Refinitiv Delivers Tick History On Google Cloud
Building on its commitment to the delivery of data on the cloud, Refinitiv today announces the launch of its Tick History dataset on Google Cloud Platform (GCP), enabling customers to access, query and analyze Refinitiv’s extensive archive of pricing and trading data using the machine learning capabilities of Google Cloud’s BigQuery.
Our #TickHistory data is now available on the cloud! Launched today with @googlecloud – Tick History customers can access, query and analyze large data sets in the cloud using the #MachineLearning capabilities of Google Cloud’s #BigQuery. Learn more here: https://t.co/u7JSNYPH7o pic.twitter.com/l0YvvygaD6
— Refinitiv (@Refinitiv) February 11, 2020
The Tick History dataset offers the full breadth and depth of Refinitiv’s historical tick data drawn from real-time content. The dataset covers Over The Counter (OTC) and exchange-traded instruments from all asset classes in more than 500 venues dating back to 1996.
The combination of Refinitiv’s managed service database and GCP’s managed compute cluster allows for customers to work across large datasets remotely and in a fraction of the time that they would typically experience. Customers using the solution are also likely to enjoy a reduced total cost of ownership, as they benefit from a reduced infrastructure spend and storage required to maintain and integrate the scale of Refinitiv’s Tick History data.
We are excited to announce the launch of @Refinitiv's Tick History dataset on Google Cloud Platform. Customers can now analyze their pricing and trading data archive using BigQuery: https://t.co/urQrwvUBG9 pic.twitter.com/1VPw5khwvv
— Google Cloud UK & Ireland (@GoogleCloud_UKI) February 11, 2020
Further, the capabilities of the BigQuery will power analytics of the Tick History data, enabling customers to build and back-test trading strategies, perform quantitative research and analysis, and meet regulatory and best execution requirements. Because the data can be analyzed in-situ and does not need to be moved and loaded into an analytics engine, customers can also obtain results in reduced timeframes when compared to what they would typically expect. This expedited delivery of data allows for data scientists and quantitative analysts to be more productive as they spend less time preparing and waiting for data delivery, and more time generating valuable insights.
A report titled Global Algorithmic Trading Market 2016–2020 suggests that by 2020, around 90% of public market trades in the U.S. will be traded by quantitative means. Refinitiv’s customers continue to strive for success in this increasingly competitive and automated financial market, where access to large volumes of historical data and near-infinite amounts of compute and storage capabilities are of great value.
A global Refinitiv survey conducted in 2019 among 300 senior executives and heads of market data found that “as cloud adoption in financial services evolves, companies are finding that the benefits are not just about cost efficiencies but also to do with resilience, agility and innovation.” The survey also found that 64% of firms believe that cloud use will be “significant, or transformational, for their sector over the next five to 10 years”.
Catalina Vazquez, Proposition Director, Tick History at Refinitiv, said: “As the cloud delivers on its promise to make AI-based analytics more readily available, the potential of data to deliver answers that drive business performance gets ever greater. Combining Google Cloud’s machine learning tools with Refinitiv’s Tick History data in BigQuery is a step-change for customers looking to develop new trading models, interpret trade patterns or comply with regulations. The cloud is changing the paradigm for the financial community, enabling less time and money spent managing data and more time innovating and getting answers from data that gives a competitive edge.”
Adrian Poole, Head of Financial Services, UKI, Google Cloud, said: “At Google Cloud, we are committed to partnering with the industry on solving complex problems. Working with Refinitiv, we are delighted to help the company with the delivery of its customer commitment to provide its datasets on GCP.”
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