Name: Harness a Lake-Centric Modernization Strategy for Al Adoption
Start: 2024-03-06T16:30:00Z
End: 2024-03-06T16:31:03.000Z
Location: BrightTALK
Rating: 4.5

At Teradata, we believe that people thrive when empowered with trusted information. That’s why we built the most complete cloud analytics and data platform for AI. By delivering harmonized data, Trusted AI, and faster innovation, we uplift and empower our customers—and our customers’ customers—to make better, more confident decisions. The world’s top companies across every major industry trust Teradata to improve business performance, enrich customer experiences, and fully integrate data across the enterprise.

Enabling everyone in the enterprise to make data-driven decisions has been a challenge. The friction of learning about data structures and accessing languages like SQL are frequent barriers.

Teradata’s MCP server eliminates these friction points through a natural language interface that leverages AI agents. This provides unprecedented semantic access to enterprise data. Built on Teradata Vantage®, the MCP server and agentic framework enable querying, analysis, and management of data with full context. It turns users into drivers of trusted knowledge. 

Watch this replay for an exclusive demo of Teradata’s MCP server, integrated with the latest agentic toolset. Discover how this modular, AI-powered framework transforms enterprise data management through intelligent automation and secure, efficient operations.

You’ll learn how to:

- Democratize exploratory data analytics across your entire data estate
- Use agentic AI to simplify and automate data platform administration
- Rapidly deploy agentic AI applications targeted to your own business data and processes
- Seamlessly integrate enterprise feature and vector stores into your agentic architectures

Build AI Agents on Enterprise-Scale Data Using Teradata MCP Server

Discover how AI is transforming the customer experience—from smarter engagement to real-time personalization.

Watch this replay and find out more about the design of AI/ML pipelines at scale with guest Martin Hillebrand, a data scientist with extensive hands-on experience in operationalizing machine learning.

We begin with tdprepview, a Python library that automates data preparation inside the database. By defining pipelines in a scikit-learn–like syntax, it generates SQL views for preprocessing tasks such as imputing, encoding, scaling, and dimensionality reduction. This approach eliminates costly data movement, ensures consistency, and allows pipelines to scale to very large datasets.

From there, we explore ClearScape Analytics Experience, which shows how the next stages of the workflow can be managed. This includes training an open-source model, converting it to an open-exchange format like ONNX and deploying this with Bring Your Own Model in-database at scale.

Together, these practices create an end-to-end path from raw data to pipelines that are efficient, reproducible, and built for scale.

Scaling AI/ML Pipelines with In-Database Analytics

As enterprises accelerate AI adoption, they're grappling with the technical reality that the growth of unstructured data will drive the need for billions of vectors and cost-effective solutions to store and analyze this data at scale. This technical revolution affects all customers, including those in highly regulated industries that require on-premises solutions to meet regulatory, compliance, and data sovereignty standards. For these customers—as well as those seeking tighter control over infrastructure costs—an on-premises AI factory solution is purpose-built to address their unique requirements.

Join us and we'll show how Teradata and NVIDIA enable AI factories—purpose-built, on-premises AI solutions tailored for regulated industries and organizations that demand greater control, enhanced security, and cost predictability. See how an AI factory delivers a full-stack AI environment seamlessly integrating structured and unstructured data essential for powering generative AI, agentic AI, and Retrieval-Augmented Generation (RAG) applications.

See how to:
• Build end-to-end AI-powered analytics and AI-augmented use cases
• Execute secure RAG workflows
• Seamlessly deploy and manage AI models

Watch it now on-demand!

Enabling AI Factories with Teradata and NVIDIA

As generative AI and agentic AI strategies continue to evolve, enterprises are looking for ways to extract insights and value from unstructured data, which will account for over 80% of global data in 2025. The growth of unstructured data will drive the need for billions of vectors and the need for cost-effective solutions to store and analyze this data at scale. This includes customers in highly regulated industries that require an on-premises solution due to regulatory, compliance, data sovereignty standards or customers who wish to closely manage infrastructure costs.
This exclusive live webinar, featuring a fireside chat with experts from Teradata and Nvidia, introduces AI On-Prem, a purpose-built AI/ML solution with an integrated Enterprise Vector Store. AI On-Prem combines Teradata’s proven analytics and AI expertise with the power of NVIDIA AI Enterprise to enable customers to maximize their GPU investments.
Join executives from Teradata and NVIDIA for our LinkedIn Live session “Unlocking the Potential of AI On-Prem: A Secure, Innovative On-Premises AI Solution.” to gain valuable insights into how enterprises can enable on-premises AI innovation while managing complexity, compliance, and cost.
During this live discussion, you’ll learn more about: 
• What C-suite executives are saying about Private AI 
• How to address the growing demands for faster AI ROI through the powerful integration of Teradata and NVIDIA
• How leading enterprises need enterprise-scale vector stores to drive AI-driven results
• How Teradata addresses the unique AI requirements of on-premises customers

Watch it now on-demand!

Unlocking the Potential of Teradata AI Factory: A Secure, Innovative On-Premises AI Solution

Enterprise organizations face critical challenges as they move from traditional analytics to AI/ML workloads. Legacy platforms often create performance bottlenecks, scalability issues, and complex multisystem environments requiring high operational effort without adequate computational gains. These inefficiencies hinder competitiveness and strain resources.

Teradata resolves these problems by combining traditional analytics, advanced analytics, and AI/ML workloads on one platform. This eliminates system fragmentation, simplifies operations, and creates a trusted data foundation essential for AI success. Organizations benefit from better performance with fewer infrastructure demands and less reliance on specialized expertise.

In this demo, we highlight Teradata's automated migration and workload optimization tools designed to help enterprises shift to modern, AI-ready architectures while maintaining data integrity and governance:

- DDL Converter: Automatically translates legacy database structures to Teradata’s platform, reducing manual work and accelerating migration.
- Data Validation Tool (DVT): Maintains data accuracy, completeness, and consistency throughout the transition.
- Workload Optimization: Routes various workload types—analytics to AI/ML—to optimal compute resources while preserving governance.
- Migration Planning Tools: Analyze current infrastructure, uncover optimization opportunities, and guide modernization strategies.

Watch the session on demand and discover how effortless transformation can be.

Simplify Platform Modernization With Automated Migration Tools

Join Alex Wurm, analyst at Nucleus Research, and experts from Teradata for a conversation about what really matters: ROI. Drawing from in-depth interviews with Teradata customers across industries like financial services, telecommunications, manufacturing, and healthcare, Wurm will share what separates high-performing data and AI initiatives from those that stall out.

In this session, you’ll learn:  

- How leading organizations are cutting model development time by up to 51% and boosting data science productivity
- Why customers are achieving 3x ROI and payback in under a year—and how they're doing it
- Where Teradata delivers the most measurable value (hint: it's not just in IT savings)
- How to reframe technical initiatives in terms of business impact so stakeholders get on board 

Whether you’re kicking off a new project or need to demonstrate impact from an existing one, this session will give you practical, independent insights to lead with value and win support.

The ROI Conversation: Framing Data & AI Projects for Executive Buy-In

During this event, you’ll learn how to accelerate text analytics with teradatagenai, a Python library that brings in-database AI capabilities to Teradata VantageCloud on Amazon Web Services (AWS). See how you can apply language models (LMs) and large language models (LLMs) to unstructured data quickly and securely—reducing the need for data movement while boosting scalability and performance. 
 
Organizations often struggle to extract insights from unstructured data when relying on manual processes, fragmented tools, or complex infrastructure. Teradatagenai simplifies gen AI text analytics by enabling secure, in-database processing of unstructured data—such as PDFs, emails, and transcripts—with flexible model options from Hugging Face and Amazon Bedrock. 
 
In this event, you’ll see how you can streamline text analytics workflows, reduce operational overhead, and unlock AI-driven insights faster—without moving data. 
 
•                Deploy Hugging Face and Amazon Bedrock models using the TeradataAI() class to simplify model integration and accelerate gen AI workflows. 
•                Apply diverse text analytics tasks—including sentiment analysis, classification, entity recognition, and personally identifiable information (PII) masking—directly within your database. 
•                Reduce complexity and operational costs by minimizing data movement and leveraging GPU acceleration inside the analytics environment. 
 
Register now to not miss out!

Simplify text analytics using AI with AWS and Teradata

Maintaining high data quality and consistency across various sources is crucial but challenging. Data engineers must manage complex workflows, ensure data quality, and scale operations to meet growing demands, including leveraging generative AI. Efficient real-time data integration is essential for timely insights and decision-making, yet it remains a significant challenge—despite robust data workflow technologies.

Teradata’s modern data stack integrations with third-party tools are intended to accelerate the building of data pipelines, increase productivity by freeing data engineers from repetitive work so they can innovate faster to drive profitable growth.

These tools, along with support for open table formats like Iceberg and Delta Lake, empower teams to simplify data extraction and loading into centralized storage solutions to seamlessly integrate and manage data across platforms.

View the live demo of a use case featuring Teradata’s newest modern data stack integration with Fivetran. We’ll show how this integration and others work together to simplify data engineering tasks and deliver a complete pipeline on Teradata Vantage®.

See how to:

- Process and deliver data in real time with Fivetran
- Transform raw data into meaningful insights with dbt
- Ensure data accuracy, consistency, and reliability throughout the pipeline
- Handle increasing data volumes to meet growing demands

Demo 18: Transform Data Pipelines for AI Insights With Teradata, Fivetran, and dbt

Sequoia Insight “Healthcare Data Reimagined”

Join Jeff Eckhaus, Chief Product Officer at Sequoia Insight and Greg Hinds, Vice President – Architecture at Sequoia Insight, for a demo of Sequoia Insight's RaaS Solution (Regulatory as a Service)

Bonus Demonstration - Google Cloud Industry AI Symposium

We kicked off the 2025 virtual Teradata Industry AI Symposium with Naveen Punjabi, Director, Analytics & AI ISV Partnership at Google Cloud, as he unveiled how Teradata and Google Cloud are transforming industries through AI and data innovation.

Welcome from Google Cloud - Google Cloud Industry AI Symposium

Why Teradata DataDNA™ matters: In today’s AI-driven world, understanding where your data comes from and how much you can trust it is more critical than ever. 

Teradata DataDNA™ helps you trace data lineage, assess data trustworthiness, and gain visibility into how your data is used across platforms. This service empowers you to confidently train LLMs and build AI solutions on a foundation of trusted data… so, the result is trusted AI.

Bonus Demonstration – Teradata DataDNA™ Service - Google Cloud Industry AI Symposium

Agentic AI, Vector Databases

A thought-provoking conversation between Lesley Scholes, Vice President, Americas Industries Sales at Teradata and Patrick Smith, Head of AI Specialist Engineers – TMEG at Google Cloud, exploring key Telco trends like Agentic AI and vector databases.

Bonus: Industry Trends Spotlights 2 - Google Cloud Industry AI Symposium

Accelerating Insights from Unstructured Data with Teradata Vantage and Google Gemini 

Calling all data scientists and developers in the audience:
80% of global data is unstructured, including text, emails, reviews, and transcripts. For years, organizations have struggled to turn this data into actionable insights using slow, manual processes. What if these insights could be generated in just hours?

In this breakout recording, we demonstrate how generative AI tools like Google Gemini and Teradata Vantage are transforming how businesses analyze unstructured data. Google Gemini’s Large Language Models (LLMs) provide quick insights, while Teradata Vantage ensures these insights are operationalized across large enterprise datasets with scalability and seamless integration.
Watch this recording to learn how this powerful combination is revolutionizing enterprise data workflows and accelerating insight generation.

Ep7: Developer Breakout - Google Cloud Industry AI Symposium

Join Praveen and Thomas for an executive summary of Day 3 – the Telecommunications and Media CX | AI Day at the Industry AI Symposium. 

In this session, you will find the Possible 2025 waiver code “SPRO25LA“ for a free event registration at https://www.teradata.com/events/possible.

Ep6 Telco: Wrap-Up and Closing - Google Cloud Industry AI Symposium

Telefónica Spain: Innovating with Data & AI in B2B Segment

This session highlights the crucial role of data and AI innovation in driving business and technology development, always with a strong customer-centric approach. 

It also features a use case with Würth Spain, demonstrating the significance of Edge Computing for AI.

Read more in our blog article “Unlocking the value of 5G to deliver business outcomes” at https://www.teradata.com/insights/cloud-data-analytics/unlocking-the-value-of-5g

Ep5 Telco: Customer Presentation (Telefonica Spain) - Google Cloud Industry AI Symposium

Seeing the Unseen: How Hybrid Customer Data is Transforming CX with AI

What if you could understand your customers so well that you could predict their needs, frustrations, or even life events—before they tell you? In this must-see demo, Yann and Denis showcase how Teradata ClearScape Analytics is making that vision a reality.

This demo brings to life the power of hybrid customer data—the fusion of structured data (like transactions and call records) with unstructured data (like emails, voice calls, and social media). You’ll see how vector embeddings and semantic search can uncover hidden patterns in customer behavior, enabling smarter, faster decisions across industries like Telco and Media.

From identifying churn signals to decoding customer sentiment in real time, this demo shows how AI can turn scattered data into actionable insights. And the best part? You don’t need to be a data scientist to follow along.

Whether you're in marketing, operations, or strategy, this session will open your eyes to how AI can elevate customer experience, drive retention, and personalize engagement at scale.

Ep4 Telco: Demonstration - Google Cloud Industry AI Symposium

Maximizing Value Potential Using Advanced Analytics at stc

Discover how Saudi Telecommunication Company (stc), one of the region’s leading telecom providers, is driving innovation across customer engagement, network planning, and operational efficiency using advanced analytics and AI.

In this session, you’ll learn how stc applies next-best engagement and next-best offer analytics to drive upgrades, upsells, cross-sells, and reduce churn—delivering highly personalized experiences at scale. Using Teradata Vantage™ and ClearScape Analytics™, stc integrates structured and unstructured data across voice, digital, and mobile channels to uncover real-time behavioral insights.

 From Generative AI-powered journey analytics that improve first-call resolution to computer vision on satellite images that informs 5G and fiber expansion and unlocking new stream of insights from retail videos aiming to uplift customer experience, stc is redefining how data fuels decision-making.

The result? Smarter campaigns, optimized infrastructure rollout, and measurable business impact. stc has not only met but exceeded its KPIs, proving the power of data-driven personalization in telecom.

If you're looking to turn customer data into top-line growth, this is a session you won’t want to miss.

Read more about this customer success story here: https://www.teradata.com/customers/stc-innovating-in-ai

Ep3 Telco: Customer Presentation (stc) - Google Cloud Industry AI Symposium

From Complaints to Clarity: Uncovering Hidden Trends in Telco Customer Feedback 

This session demonstrated how Teradata helps Telcos turn customer complaints into valuable insights. By analyzing customer feedback, we revealed hidden trends and patterns, allowing companies to understand and address customer experience challenges more effectively. We showed a demo of an interactive dashboard that provides a clear, real-time view of these trends, helping decision-makers improve customer satisfaction.

Discover how Teradata's unique GenAI based approach ensures reliable and consistent results, making it an essential tool for the telecommunications industry.

Ep2 Telco: Use Case - Google Cloud Industry AI Symposium

8:30 a.m. PT/ 11:30 a.m. ET/ 4:30 P.M. GMT

For companies looking to adopt AI/ML at enterprise scale, streamlined access to data is critical. And yet, many companies are contending with a tangled web of data silos and technologies,  leading to data sprawl, mounting technical debt, and bloated storage costs— all of which and hamper innovation. And new advances in AI/ML will only add to the complexity. 

 To address this problem, the most successful companies are adopting a lake-centric approach. A cloud-based lakehouse pairs the robust data management and processing ability of a data warehouse with the flexibility, scalability, and cost-effectiveness of a data lake, enabling you to accelerate innovation and gain a critical competitive edge. 

In this live webinar moderated by veteran technology journalist Kate Russell, GigaOm Analyst Andrew Brust will be joined by Teradata’s Vice President of Technology, Martin Willcox, and David Jerrim, Director of Ecosystem Architecture, to share how to  unlock the full power of your data with a lake-centric modernization approach. Tune in to learn how to: 

- Consolidate all your data, compute, and AI/ML technologies into a single cloud environment 
- Manage tech debt and harmonize data across the entire enterprise 
- Maximize workload efficiency 
- Achieve transparent financial governance with trusted AI capabilities

Harness a Lake-Centric Modernization Strategy for Al Adoption

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Harness a Lake-Centric Modernization Strategy for Al Adoption

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Teradata – Enterprise Data Analytics