Teradata Announces ClearScape Analytics: The Most Powerful, Open, and Connected Cloud Analytics Available in the Industry
Teradata has launched ClearScape Analytics, enhancing its analytics capabilities with over 50 new in-database functions. This new offering is integrated within VantageCloud and VantageCloud Lake, providing advanced AI/ML functionalities designed to streamline data insights and operational efficiency. The features include integrated ModelOps for managing AI/ML models, allowing organizations to quickly adapt and scale their analytics. The advancements aim to help clients tackle complex challenges and accelerate digital transformations.
- Introduced over 50 new in-database time series and machine learning functions.
- Integrated ModelOps for efficient AI/ML management, enabling faster deployment of models.
- Enhanced analytics offerings across the VantageCloud platform to support complex problem-solving and data integration.
- None.
ClearScape Analytics operationalizes AI/ML at scale with the most robust in-database functionality of any analytics offering today to solve organizations’ most complex problems
ClearScape Analytics – which encompasses the same high-performing analytics that Teradata is known for but with 50+ new analytic functions – is available as part of Teradata VantageCloud and the new
These newly released features elevate Teradata’s analytics capabilities even further beyond competitors by introducing more than 50 new in-database time series and ML functions, and integrated ModelOps that are designed to rapidly operationalize AI/ML initiatives. This new functionality – in combination with the launch of
“Data is only as valuable as its ability to be synthesized for actionable, real-world insights that drive better outcomes,” said
ClearScape Analytics’ new in-database time series functions span the entire analytics lifecycle, from data transformation and statistical hypothesis tests, to feature engineering and machine learning modeling. Because these functions are built into the database, they are highly performant and require limited data movement. This can represent significant cost and friction reduction, particularly when an organization wants to apply time-series analytics on large volumes of data such as millions of products or billions of sensors. When the results of these analytic functions, such as forecasts, are stored inside the database, organizations can easily integrate that with other data. For example, a manufacturer could integrate a sensor anomaly detection score with the location of a machine and find out the location of a predicted failure, or a global retailer could integrate forecast results with price to predict revenue.
Additionally, with ClearScape Analytics, complex machine learning functions can be easily integrated into analytic pipelines – a collection of related operations that go from data preparation all the way through modeling and deployment – but packaged together to address specific problems. For example, a classification pipeline can be tweaked and tuned specifically for fraud detection that might go into a financial application, or a time series pipeline might be used for demand forecasting in a retail or manufacturing scenario. And with ModelOps embedded into ClearScape Analytics, organizations will be able to quickly scale AI/ML initiatives to unlock the full value of their investment while mitigating risk. ModelOps plays a key role in model governance and risk management, which will become increasingly important as companies send more models into production.
“Teradata’s comprehensive analytics offering has long helped organizations make the most use of their data, regardless of where it sits within an organization,” said
ClearScape Analytics Details
The recent additions to ClearScape Analytics significantly expand the overall capabilities of Teradata VantageCloud and are intended to deliver value at every stage of the analytics lifecycle.
Key benefits of ClearScape Analytics include:
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Solve more complex problems with newly added in-database analytics capabilities – *NEW*
- Teradata’s recently expanded in-database analytics library includes more than 50 new time series functions as well as a broad array of machine learning capabilities that are designed to support full end-to-end machine learning pipelines. These native functions make it possible to process machine learning at scale. Teradata VantageCloud is designed to not only support scaling massive amounts of data, but also to enable larger model complexity, including significantly more model variables, for deeper insights.
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Deploy models confidently with integrated ModelOps – *NEW*
- Despite the significant investments most organizations put into AI/ML, most predictive models are never implemented into production. Teradata VantageCloud makes it easier than ever to operationalize these investments using its governed ModelOps tool which is designed to supply the framework to manage, deploy, monitor, and maintain analytic outcomes. Teradata VantageCloud ModelOps includes capabilities such as auditing datasets, code tracking, model approval workflows, monitoring model performance, as well as alerting when models become non-performing. ModelOps can be leveraged to schedule model retraining as organizations drive towards autonomous retraining based on data drifts.
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Activate more resources by allowing experts to work with tools of their choice – *ENHANCED*
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With VantageCloud, data teams can use the languages and tools of their choice (e.g.,
Dataiku , Python, H2O.ai, etc.) which makes it easier for businesses to tap into analytic talent across the organization. Models developed outside of Teradata VantageCloud can be imported directly into Teradata VantageCloud to be run in parallel and at scale. In addition, integration with services such as Amazon SageMaker allow data science teams to tap into the expanding array of data science services in the cloud.
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With VantageCloud, data teams can use the languages and tools of their choice (e.g.,
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Drive more collaboration and efficiency with the enterprise feature store – *ENHANCED*
- Greater value can be achieved when data teams work collaboratively across the organization to drive business results. By leveraging Teradata's feature store to foster collaboration and reuse models, organizations often see a significant reduction in the amount of effort spent on data preparation and feature definition. This makes trying out new ideas easier, faster, and less expensive.
Availability: ClearScape Analytics is available today.
Note to Investors
This release contains forward-looking statements within the meaning of Section 21E of the Securities and Exchange Act of 1934. Forward-looking statements generally relate to opinions, beliefs, and projections of expected future financial and operating performance, business trends, liquidity, and market conditions, among other things. These forward-looking statements are based upon current expectations and assumptions and often can be identified by words such as “expect,” “strive,” “looking ahead,” “outlook,” “guidance,” “forecast,” “anticipate,” “continue,” “plan,” “estimate,” “believe,” “will,” “would,” “likely,” “intend,” “potential,” “designed,” “can,” or similar expressions. Forward-looking statements involve risks and uncertainties that could cause actual results to differ materially, including those relating to: the rapidly changing and intensely competitive nature of the information technology industry and the data analytics business; the timely and successful development, production, availability, market acceptance, and/or performance of new and existing products, product features and services, including
About Teradata
Teradata is the connected multi-cloud data platform for enterprise analytics company. Our enterprise analytics solve business challenges from start to scale. Only Teradata gives you the flexibility to handle the massive and mixed data workloads of the future, today. Learn more at Teradata.com.
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INVESTOR CONTACT
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christopher.lee@teradata.com
MEDIA CONTACT
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Source: Teradata
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