Teradata Solves Biggest Challenges of Executing Analytics at Scale for Enterprise Customers

New Bring Your Own Model (BYOM) functionality integrates open-source technologies, complementing an analytics framework that helps businesses operationalize artificial intelligence (AI) and machine learning (ML) projects at scale

Teradata, the connected multi-cloud data platform for enterprise analytics company, announced that Vantage is now able to operationalize externally created predictive models, also known as model sharing or BYOM. This move further supports Teradata’s strategic analytics framework that gives data-driven enterprises a step-by-step solution for deploying analytical models at scale. Businesses will now be able to quickly realize a greater return on investment (ROI) in developing analytical models through increased model operationalization, expanded analytic use cases, and a streamlined approach to data-driven decision-making.

Business leaders recognize that artificial intelligence and machine learning are the basis of competitive advantage in their industry, leading to an explosion in AI/ML technology investments. Despite these investments, many businesses are struggling to see returns from AI/ML projects due to inefficient data processes. To address this challenge, Teradata has created a strategic analytics framework – Analytics 1-2-3 – to establish a straightforward roadmap for businesses to create robust, efficient, and easily deployed processes that ensure AI/ML projects live up to their promise and deliver business value.

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BYOM further supports this framework as it enables a significantly wider group of models and analytic algorithms to be available for deployment at scale. This means that models typically created on small systems with limited data sets can now be operationalized and scaled to the level required to score the various models rapidly, securely and consistently, all within Vantage.

By leveraging this new functionality, Analytics 1-2-3 provides Teradata customers with an easy way to create and operationalize any number of models on any data volume in near real time.

• BYOM ensures customers can retain their investments in model development technologies without any risk or functionality loss when deployed in Vantage. This is realized by importing externally created predictive models by open-source packages or third-party solutions into Vantage, and then allowing the scoring of these models in parallel, using all the data that Vantage can ingest.
• As part of BYOM, Teradata data scientists can use any of their preferred open-source tools, such as R, Python, Apache Spark, SAS, KNIME, and more, to be executed in parallel alongside native Vantage analytic functions, enabling the operationalization of insights without needing to sample data or create data silos outside of Vantage.
• Teradata has a robust partnership community with leading advanced analytics and AI/ML vendors. The Analytics 1-2-3 framework naturally incorporates existing and new partners in Teradata’s analytics and AI/ML portfolio, providing customers, and the data science community, with the industry’s most optimal analytics ecosystem. Teradata provides customers support for their analytic tools of choice – now, in an industry-best, optimized configuration. The result is an analytics ecosystem that provides business users with answers and insights in minutes rather than hours or days, enables more robust models for deeper insights, and delivers faster model refresh, updates, and replacements.

“As our enterprise customers continue to explore the possibilities of AI to increase customer engagement, revenue, and reduce risk and cost, they need solutions that are built for the complexity of today’s modern data analytic ecosystem,” said Hillary Ashton, Chief Product Officer at Teradata. “Teradata Vantage was built with the flexibility and scalability to handle the most complex enterprise workloads, regardless of where the data sits. Now, with its new BYOM functionality, Vantage can address the most stubborn challenges facing organizations that wish to quickly realize value from their AI/ML investments.”

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Analytics 1-2-3: A Strategic Framework Leveraging New BYOM Capabilities

Analytics 1-2-3 provides an easy way to create and operationalize any number of models on any data volume in near real time. It decouples the different elements of the analytics process and ensures appropriate weight is given to each. This framework, when combined with Vantage’s BYOM functionality, gives enterprises the ability to test, scale and deploy analytical models quickly and efficiently.

• Analytics 1 – Data Preparation: This is when any type of data and at whatever volume is prepared. The core features are then extracted which are in turn used for analytic modeling. These features, once created, are curated within an Enterprise Feature Store (EFS) so that they can be repeatably used.
• Analytics 2 – Model Training: This is when analytical models (e.g., machine learning, statistical) are created from the features delivered in the first step. Model functionality that is natively available in Vantage, as well as the BYOM functionality, ensures that a wide range of models, often used in combination, are made available for operationalization.
• Analytics 3 – Deployment: With Vantage’s AnalyticsOps service, users can manage end-to-end analytic model creation at scale. Vantage will monitor model performance and automatically trigger rescoring or model updates, all while maintaining model, features, code, and data lineage.

Teradata Vantage is the connected multi-cloud data platform for enterprise analytics. It enables ecosystem simplification by unifying analytics, data lakes and data warehouses. With Vantage, enterprise-scale companies can eliminate silos and cost-effectively query all their data, all the time, regardless of where the data resides — in the cloud, on multiple clouds, on-premises or any combination thereof — to get a complete view of their business.

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