Teradata unveils AI/ML boosts for ClearScape Analytics platform

Teradata has announced new features and productivity enhancements to its ClearScape Analytics platform, aimed at enhancing AI/ML capabilities for its users.

The company stated that the new features aim to assist organisations in maximising the return on their AI/ML investments and improving data science productivity to achieve business outcomes more efficiently. In recent years, the complexity of AI tools and platforms, alongside the rapid proliferation of data and analytic platforms, has led to inefficient AI/ML processes. This has prevented companies from obtaining comprehensive insights from their data and increased the costs associated with large-scale AI operationalisation. Data scientists are facing mounting pressure from their organisations to boost productivity and increase AI output, a process often hampered by inefficient data preparation, manual machine-learning processes, and the overall challenges of AI operationalisation.

The release showcased enhancements to ClearScape Analytics designed to address these challenges. All Teradata VantageCloud customers have access to the new features, which are intended to enable users to realise their full AI potential.

One of the key updates includes the introduction of the pyspark2teradataml tool, which facilitates the conversion of legacy pyspark code to Teradata machine learning without the need for data transfer. This feature aims to reduce complexity and costs by eliminating the necessity for data exportation from VantageCloud to Spark platforms. The tool is expected to aid in operationalising AI at scale, leveraging VantageCloud's workload management, security, and data integration capabilities. It also supports a hybrid-cloud environment, which can be advantageous for customers with Spark-based investments.

Another new feature is AutoML, designed to allow data scientists to automatically train high-quality models tailored to specific business needs. This automation aims to save time and extend the capability to non-technical business users, enabling them to build AI/ML models without extensive technical knowledge.

Teradata has also integrated KNIME, a no-code, low-code platform for building data science workflows, with Teradata VantageCloud and ClearScape Analytics. The integration is expected to accelerate AI initiatives by providing a user-friendly interface suitable for a range of technical and non-technical users. This integration leverages the simplicity of KNIME alongside the scalability of VantageCloud.

New self-service UX enhancements are set to improve user experience by introducing widgets that facilitate self-service queries and plotting. This feature is intended to enhance ease of use and mitigate the risk of errors by allowing data access without coding.

Additionally, the update allows ClearScape Analytics users to run popular open-source machine learning functions on VantageCloud. This feature is designed to offer ease of use, scalability, and performance for open-source functions, while also enabling the operationalisation of trained open-source models stored in VantageCloud.

"We launched ClearScape Analytics nearly two years ago to help our customers maximise 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 operationalisation at scale, faster and more cost effectively."