Query-ready: Tick History data at your fingertips with Google Cloud Platform
Work More Powerfully and Efficiently with Refinitiv Tick History in Google Cloud Platform
Financial models don’t only need vast data; they also need deep past data to test historic scenarios. Learn how to derive quality insights with a smarter workflow so you can focus your time on formulating strategies instead of getting data ready for analysis. Register for Query-ready: Tick History data at your fingertips with Google Cloud Platform now.
Why should I attend?
This webinar is valuable for anyone in financial markets that works with historical pricing data. It will teach you how to access the full depth and breadth of Tick History data using Google Cloud Platform. Whether you’re a quant trying to uncover new opportunities, a trader pursuing strategies for alpha and best execution, or a risk manager striving to streamline compliance, Tick History in GCP delivers faster results for an improved workflow.
In the next 60 minutes you'll hear from Refinitiv and Google experts as they discuss:
Getting to know Refinitiv Tick History Data
Refinitiv's Tick History data offers 25 years of real-time pricing data covering every trade, quote, and asset class from over 500 global contributors. This data is cleansed and normalized allowing nimble market insights. Learn how to access Tick History's extract service to specify the instruments, field set and time frame you're interested in.
Architecture of Google BigQuery
Google BigQuery is an enterprise data warehouse that enables super-fast SQL queries. We will cover how to capture insights, implement predictive analytics, visualize intelligently and securely access data in Google BigQuery.
Modeling Tick History Data with Google BigQuery
We’ll show you how to model Tick History Data in Google BigQuery and achieve your market insights with maximum efficiency at a fraction of the time it would take outside of GCP.
Registration has now closed. Complete the form below to view the webcast
Date: April 20, 2020
Time: 3 PM BT | 10 AM ET
Location: Webinar On-Demand