Name: ESG: How Google Cloud Drives More Value from Big Data
Start: 2023-06-07T19:23:00Z
End: 2023-06-07T19:23:26.000Z
Location: BrightTALK

Google’s Data and AI Cloud is not only the most complete and unified data analytics and AI solution provider in the market but also a total-cost-of-ownership (TCO) leader. Learn more about Google Data Cloud and how it can help you transform your business.  It supports various data use cases (e.g. applications, analytics, predictions, visualizations) through products that cater to different data personas (e.g. application developers and system builders, data engineers and data analysts, data scientists and ML engineers, and business users).


AlloyDB AI’s latest innovations are fresh out of the oven! Take your operational workload into the agentic AI era with just a few lines of SQL. From database embedding generation, to zero configuration vector indexes, AlloyDB AI provides a fully managed vector search experience. Leveraging Gemini CLI and MCP Toolbox you can take your vector search application to the next level to build agentic applications that intelligently search your data.

Level up your agentic AI apps with AlloyDB

Learn how the Google Car-to-Cloud solution, powered by Bigtable and Android Auto Software Defined Vehicle (SDV), utilizes Vertex and Agentic AI to enable real-time analytics for features such as driver personalization and predictive maintenance.



Bigtable offers exceptional performance for time-series data, providing high ingestion rates, low latency, and massive scalability. Its adaptable schema accommodates evolving data structures. Real-time aggregations for live dashboards are efficiently supported through built-in Counters (for sums, min/max, and HLL) and Continuous Materialized Views, which process data directly at write time.

From data to drive: Building AI-powered experiences for Android Auto with Bigtable

Supercharge your AI agents with knowledge graphs! In this session learn how GraphRAG systems, powered by Spanner's cutting-edge multi-model capabilities and Vertex AI, enhance AI reasoning and deliver more insightful, relevant and accurate customer experiences.

Enhance AI agents with GraphRAG on Spanner

Building applications and analyzing trends with services like Cloud SQL, AlloyDB and BigQuery has never been easier — all from your local development environment! Whether you’re just getting started or a seasoned developer, learn how these extensions make common data interactions such as app development, deployment, operations, and data analytics much more productive.

Supercharge your database workflows with Gemini CLI extensions

You are invited to join Google Cloud's database product leadership for an exclusive strategy & roadmap session on October 30, as well as additional on-demand sessions for a deep dive into key capabilities.

Crafting transformative, next-generation agentic AI experiences begins with selecting the right operational database, which serves as the essential engine that powers your AI application. Google Cloud databases are specifically engineered to help organizations not just keep pace, but actively pioneer the next wave of AI innovation. You will hear directly from the team shaping the future, learning how to revolutionize customer interactions and unlock the full, game-changing potential of generative AI.

Join us live to dive deep into our vision and product roadmap, including:
- How Google Cloud databases can supercharge agentic AI development
- Innovations in next-generation relational databases—Cloud SQL, AlloyDB, and Spanner
- Enhancements to non-relational databases, including Bigtable, Memorystore and Firestore

Databases Roadmap Webinar

Join this webinar to explore the cutting-edge advancements in Google Cloud’s data analytics platform to gain a competitive advantage and improve your productivity in the agentic era.

In this webinar, we'll dive into our product direction for BigQuery, BigLake, Dataproc, Dataplex and more. Learn how you can take advantage of new capabilities to power your AI-ready Data Cloud, including: 

- Gemini-powered agentic experiences: To automate tasks and proactively identify and resolve issues, across data science, engineering and data analysis
- Multimodal data foundations: To access and analyze structured and unstructured data together for deeper insights and ground AI models
- Interoperable engines: To gain flexibility to across data engines for SQL, Spark, and streaming, as well as open formats like Iceberg
- Built-in AI to take action: To gain automation for model building, inference, and co-processing all with built-in governance and security

Data Analytics Innovation Roadmap

Unlocking the full potential of AI demands a robust, adaptable data architecture.  However, traditional approaches often fall short, where organizations often struggle with scale, interoperability, and governance for today’s data and AI workloads. Join us to learn how to build an open data lakehouse powered by Apache Iceberg and Google Cloud so you can unlock the full potential of all of your data without sacrificing flexibility or choice. Gain practical insights to optimize your open lakehouse strategy, reduce complexity, and accelerate your data and AI workloads.

Architecting the Future: How to build an AI-ready lakehouse with Apache Iceberg and Google Cloud

Migrating your Business Intelligence platform to Looker presents a powerful opportunity to modernize your data stack, but it requires careful planning and execution. This webinar provides a strategic roadmap for navigating the complexities of migration, from initial assessment to final rollout. We will focus on turning common challenges into strategic advantages by leveraging proven best practices and automation tools, ensuring you build a scalable and trusted analytics foundation on Looker.

Modernize Your Analytics and Accelerate Your Move to Looker with Confidence

Data Science on BigQuery: 3-part Webinar Series with BrightTalk

Part 2: Supercharge your analytics with BigQuery multimodal embeddings and vector search
The ability to search and analyze data based on its meaning, not just keywords, is crucial for building the next generation of AI-powered applications. As data becomes increasingly multimodal—a mix of images, text, audio, and more—you need powerful tools to unlock insights from these complex datasets. This webinar introduces BigQuery's latest capabilities for generating multimodal embeddings and performing efficient vector search at scale, directly within your data warehouse. We'll explore how these features simplify your data architecture and enable you to build sophisticated applications. Join us for a live demo where we'll showcase how to perform powerful semantic searches on your own data.

What you will learn:

Generate multimodal embeddings with ease: Discover how to use BigQuery ML to create embeddings for various data types, including text and images, using pre-trained Vertex AI models. 

Perform high-performance semantic search: Learn how to use the VECTOR_SEARCH function and vector indexes in BigQuery to find similar items in your datasets at scale and with low latency. 

Build End-to-End AI Solutions in BigQuery: Understand how to combine multimodal embeddings and vector search to create powerful, end-to-end AI solutions. We will discuss use cases such as retrieval-augmented generation (RAG), document analysis, and building your own semantic search applications, all within your existing BigQuery environment.

BigQuery embeddings and vector search

For resource-constrained organizations, the path to data-driven decision-making and GenAI can feel out of reach. Manual, time-intensive data tasks often create a bottleneck, slowing down innovation and draining valuable time.

This session introduces BigQuery's family of AI agents designed to automate complex data tasks and accelerate your path to innovation. 

Join us for a deep dive on how to simplify your entire data workflow and become AI-ready with BigQuery AI agents. We'll explore how these agents empower every role, regardless of technical skill:

- Data Engineering Agent: Automate complex tasks like data ingestion and transformation, so you can get clean, reliable data faster.
- Data Science Agent: Assist with exploratory data analysis and predictive modeling, enabling you to build powerful models and test hypotheses without a full data science team.
- Conversational Analytics Agent: Empower business users to get answers and forecasts from data using simple, natural language questions, freeing up analysts from ad-hoc report requests.
- Custom AI Agents: Build and deploy custom AI agents with open-source frameworks like ADK, the MCP Toolbox, Vertex AI Agent Builder, and the Conversational Analytics API. 

Register now to learn how you can leverage BigQuery AI agents to unlock strategic insights and AI innovation from your data faster and easier than ever.

Automate Your Data Workflow & Become AI-Ready with BigQuery AI Agents

The shift to AI is urgent, but fragmented data platforms are a fundamental roadblock. This webinar focuses on the critical path to modernization: unifying your data to make it AI-ready. The hardest part of the journey? It’s getting started. We will provide practical advice for planning your migration, from getting leadership aligned to creating a plan that ensures your migration is smooth, on time, and is designed to accelerate AI innovation. Hear how Cadent, a leading AdTech company that provides seamless connections between brands, publishers & consumers, plans to build an expansive and unified data ecosystem that is AI-native with BigQuery, and how they got started with their migration journey.  Join us to learn how to transform your data platform migration from a technical challenge into a strategic business win.

Get your data AI-ready: How migrating your data platform can accelerate AI and how to get started

The journey from data to AI is often complex and fragmented, requiring data movement between different tools and learning advanced programming languages.
This webinar will demonstrate how to leverage built-in AI & ML capabilities of BigQuery for a complete, end-to-end machine learning journey, all within the familiar BigQuery environment. We will explore how you can go from using pre-trained models for quick and powerful inference to feature engineering, model training & evaluation and scaling your ML workflows with Vertex AI integrations. 
Join us for a live demonstration and learn how to:
• create and execute machine learning models directly in BigQuery using simple SQL with pre-built, custom and remotely hosted models
• leverage state-of-the art pre-trained models to analyze unstructured data for tasks like sentiment analysis and image annotation
• use specialized AI-powered agents for automating data engineering and data science workflows
• integrate with Vertex AI Model Registry to manage, version, and automate the deployment of your BigQuery ML models

Data Science on BigQuery: 3-part Webinar Series Part 1: Introduction to AI and ML in BigQuery

In the age of AI, a solid data foundation isn't just an advantage—it's a necessity. Join Google Cloud experts for an insightful webinar and learn how to construct a powerful data infrastructure that will accelerate your AI initiatives and drive transformative business outcomes.

Discover the latest trends in data and AI, understand the pivotal role of enterprise data in successful AI adoption, and explore the essential components of an AI-ready data foundation. See how Google's Data Cloud seamlessly integrates the power of AI with your data through a unified approach to data management and analytics.

In this webinar, you will learn:
- The latest trends shaping the future of data and artificial intelligence.
- Why a robust enterprise data strategy is critical for successful AI implementation.
- The key characteristics of a data foundation that is primed for AI.
- How Google's Data Cloud, featuring solutions like AlloyDB, BigQuery, Looker, and Vertex AI, brings the power of AI directly to your data.

Your Data Foundation: Paving the Way to AI Success

Stop treating your data and AI as separate workflows. This session will demonstrate how to build a seamless, end-to-end AI lifecycle by combining the power of BigQuery as your data engine and Vertex AI for model development and deployment. We will move beyond theory to show you how to implement a unified strategy for data preparation, training, governance, and ETL directly within the Google Cloud ecosystem. You will see firsthand how this integration accelerates agents, model development, simplifies MLOps, and enables your teams to deliver real business value from your data.

BigQuery + Vertex AI: Unify Data and AI for Accelerated Results

Ready to move beyond basic reporting and truly drive business impact with your Google Cloud data? This webinar will showcase Looker Core on Google Cloud as the essential analytics layer for your GCP ecosystem. We'll demonstrate how Looker empowers users of all technical levels to access and analyze data, build custom applications, and integrate insights directly into their workflows. Discover how Looker's robust security features, scalability, and seamless integration with BigQuery and other GCP services can help you achieve data governance, accelerate time to insight, and foster innovation across your enterprise.

Beyond the Dashboard: Driving Business Impact with Looker Core and BigQuery

Ready to ignite your open data and AI initiatives? The rapid adoption of open table formats, open source engines, and the transformative lakehouse paradigm demands a fundamental re-evaluation of enterprise data strategy. 

Join us to hear from our product and engineering leaders, who will unveil significant new innovations designed to elevate your open data strategy, including:

*Enhanced BigLake support for Apache Iceberg native storage in GCS
* Operational and analytical engines united on an open lakehouse data foundation
* BigQuery SQL automated engine enhancements for market leading performance
* Launch of the new Lightning Engine to supercharge Apache Spark across serverless and cluster based deployments
* Dataplex Universal Catalog driving governance across data to AI, with AI powered curation, metadata generation, data insights and semantic search.
* Breakthrough AI driven notebook experiences for data science and data engineering teams 
* On demand customer panels discussing building a lakehouse with Google Cloud, how to govern your lakehouse, migrating your lakehouse to Google Cloud and more.

Lakehouse LIVE: Architecting the future of open lakehouses with Google Cloud

Join us for a live webinar to explore the cutting-edge advancements in Looker, Google Cloud's enterprise business intelligence (BI) platform. Learn how we're transforming data-driven decision-making with powerful AI integrations and a unified BI experience.

In this webinar, we'll dive deep into our latest product vision and roadmap, showcasing how Looker is empowering organizations to transform their approach to data analysis.

* AI & Unified Platform: Learn about Looker's unified BI vision, tapping Google’s latest AI models and driving a new experience with Looker reports.
* Conversational Analytics API & CI/CD: Discover the Conversational Analytics API to extend natural language capabilities to new surfaces and explore Continuous Integration/Continuous Deployment for faster deployments.
* Empowered Users & Insights: Learn how Looker democratizes data access and drives actionable insights through powerful tools.
* Product Demonstrations: Witness all these features in action, showcasing their real-world impact.

AI for BI Innovation Roadmap

Data is the fuel for agentic experiences and Google Cloud’s data analytics platform helps you connect your data to AI. Join us for an exclusive live webinar to explore the cutting-edge advancements that help you build AI agents, intelligent search, and AI-powered analytics for productivity, deeper insights, and a competitive edge.

In this webinar, we'll dive deep into our vision and roadmap for various product elements including:

* Data agents that automate complex tasks and proactively identify and resolve issues, acting as expert analysts, engineers, and guardians.
* Gemini assistance across the entire data lifecycle, from ingestion to AI-driven insights, to minimize manual effort
* Advanced analytics and ML workflows from model creation and inference to embeddings and vector search
* Multimodal data foundation with built-in governance and support for open formats, multiple engines and real-time analytics

Data Analytics Roadmap Webinar

"What does it mean to be a data-driven organization?” is a question every organization must ask themselves as they distill zettabytes of data into business-boosting insights. 

Unlocking the heart of being data-driven requires more than ingesting data to create business efficiencies and drive new revenue streams, though. Increasingly, this critical data must be simultaneously secure, easily accessible, and self-service—three often contradictory objectives.

In this webinar, ESG Analyst Nathan McAfee and Google’s Senior Director of Product Irina Farooq cover:
• The definition of what being data-driven means & how to achieve it 
• Challenges of on-prem and self-managed data infrastructure
• How Google Cloud assists customers in driving more value from big data

ESG: How Google Cloud Drives More Value from Big Data

Cloud Data

Cloud Platform

Data Platform

Big Data

Big Data Analytics

Big Data Management

Data Analytics

Business Intelligence

Data Infrastructure

Data Governance

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ESG: How Google Cloud Drives More Value from Big Data

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Google Data and AI Cloud