Name: Real time analytics, ML and applications made simple
Start: 2023-08-25T16:00:00Z
End: 2023-08-25T16:00:45.000Z
Location: BrightTALK
Rating: 0

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).


In the era of AI, the role of a data analyst is evolving rapidly from analyzing complex datasets to predicting outcomes such as customer behavior or product sales. This trend is largely driven by the increasing availability of large datasets and the development of more sophisticated machine learning algorithms. Data analysts are now able to use these tools to identify patterns and trends in data that would be impossible to detect manually.
However, building and using AI models can be challenging for data analysts. You often need to learn advanced coding languages such as Python, build pipelines to move data from analytics to AI tools, and be able to import ML models into analytics tools.
To help accelerate the path to AI adoption, BigQuery provides built-in capabilities that allow you to create, train, and execute machine learning models using simple SQL. BigQuery ML supports a broad range of ML models, including built-in models, models trained in Vertex AI, and imported custom models.
In this webinar, you will see a live demo of BigQuery ML and learn how to:
• Create and use machine learning models in BigQuery ML using simple SQL
• Apply Google's best-in-class AI models, such as PaLM 2, to your data right inside BigQuery
• Deploy models and operationalize ML workflows without moving data from BigQuery

How Data Analysts Can Build and Run AI Models Using BigQuery ML

Learn about Google Cloud’s differentiated architecture and how it’s designed to solve customer use cases for the digitized economy. Discover common architectural patterns that Google Ads and Gmail solve to achieve infinite scale, developer productivity, and efficiency. Learn how Google Cloud databases leverage common infrastructure – such as our highly durable and distributed storage system, disaggregated compute and storage at every layer of the stack, and our high-performance networking infrastructure – to get the highest levels of availability and reliability.

Building next-generation applications with Google Cloud Databases

Hear from Booking.com’s Engineering Manager Warren Qi on how his team supports pay-per-click ads bidding across billions of messages a day with Google's Data and AI Cloud. Learn about their data modernization journey and the top three ways Warren and his team are using BigQuery and Dataflow to push the limits on large-scale data processing.

How Booking.com modernized its large scale ads data systems with Google Cloud

AI advancements are triggering one of the most significant technological shifts in history, with many companies adopting an AI-first mindset to gain a competitive edge. For those looking to build differentiated products and services, activate data, and create a culture of AI innovation, investing in an AI Platform with the necessary end-to-end capabilities provides the foundation to innovate faster. 

Attend this webinar to hear from our guest speakers from Forrester and Google Cloud leaders on:
Forrester’s Predictions for 2024, including how AI platform budgets will increase to support enterprise teams.
Findings from the commissioned study conducted by Forrester Consulting, “The Total Economic Impact(™) of Google Cloud Vertex AI”, including how customers achieved a 397% ROI using Google Cloud’s Vertex AI.
Continued investments to make Vertex AI the platform of choice for building enterprise-grade Generative AI

Investing in the AI Platform of the future: Vertex AI, powered by Google Cloud

New advancements in Gen AI can help ISVs unlock new revenue streams, personalized experiences, cost savings and more. To help you build a strong data foundation and accelerate your path to Gen  AI adoption, Google Cloud brings the approach of organizing world’s information and making it universally accessible and useful to your organization. Google’s data and AI Cloud is built with and for AI, so that you can get to use the latest tools for training, tuning, and deploying your choice of AI models.

Join this webinar to hear from the BigQuery Product Management team how the 1,000+ software partners whose solutions are built with BigQuery can leverage the latest AI/ML features to rapidly deliver Gen AI experiences. You’ll learn:

- How to apply Google’s foundational AI models to your data right inside BigQuery
- How BigQuery Studio, which includes a new notebook experience, can accelerate data and AI workflows from data ingestion and preparation to analysis, exploration, and visualization — all the way to ML training and inference
- How to generate and store text embeddings using SQL commands

How ISVs can accelerate Gen AI adoption with BigQuery

Delivering relevant campaigns while making your budget work as efficiently as possible and navigating multiple marketing channels can be challenging — but when done well, it can yield results you’ll want to brag about. Join Google Cloud experts to learn how you can get a more holistic view of your customers, use that view to better predict their behaviors, and ultimately create the personalized experiences they’ll love. Google Cloud can help you reduce data silos, unlock new AI capabilities that can help you get more efficiency with your ad spend, and increase ROI. Tune in to learn how.

Get More, Spend Less, and Delight Your Customers: Data & AI Cloud for marketing

Spikey workloads are no match for Climate Engine, a satellite-powered analytics hub dedicated to helping companies assess and prevent climate risks. Bennett Kanuka, Climate Engine's CTO and all-around data science warlock, guides us through the cost-reducing and labor-saving integrations of BigQuery and GKE Autopilot. In conversation with Bruno Aziza, we'll find out the best practices of autoscaling to best avoid any hazards, climate or otherwise.

Autoscaling and the secrets of climate risk assessment

Join Ryan de Melo of Tokopedia, an Indonesian company that started as a digital marketplace and has since grown to cover fintech, payment, and new retail as well. Recently, de Melo's team migrated their seller analytics engine over to a Google Cloud stack—and dropped their computing costs by 25% as a result. Watch the episode to learn more and to hear de Melo's best (and worst) data practices.

Data Journeys: Tokopedia

Bruno Aziza is joined by Sanjeev Mohan, Principal at SanjMo - a company that helps organizations discover opportunities for market advancement and growth by providing independent insights into their data analytics, internal processes, customer feedback, and competition. Mohan talks about rejecting one-size-fits all solutions, the ease of autoscaling, and workload efficiency with compressed storage through BigQuery for cost savings.

SanjMo talks optimizing cost and performance with Google Cloud

As an early player in the customer data platform arena, Lytics is unique for using 100% real-time data, having a rich legacy of AI and machine learning with Vertex, and being built entirely within Google Cloud Platform. Jascha Kaykas-Wolff, President of Lytics, joins Bruno Aziza to talk about how packaging and additions like autoscaling from BigQuery have increased performance at Lytics by 15% and cut costs by 20%.

How Lytics cut costs by 20% with Google Cloud

Experience the magic of Google Cloud’s Generative AI technology
With all the buzz in the market around Generative AI, getting started meaningfully can feel like the challenging part. Whether you and your teams are looking to create new projects from simple natural language prompts, summarize information in a digestible way, discover what your customers want, or automate your customer services, Generative AI is the start of the new era of innovation.

Generative AI: What You Can Do Right Now with Google’s Technology

Unlock Innovation & Governance with Google’s Data Cloud

Join our product management leadership for a BigQuery Innovation Roadmap session. In this first-ever session, we will go through recent innovations, strategy, and plans for BigQuery.

What's new (and coming) in Google BigQuery

Paypal's data volume grew 400% in the past two years—due, in part, to a surge in online purchasing with the pandemic. When their existing data clusters struggled to keep up with the strain, Sr. Director of Data Infrastructure and Cloud Engineering Bala Natarajan started looking for new solutions. In just a year, his team has moved their data cluster to Google Cloud. Learn about the process, plus Natarajan's top tips for migration, in this episode of Data Journeys.

Data Journeys: Paypal

With 400 analytics users working in 40 different workspaces running heaps of monthly and quarterly forecasting and risk models to manage $145B in assets, Key Bank needs elasticity, speed, and a consistent environment for its data in order to succeed. That's exactly what they found in Google when they started looking for a solution for cloud computing. Listen as  EVP Chief Data Officer, Divisional CIO, and Head of Enterprise Mike Onders discusses the bank's data journey, plus some lessons learned.

Data Journeys: Key Bank

This installment features Matteo Fava, Senior Director of Global Data Products and Analytics for the largest food delivery network outside of China—Delivery Hero. The delivery company's data needs had been growing explosively as they opened up new business verticals, so they turned to Google Analytics and Big Query to pair the right users with the right data access, make use of real-time insights, and improve customer recommendations. Listen as Fava shares his take on the process, plus his advice on dealing with data at scale and driving widespread adoption.

Data Journeys: Delivery Hero

The increasing digitization of smaller and smaller events in business and society is driving the increase in real time data. This has created an unprecedented opportunity for organizations to create a competitive edge by increasing customer satisfaction, driving major productivity gains and capturing revenues sooner.  Join this session to hear how Google Cloud can help you to build real time visibility, prediction and activation into your products and systems so that your organization maximize value from each data point instantly.

Real time analytics, ML and applications made simple

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BigQuery

Data Warehousing

Analytics

Real Time Analytics

Cloud

Cloud Analytics

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Real time analytics, ML and applications made simple

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