Teradata is introducing new features and productivity enhancements to ClearScape Analytics, that are designed to enable innovative organizations to maximize the ROI of their AI/ML investments and boost data science productivity.
In recent years, the increased complexity of AI tools and platforms coupled with the proliferation of data and analytic platforms has resulted in complicated and inefficient AI/ML processes.
As a result, companies are unable to derive complete insights from their data and the cost of AI operationalization at scale has risen. At the same time, data scientists are under growing pressure from their organizations to maximize productivity?and increase their AI output, according to the company.
With ClearScape Analytics’ enhanced features and functionality, Teradata is addressing these challenges and enabling its customers to realize their full AI potential. All Teradata VantageCloud customers have access to ClearScape Analytics and these updates.
New features and functionality includes:
- Spark to ClearScape Analytics: Leverage Teradata’s tool, pyspark2teradataml, to easily convert legacy pyspark code to Teradata machine learning, eliminating the need for data movement.
- AutoML: Designed to enable data scientists to automatically train high-quality models specific to the business needs of each organization.
- KNIME Integration: KNIME, a complete no-code, low-code platform that allows users to build data science workflows?, is integrated with Teradata VantageCloud and ClearScape Analytics.
- New self-service UX enhancements: New widgets enable a self-service user experience to access a variety of queries and plotting.
- Teradata Open-source ML: ClearScape Analytics users can run popular open-source machine learning functions on VantageCloud.
"We launched ClearScape Analytics nearly two years ago to help our customers maximize the value of their data, unlock innovation, and navigate AI complexity,” said Daniel Spurling, senior vice president, product management at Teradata. “With these latest enhancements, we’re helping data scientists streamline complex processes through various self-service and automated features that are designed to allow AI models to get from training to production to enterprise-wide operationalization at scale, faster and more cost effectively.”
For more information about this news, visit www.teradata.com.