Name: Demo 16: Enhancing Sports Fan Engagement With Data-Driven Insights
Start: 2025-04-22T14:45:00Z
End: 2025-04-22T14:45:34.000Z
Location: BrightTALK

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.

In today’s data-driven world, automating complex decision-making processes is a key competitive advantage. Multi-agent AI systems—where multiple specialized AI agents collaborate to solve problems—are at the forefront of this transformation.

This session will provide a comprehensive overview of how to design, build, and deploy multi-agent systems on Google Cloud, leveraging the power of Google’s Gemini Enterprise, Google AgentBuilder, and the analytical capabilities of the Teradata MCP server, all orchestrated through Vertex AI Agent Engine.

We will explore the core components of modern multi-agent architecture, including Google’s Agent Development Kit (ADK), the open Agent-to-Agent (A2A) communication protocol, and Teradata MCP Server. Using a conceptual example of a customer journey analysis system, we will demonstrate how specialized agents can collaborate to transform natural language queries into actionable business insights.

Key Takeaways:

How to design, build, and deploy multi-agent systems on Google Cloud

Leveraging Gemini Enterprise, AgentBuilder, and Vertex AI Agent Engine for scalable solutions

Integrating Teradata MCP Server for advanced analytical capabilities

Understanding the Agent Development Kit (ADK) and Agent-to-Agent (A2A) communication protocol

Practical example: customer journey analysis powered by multi-agent collaboration

Architectural patterns and best practices for enterprise-ready multi-agent systems

Inspiration to apply multi-agent AI technology to real-world business challenges

Register today!

Collaborative AI in Action: Foundations for Multi-Agent Systems with Google Cloud and Teradata

2025 was a year of acceleration. As enterprises pushed toward autonomy, five key themes emerged as the backbone of transformation—from AI adoption and agentic workflows to model governance, data sovereignty, and customer intelligence. This webinar offers a high-level look at what mattered most in 2025—and what’s next.

We’ll reflect on the milestones that shaped the year, share expert insights on the technologies gaining traction, and close with a forward-looking vision for 2026 from Teradata’s new chief product officer.

In this session, you'll:

- Understand the impact of five trends that dominated enterprise strategy in 2025
- Hear directly from Teradata experts on what’s driving real business impact
- Learn how agentic AI, model management, and data sovereignty are evolving
- Discover how autonomous customer intelligence is reshaping engagement
- Leave with a strategic lens on what’s coming in 2026

Whether you're shaping enterprise strategy or scanning the horizon, this session will help you connect the dots—and stay ahead of the curve.

Spotlight 2025: The Big Five Shaping Autonomous Enterprise

In this recorded live demo, we'll demonstrate how business users can design, deploy, and manage autonomous customer intelligence—without needing deep technical expertise. This session will walk through how intuitive interfaces, natural language capabilities, and real-time decisioning come together to deliver hyper-personalized, scalable customer engagement across channels.

Autonomous Customer Intelligence - Live Demo

AI That Works Where You Work: resilient hybrid and on-prem AI architectures that deliver results.
AI Where You Need It: Hybrid & On-Premise Excellence
AI That Works Where You Work: Discover how resilient hybrid and on-prem architectures are powering real-world AI success across industries.

Watch the replay and learn from our Teradata expert as he unpacks how to deploy trusted, scalable AI—whether in the cloud, on-prem, or at the edge.

- Real-world use cases
- Enterprise-ready strategies

Don’t miss this chance to future-proof your AI strategy. Watch the replay today

AI Where You Need It: Hybrid & On-Premise Excellence

Telecommunications providers are under increasing pressure to deliver innovation, efficiency, and new customer value—while keeping costs under control. Agentic AI has the potential to fundamentally transform the way telcos operate, but only if it is applied with the right strategy, governance, and execution.

In this LinkedIn Live session, two of Teradata’s global experts will share their perspectives on how to move beyond experimentation and drive measurable business impact with Agentic AI:

Laurent Laisney, Global Telecoms Industry Specialist, will outline the strategic opportunities of Agentic AI in telecoms—covering use cases, dos and don’ts, and how operators can achieve early ROI.

Dr. Chris Hillmann, Global AI Lead, will dive into the practicalities of implementation—what it takes to deploy Agentic AI effectively, how to scale responsibly, and how to turn pilots into enterprise-wide value with Teradata´s Trusted AI solutions.

This interactive session is your chance to hear directly from industry and AI leaders, ask questions live, and gain actionable insights to accelerate your AI journey with confidence.

Agentic AI in Action: The Telco Advantage

Personalization isn’t just a trend — it’s the new standard for customer and patient experiences alike. Whether it’s a healthcare provider tailoring engagement to improve outcomes, or a retailer delivering relevant product recommendations, success depends on turning vast amounts of data into timely, trusted, and actionable insights.

Join Teradata, AWS, and Qlik for a dynamic session that reveals how leading organizations are scaling hyper-personalization across industries. With a spotlight on healthcare, you’ll see how trusted data, real-time analytics, and scalable AI can transform the way organizations connect with individuals — patients, members, or customers — at the moments that matter most.

In this webinar, you’ll learn how to:

- Build a trusted data foundation with Teradata to fuel AI-ready insights
- Deliver real-time, data-driven actionable insights with Qlik.
- Deploy scalable, production-ready AI with AWS tools like Amazon Personalize

Whether you’re focused on marketing, patient engagement, customer experience, or data strategy, this session will show you how to connect the dots among data, analytics, and AI—so you can deliver the right experience, to the right person, at the right time.

Hyper-Personalization at Scale: Turning Trusted Data into Timely CX with Teradata, AWS & Qlik

Leading South Asian financial services and retail bank United Bank Limited (UBL) has implemented an on-premises lakehouse architecture to scale artificial intelligence. The new lakehouse architecture encompasses IntelliFlex® and Dell Object Store, while consolidating and migrating a Cloudera data lake. The AI-ready architecture will advance customer experience and risk mitigation use cases to improve banking experiences for over 11 million customers. In this session, United Bank Limited will share its strategy and journey of an on-premises lakehouse architecture to prepare and enable its AI roadmap via self service and democratized data.

United Bank Limited Implements a Lakehouse Architecture With Teradata and Dell on Its Journey to AI

Mission critical asset performance monitoring relies on data readiness and analytics availability. While the former requires high throughput ingestion capabilities and heavy downstream transformations of heterogenous data to create actionable information through different AI techniques (multi-domain sensor time-series data coupled with business data), the latter must deliver the resulting information in a timely manner with proper user experience through different interrogation techniques including GenAI. In the current presentation we discuss the continuous integration and improvement of the AI process to achieve effective decision making in the context of Prognostics and Health Management for higher asset reliability and availability.

Mission Critical Asset Performance Monitoring Using Industrial AI

Are you ready to explore how cutting-edge geospatial tools empower sustainable development in Brazil? Agro-business stands as a cornerstone of Brazil’s economy, driving growth and prosperity across rural regions. Sicredi, one of the top 10 financial institutions in Brazil, plays a pivotal role in supporting the expansion of agro-business through credit lending. However, with this expansion comes the obligation to verify rural property boundaries (over 8 million) and their proximity to over 2,000 protected forests to ensure compliance with stringent environmental laws. Previously, Sicredi processed and analyzed rural properties against protected forest areas using Databricks. Processing in Databricks often took over 4 hours and resulted in outdated insights for Sicredi credit lenders to take action. Given the reliance of each banking branch on this data, having accurate and timely information was crucial to assessing credit risk effectively. Teradata’s geospatial capabilities transformed Sicredi’s operations by significantly reducing processing times, reducing costs, and enabling trusted credit decisions that comply with environmental regulations. This breakthrough not only enhances operational performance but also positions Sicredi as a leader in sustainable development, earning it prestigious environmental finance and sustainability awards.

Using Teradata’s Geospatial Tools To Protect Forests, Reduce Credit Risk, and Create Sustainable Development in Brazil

In today's data-driven world, the ability to automate complex decision-making processes is a key competitive advantage. Multi-agent AI systems, where multiple specialized AI agents collaborate to solve a problem, are at the forefront of this transformation. This session will provide a comprehensive overview of how to design, build, and deploy multi-agent systems on Google Cloud, leveraging the power of Google's AgentSpace, Google AgentBuilder and the analytical prowess of the Teradata MCP server.

We will explore the core components of a modern, multi-agent architecture, including Google's Agent Development Kit (ADK) and open Agent-to-Agent (A2A) communication protocol along with Teradata MCP Server. Through a practical (conceptual) example of a customer journey analysis system, we will demonstrate how specialized agents can work together to transform a natural language query into actionable business insights.

Attendees will leave this session with a clear understanding of the architectural patterns and best practices for building their own multi-agent systems on Google Cloud with Teradata, and will be inspired to explore how this powerful technology can be applied to their own business challenges.

Building Collaborative AI: Orchestrating Multi-Agent Systems with Google Agent Builder, Google AgentSpace, and Teradata

Join an interactive fireside chat with Verizon, discussing how the leading media and communications provider is approaching platform innovations across hybrid cloud. Verizon’s Head of Data and AI Enablement, Arvind Rajagopalan, and Teradata’s Director of AMS Platform Architecture, Matthew Beaver discuss how teams at Verizon are driving efficiency in its AI and data initiatives.

Architecting Tomorrow’s AI and Knowledge Platforms at Verizon

Join us for an exclusive look at Teradata’s AI strategy and product roadmap, focused on delivering transformative outcomes across industries. We’ll showcase innovations including AI Workbench, AgentBuilder, and AI apps designed to simplify user experiences. Learn how Teradata enables scalable, on-demand compute, industry-best performance for OTF data products, and a unified, intelligent data foundation—powering the shift from traditional EDW to a modern AI-driven platform.

Accelerating AI Outcomes: Teradata’s Strategy and Product Roadmap

Teradata’s Chief Technology Officer and VP of Advanced Research lead this keynote on the path to AI autonomy. They share practical steps and visionary insights for organizations aiming to achieve self-driving, trusted AI systems.

Journey to AI Autonomy: Louis Landry

In this fireside chat, Teradata’s Senior Director of Product Strategy and Google Cloud’s Digital Transformation and Generative AI Innovation Leader to explore how enterprises can unlock value by integrating with Google Cloud’s AI suite. The discussion highlights Google’s leadership in AI innovation and Teradata’s commitment to delivering trusted, scalable solutions. Together, they showcase how combining Teradata’s enterprise-grade analytics with Google’s cutting-edge AI technologies accelerates time-to-value and drives meaningful business impact.

Fireside chat with Google

This interactive keynote features Teradata’s SVP of Worldwide Analytics Sales, dbInsight’s Principal, and Halfpipe Systems’ Principal, tackling tough questions about AI agents. The session demystifies AI agent technology, addressing common concerns and exploring future possibilities.

The Questions You Were Afraid to Ask About AI Agents (and More)

Leaders from AWS and the New York Giants join Teradata’s Richard Petley to discuss their joint AI-powered solution. Teradata’s enterprise-grade platform, combined with AWS’s scalable cloud infrastructure, enables the Giants to unify data across ticketing, marketing, e-commerce, and concessions. Together, they deliver secure, resilient insights through an AWS customer warehouse connected to Teradata’s QueryGrid.

Fireside chat with AWS and the New York Giants

In this fireside chat, a General Manager at Microsoft Azure shares how Microsoft and Teradata are deepening their collaboration to empower customers through trusted, secure, and scalable digital platforms. The Microsoft specialist team plays a pivotal role in guiding partners to build impactful solutions on Microsoft technologies—solutions that drive measurable outcomes and innovation.The session highlights how evolving go-to-market strategies are unlocking greater value from Teradata’s offerings, with a focus on operating at the speed of trust. Security remains foundational to every initiative, reinforcing Microsoft’s commitment to being a reliable and forward-thinking partner in the journey toward digital transformation.

Fireside chat with Microsoft

Focused on accelerating data innovation, this session brings together Teradata’s Chief Product Officer and SEBI’s Chief General Manager to discuss transformative strategies. The keynote emphasizes how organizations can harness Teradata’s technology to propel data-driven growth and efficiency.

Driving Data Innovation on Teradata: Sumeet Arora

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

Demo 21: Build AI Agents on Enterprise-Scale Data Using Teradata MCP Server

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!

Demo 20: Enabling AI Factories with Teradata and NVIDIA

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.

Demo 19: Simplify Platform Modernization With Automated Migration Tools

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

Organizations are under increasing pressure to quickly deploy valuable generative AI applications and demonstrate a strong return on investment (ROI). However, deploying gen AI comes with significant challenges such as selecting the right large language model (LLM), while ensuring data security, privacy, and cost control. 

The Bring Your Own LLM (BYO-LLM) capability within Teradata VantageCloud offers a streamlined approach to experimentation, deployment, and performing inference using LLMs directly within the database. This capability reduces complexity and costs, while ensuring that developers and data professionals retain complete control over their data in a secure, flexible and trusted environment. 

Join our live demo to see how to bring Hugging Face open-source language models into Teradata VantageCloud and supercharge unstructured text analysis with GPU acceleration — right where your data already lives. 

We will explore: 

- Setting up VantageCloud: Configuring analytic GPU compute groups and connecting using teradataml
- Model deployment and inference: Step-by-step guide on downloading and deploying the 'tner/roberta-large-ontonotes5' model from Hugging Face and conducting batch inference jobs for entity recognition
- Extracting insights from unstructured data: Demonstrating how to analyze texts, emails, PDFs, customer communications, call center transcripts, and other forms of unstructured data to extract valuable insights

Demo 17: Unstructured Text Analysis With BYO-LLM and NVIDIA GPUs on VantageCloud

Agentic and generative AI use cases rely on vast amounts of unstructured data, including text, audio, PDFs, and videos, often involving millions of objects. This could result in billions of inferences. These use cases also need to leverage structured data for operationalization purposes.

Teradata Enterprise Vector Store efficiently handles both structured and unstructured data, enabling companies to scale and build toward an agentic AI future for dynamic customer experiences and more. By integrating seamlessly with enterprise data, it reduces data movement and maximizes value. 

Join our live demo to see Teradata’s Enterprise Vector Store in action as we demonstrate a generative AI use case for state-of-the-art call center augmentation, featuring our partnership with NVIDIA.  

Learn how to: 

- Ingest PDF documents
- Generate embeddings 
- Perform intelligent search and retrieval
- Integrate with operational data

Demo 15: Agentic and Gen AI Use Cases With Teradata Enterprise Vector Store

Open LLMs offer a transformative solution for many use cases. Teradata's innovative capabilities allow you to implement generative AI within Teradata VantageCloud Lake environments through Bring Your Own LLM (BYO-LLM). With this technology, you can deploy open-source LLMs in the same environment where data resides, utilizing scalable, dependency-isolated, and highly parallelized environments. During this demo, you'll learn how to create your Open Analytics Framework environment in VantageCloud Lake, deploy open-source LLMs from Hugging Face or other open-source LLM publishers or aggregators and seamlessly operationalize your deployed LLMs for inference on your unstructured data.

Demo 14: Leverage the Power of Open LLMs With VantageCloud

In this demo, we'll discuss how to overcome this data fragmentation and accelerate AI innovation in a siloed data and application environment. With Teradata VantageCloud Lake and QueryGrid, organizations can integrate and leverage all their data, better positioning them to adapt, evolve, and thrive in the face of uncertainty. This demo features QueryGrid and Open Table Formats (OTF).

Demo 13: Overcoming Data Fragmentation to Unlock AI Innovation

Organizations face significant challenges in the analytics lifecycle. Teradata's ClearScape Analytics offers a robust solution to these challenges with a comprehensive suite of in-database functions designed to accelerate analytics at scale. In this demo, we'll explore ClearScape Analytics functions and demonstrate practical applications.

Demo 12: Drive Fast, Reliable Insights With In-Database Analytics

This recorded demo shows how Teradata can help you streamline data preparation and optimize ML workflows so you can deliver impactful insights to maintain your competitive edge. It showcases Enterprise Feature Store (EFS), AutoML, and Widgets.

Demo 11: Boost Data Science Productivity With Scalable AutoML and Code Automation

In this demo, we'll demonstrate how you can use VantageCloud's generative AI capabilities to improve customer retention by quickly analyzing and resolving customer complaints. Although this example is related to banking, the use case is applicable to many other industries. This content is also available at https://www.teradata.com/resources/fast-track-customer-complaint-resolution.

Demo 10: Fast Track Customer Complaint Resolution with Gen AI

This demo features Teradata's new conversion tool, pyspark2teradataml, to seamlessly migrate PySpark workloads to an equivalent format that works in Teradata Vantage with minimal additional coding. During the demo you will see a step-by-step implementation of a workflow using a PySpark-based use case entirely on a Vantage system. With this approach, data scientists can leverage Teradata's truly multi-cloud architecture to develop, train, and score models while limiting data movement from tools such as Databricks.

Demo 9: Migrate PySpark Workloads to Teradata to Fast Track AI/ML, Minimize Costs

This 30-minute live demo will demonstrate VantageCloud Lake's financial governance features and show you how to use the Console to gain greater visibility into costs - and centralized control over the financial governance of the entire organization.

Demo 8: Simplify Cloud Cost Governance With VantageCloud Lake

This demo provides detail on VantageCloud Lake console built-in data insights and visualizations. See how Teradata VantageCloud Lake and ClearScape Analytics provide native in-database functions to deliver rapid and scalable data insights for the largest datasets stored in data lakes, warehouses, or lakehouse architectures.

Demo 7: Get Bettter, Faster Insights With In-Database Analytics

With Teradata VantageCloud and ClearScape Analytics, you can reveal crucial insights about key moments in your customer journeys to deliver more relevant, authentic, and frictionless experiences every step of the way. During this live demo, see how you can: quickly and easily identify and eliminate friction points in customer journeys; analyze customer interactions to determine conversion, abandonment, or churn; build and operationalize AI/ML models that enhance customer experiences; uncover opportunities to increase revenue, acquire leads, and improve conversions.

Demo 6: Pinpointing High-Impact Moments in Your Customers' Digital Journeys

During this live demo, you'll see some of the most exciting new use cases for generative AI natural-language interfaces and LLMs. This demo features ask.ai.

Demo 5: Improve Customer Experiences and Maximize Data Productivity with Generative AI

Watch this live demo to see how Teradata VantageCloud and ClearScape Analytics™ simplify AI operations so you can accelerate AI innovation, reduce cost and friction, and fast-track time-to-value throughout your organization.

Demo 4: Seamlessly Operationalize and Share AI/ML Models

Watch this live demo to see how Teradata VantageCloud and ClearScape Analytics™ offer data practitioners the flexibility to leverage the widest range of modeling tools and technologies, enabling enterprises to drive more breakthrough growth, performance, and value from AI/ML projects.

Demo 3: Enabling Agility & Scale in Model Building and Evaluation

Find out in this video how to solve challenges in the data science lifecycle with Teradata VantageCloud.

Demo 2: Optimizing Data Prep for Advanced Predictive Modeling

In this video, we’ll explore VantageCloud Lake’s self-service console and key features that IT admins, data engineers, data analysts, and data scientists can leverage to innovate faster, scale smarter, and govern better.

Demo 1: Getting to Know VantageCloud Lake

Accelerate Innovation with VantageCloud & ClearScape Analytics

Sports organizations often struggle to understand and engage their diverse fan bases, missing opportunities for personalized experiences and revenue optimization. This challenge isn’t unique to sports: Organizations across various industries face similar difficulties delivering deep individual customer insights in a timely manner, despite the growing investment in customer data platforms.

By leveraging insights that sports organizations are now gaining, other industries can enhance customer satisfaction and optimize their engagement strategies, too.

Teradata Vantage™ provides a unified view of customer data, while ClearScape Analytics™ provides advanced analytics to analyze multitudes of interactions, delivering personalized experiences and increasing satisfaction.

Join this live demo to learn practical strategies for harnessing data to enhance fan experiences, so you can stay ahead of the competition.

Find out how to:

- Segment fans into distinct clusters based on behaviors, preferences, and demographics to tailor marketing strategies and enhance personalized fan experiences
- Quickly and easily identify and eliminate friction points in customer journeys

Demo 16: Enhancing Sports Fan Engagement With Data-Driven Insights

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Demo 16: Enhancing Sports Fan Engagement With Data-Driven Insights

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Teradata – Enterprise Data Analytics