EZOPS’ AI-powered software can detect anomalies, predict break reasons, and optimize reconciliation across Snowflake’s Data Cloud
EZOPS, the leading provider of AI-enabled data control, workflow automation, and regulatory reporting, announced that they are incorporating support for Snowflake the Data Cloud company, to enhance operational efficiency for their customers.
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“EZOPS’ innovative artificial intelligence-powered data automation platform delivers major cost and time savings, drives operational efficiencies, and eliminates risk. We’re excited to bring this functionality to Snowflake customers.”
Snowflake customers can leverage EZOPS AI models to analyze patterns of streamed data, which can be validated for anomalies prior to storage. EZOPS AI models allow Snowflake customers to detect anomalies as well as predict break reasons. Additionally, data stored in Snowflake’s single, integrated platform can in turn be used for reconciliation without having to load data from multiple sources.
“Snowflake offers customers the ability to derive value from sharing rapidly growing data sets in secure, governed, compliant, and seamless ways,” said Sarva Srinivasan, President and Co-founder of EZOPS. “EZOPS’ innovative artificial intelligence-powered data automation platform delivers major cost and time savings, drives operational efficiencies, and eliminates risk. We’re excited to bring this functionality to Snowflake customers.”
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Data that is streamed into Snowflake’s Data Cloud can be validated for anomalies prior to storage by leveraging the EZOPS AI models. If anomalies are identified, they can be escalated within the EZOPS Workflow module for processing and triaging. By incorporating EZOPS, Snowflake customers can identify data quality issues before the data is stored, in turn ensuring that their downstream processes are managed efficiently.
Customers can store reconciliation data and the results in Snowflake. EZOPS leverages AI to predict reasons for breaks, thereby ensuring that the time spent on researching the breaks is reduced. EZOPS Curie uses a number of supervised Machine Learning models to support this capability and gives Snowflake users the ability to select the right model, hyperparameters, and features to get optimal performance from the solution.
“EZOPS offers Snowflake customers access to their machine learning & enhanced reconciliation capabilities. From low code data transformation, to predictive analytics and anomaly detection, customers can leverage the EZOPS platform directly on Snowflake leveraging the flexibility, performance and ease of use of the Snowflake Data Cloud in order to attain more meaningful insights and value across their enterprise,” said Tarik Dwiek, Head of Technology Alliances, Snowflake.
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Data stored in Snowflake can also be used for reconciliation without having to load data from multiple databases and sources. Once the data is available, EZOPS ARO can run the reconciliation and provide the results back to the Snowflake user. This data can then be used for reporting and other downstream operational processes, reducing the amount of data movement and points of failure while increasing efficiency.
The integration between Snowflake and EZOPS is seamless, allowing for a reduction in time and cost to deploy and go into production. EZOPS’ Machine Learning and AI-powered data automation can be leveraged across both financial and non-financial data to establish well-defined data governance for data stored in Snowflake. The all-in-one data quality and control capabilities eliminate the need to have multiple asset class or business function specific systems, saving significant technology licensing costs. Additionally, EZOPS’s flexible and user-driven reporting allows executives, managers, users, and clients to build private and shared visualization dashboards and share actionable data across the business ecosystem.
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