Teradata has introduced ask.ai, a recent generative AI (artificial intelligence) capability for VantageCloud Lake. The natural language interface is designed to allow anyone with approved access to ask questions of their data and receive instant responses from VantageCloud Lake, a complete cloud analytics and data platform for AI. By reducing need for complex coding and querying, ask.ai can increase productivity, speed and productivity for technical users and expands analytic use to non-technical roles, who can now also use Teradata’s cloud-native platform to sift through mountains of data and draw insights.
The increased use of data and analytics via VantageCloud Lake can drive creations that positively impact business results. The mainstreaming of natural language interfaces has set recent expectations for ability to gather, understand and use information, even within complex enterprise environments and outside of traditional technical roles. Implementing these generative AI capabilities and expanding access can save employee time and improve productivity.
Generative AI tools are only as useful as an enterprise’s underlying analytic capabilities and quality of data sets. The harmonised data approach and rich in-database analytics that Teradata provides in VantageCloud Lake is designed to ensure that ask.ai delivers accurate results, enabling cloud analytics for more confident decision-making at every level.
“Teradata ask.ai for VantageCloud Lake enables enterprises to quickly get to the value of their data, wherever it is, and democratises AI and ML (machine learning). Teradata was recently called out by Forrester for its strong vision and strategy that includes AI/ML at scale and now Teradata ask.ai takes this even further with a dramatic improvement in productivity and ease of use. Enterprises choose Teradata’s open and connected platform which empowers AI and ML at massive scale, harmonises data, and delivers a price-per-query advantage.” says Hillary Ashton, Teradata’s chief product officer.
VantageCloud Lake’s generative AI capabilities in ask.ai enable employees with approved access, from any function and at any level, to analyse and visualise data, analyse metadata, map tables for joining, generate code and more. Even technical personnels should experience benefits, system administrators can save time and increase productivity by simply asking questions, and data scientists may see improved development and productivity by eliminating need to manually write code. For every scenario and role, Teradata’s strong governance capabilities are designed to ensure appropriate access and security.
Main use cases include:
- Data insights: Teradata ask.ai enables data exploration and insights. Users can ask questions in natural language and receive instant responses, eliminating need to manually construct queries and scripts.
- Model and code-generation: Those without coding experience can now create code snippets by expressing their intention in natural language, democratising process of data analytics. Data scientists will see improved development by reducing need to manually write code, which is also intended to reduce syntax errors, increase code consistency, and enhance general productivity as developers can focus on high-level logic and problem-solving.
- System administration: It helps to retrieve system information related to VantageCloud Lake, such as environment and compute groups. An administrator can login and simply ask questions about system (such as, “What is the state?” or “What is the current consumption?”) as if speaking to an informed colleague.
- Metadata analysis: Teradata ask.ai can provide information on table design to explore datasets and schemas, helping users understand the nuances in data attributes and existing relationships between datasets. This helps to understand the data available for building analytics, providing deeper insights.
- Help: Any user can ask for help on variety of topics, including general documentation, questions about what Teradata functions exist in a particular database, detailed descriptions for a particular function, SQL (structured query language) generation for that function, and more.
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