DATA SCIENCE

SlyceData to launch Investment Research Intelligence Engine with Snowflake

SlyceData Corporation | February 28, 2022

SlyceData Corporation
SlyceData has announced the release of a Snowflake-powered intelligent financial data wrangling and analytics platform. Investment analysts may use this solution from SlyceData and Snowflake, the Data Cloud provider, to seamlessly examine and extract their numerous financial data sources across vendors, substantially speeding up the production of investment ideas.

With its one integrated platform, Snowflake's Data Cloud provides customers access to a wide range of data sources. Snowflake, a technological initiative that accelerates the capacity of enterprises and application developers to produce innovative apps, powers SlyceData's technology. SlyceData takes advantage of Snowflake's performance and versatility to enable clients to easily merge their numerous financial data sources, allowing them to identify insights and generate portfolio returns more effectively.

SlyceData and Snowflake handle the time-consuming but critical challenge of producing research-ready data for investment analysis, allowing customers to tap into new sources and get fresh insights. As per a recent HBR article, data scientists spend 80% of their time preparing data and just 20% evaluating it, which is something SlyceData wants to change.

VP of Equity Investment Management Technology at AllianceBernstein, Mike Bauer, said that "Access to a vast range of data in the research-ready form is crucial for our organization's success. SlyceData and Snowflake are building technology to dramatically simplify the work of data delivery and wrangling, and we're very excited to see the value it should bring."

"We're delighted to work with Snowflake to provide customers with ready-to-use data at their fingertips. Our mission is to empower customers to get the most out of their data, to drive performance."

Chris Harrison, CEO of SlyceData

Spotlight

Unplanned downtime is one of the most significant pain points for industrial manufacturers today, costing them an estimated $50 billion each year. The risk is even greater for process manufacturing, where a critical equipment failure could result in the loss of an entire batch, environmental hazards, or safety risks. The adoption of digital technologies, such as the industrial internet of things (IIoT), promises to mitigate these threats by forecasting equipment failures and catching faults before they lead to unscheduled shutdowns. However, in practice, several challenges arise when maintenance personnel and operations leaders work to implement an IIoT solution aimed at eliminating unplanned downtime.

Spotlight

Unplanned downtime is one of the most significant pain points for industrial manufacturers today, costing them an estimated $50 billion each year. The risk is even greater for process manufacturing, where a critical equipment failure could result in the loss of an entire batch, environmental hazards, or safety risks. The adoption of digital technologies, such as the industrial internet of things (IIoT), promises to mitigate these threats by forecasting equipment failures and catching faults before they lead to unscheduled shutdowns. However, in practice, several challenges arise when maintenance personnel and operations leaders work to implement an IIoT solution aimed at eliminating unplanned downtime.

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