Teradata has expanded its portfolio of cloud-native tools with the launch of the Teradata Vantage Platform Cloud Lake and the analytics tool Teradata ClearScape Analytics. The first focuses on extending the Teradata Vantage data lake to offer a more elastic cloud deployment model, and is compatible with software-as-a-service deployment models. As for the second, it helps companies take advantage of the development workloads of Artificial Intelligence, machine learning and new analytics.
The combination of cloud-native databases and analytics enables streamlined data science workflows. It also offers support for ModelOps and improves component reuse. Everything from a single platform. Teradata assures that in both products it will combine new architectures typical of the cloud with the governance, simplicity and cost controls of a consolidated offer. In addition, both innovations take advantage of Teradata’s research and development in intelligent scaling, allowing users to scale based on their actual resource usage rather than statistical metrics.
VantageCloud Lake is designed to take advantage of fully isolated and elastic multi-computer clusters as well as scalable, elastic, durable and cost-optimized object storage. Like Amazon Simple Storage Service (Amazon S3). With this new platform, Teradata customers can launch cross-department projects leveraging core data, while eliminating the need for “shadow” IT systems by covering the needs of exploratory projects and custom requests. It offers both workload management and workload isolation at scale.
this platform is now available on AWSand Teradata claims that will be available in the main cloud services in early 2023. Both innovations promise users a lower total cost of ownership, as well as direct support for more types of analytics processing. So, for example, ClearScape Analytics includes a grid of questions, governance, and financial visibility. This will also simplify predictive and prescriptive analytics.
ClearScape Analytics includes database-integrated time series capabilities that take care of tuning the entire analytics lifecycle. From data transformation and statistical hypothesis testing to machine learning modeling and feature engineering. These capabilities are built directly into the database, improving performance and eliminating the need to move data. In this way, the costs and problems that arise when analyzing a large volume of data from millions of sales or from Internet of Things sensors can be reduced.
With ClearScape Analytics, which It is now available, data scientists can code analytic functions into prebuilt components that can be reused by other analytics, machine learning, or AI workloads. ClearScape Analytics has 50+ new time series built in database and machine learning functionsas well as integrated ModelOps, which makes it designed to operationalize machine learning and Artificial Intelligence initiatives.
This new feature, in combination with Teradata VentageCloud Lake, is intended to give customers the ability to activate big data and solve complex business problems with a robust library of open and connected analytics tools built for autonomy, easy access and real-time data.
