Eliza Raphael.  Francis emphasized the importance of being able to centralize and normalize data assets regardless of the source. 

Themes & Lessons Learned

We also enjoyed many of the panels, discussions and the themes that were covered.  It’s important to understand the risk of the data and what are the results when it is mishandled. Many of the technologies built for capital markets deal with data that is critical to the trading practices of the institution and mishandling of it can lead to severe consequences.  A big opportunity for firms to improve their current process is to assist in the centralization and control of data. Information on the data, such as the pedigree, anthropology, and quality of data are key pieces of information to capture.

Some of the biggest challenges facing the industry today are knowing what data exists and how its useful (how to make data discovery easier and faster), the cleanliness of data is still ever prevalent as an issue, and managing the combination and execution of analytics on large numbers of massive datasets.

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