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Events Data + AI Summit Data + AI World Tour Data Intelligence Days Event Calendar Blog and Podcasts Databricks Blog Explore news, product announcements, and more Databricks Mosaic Research Blog Discover the latest in our Gen AI research Data Brew Podcast Let’s talk data!
Events Data + AI Summit Data + AI World Tour Data Intelligence Days Event Calendar Blog and Podcasts Databricks Blog Explore news, product announcements, and more Databricks Mosaic Research Blog Discover the latest in our Gen AI research Data Brew Podcast Let’s talk data!
It’s a great, no-cost way to start learning and experimenting with large-scaleanalytics. By KDnuggets on July 22, 2025 in Partners Sponsored Content How much time do you spend fighting your tools instead of solving problems? They’re familiar, easy to use, and great for collaboration. No credit card required.
Events Data + AI Summit Data + AI World Tour Data Intelligence Days Event Calendar Blog and Podcasts Databricks Blog Explore news, product announcements, and more Databricks Mosaic Research Blog Discover the latest in our Gen AI research Data Brew Podcast Let’s talk data!
Events Data + AI Summit Data + AI World Tour Data Intelligence Days Event Calendar Blog and Podcasts Databricks Blog Explore news, product announcements, and more Databricks Mosaic Research Blog Discover the latest in our Gen AI research Data Brew Podcast Let’s talk data!
Events Data + AI Summit Data + AI World Tour Data Intelligence Days Event Calendar Blog and Podcasts Databricks Blog Explore news, product announcements, and more Databricks Mosaic Research Blog Discover the latest in our Gen AI research Data Brew Podcast Let’s talk data!
Events Data + AI Summit Data + AI World Tour Data Intelligence Days Event Calendar Blog and Podcasts Databricks Blog Explore news, product announcements, and more Databricks Mosaic Research Blog Discover the latest in our Gen AI research Data Brew Podcast Let’s talk data!
Events Data + AI Summit Data + AI World Tour Data Intelligence Days Event Calendar Blog and Podcasts Databricks Blog Explore news, product announcements, and more Databricks Mosaic Research Blog Discover the latest in our Gen AI research Data Brew Podcast Let’s talk data!
Events Data + AI Summit Data + AI World Tour Data Intelligence Days Event Calendar Blog and Podcasts Databricks Blog Explore news, product announcements, and more Databricks Mosaic Research Blog Discover the latest in our Gen AI research Data Brew Podcast Let’s talk data!
Events Data + AI Summit Data + AI World Tour Data Intelligence Days Event Calendar Blog and Podcasts Databricks Blog Explore news, product announcements, and more Databricks Mosaic Research Blog Discover the latest in our Gen AI research Data Brew Podcast Let’s talk data!
Instead of sweating the syntax, you describe the “ vibe ” of what you want—be it a data pipeline, a web app, or an analytics automation script—and frameworks like Replit, GitHub Copilot, Gemini Code Assist, and others do the heavy lifting. You describe your goal in plain English (e.g., “ Build a REST API for customer management in Python ”).
Zero-ETL integration with Amazon Redshift reduces the need for custom pipelines, preserves resources for your transactional systems, and gives you access to powerful analytics. In this post, we explore how to use Aurora MySQL-Compatible Edition Zero-ETL integration with Amazon Redshift and dbt Cloud to enable near real-time analytics.
The latest guest on our series is Madhura Raut, Lead Data Scientist and the seed engineer for global leader tech platform for human capital management. Q: You’ve achieved remarkable recognition in the AI and ML field, particularly for your work on labor demand forecasting systems.
They use fully managed services such as Amazon SageMaker AI to build, train and deploy generative AI models. Deploying, upgrading, managing, and scaling the selected application also demands considerable time and effort. Organizations are looking to accelerate the process of building new AI solutions.
A more advanced cost-tracking implementation will also allow users to set a spending budget and limit , while also connecting the LiteLLM cost usage information to an analytics dashboard to more easily aggregate information. LLM implementation has introduced features that were previously non-existent. Anthropic, like Claude.
Using generative AI , handwritten notes can be scanned to record and analyze the document and establish automated workflows for product procurement, the supply chain, and entry into customer relationship management (CRM), enterprise resource planning (ERP), and farm management information systems (FMIS).
Events Data + AI Summit Data + AI World Tour Data Intelligence Days Event Calendar Blog and Podcasts Databricks Blog Explore news, product announcements, and more Databricks Mosaic Research Blog Discover the latest in our Gen AI research Data Brew Podcast Let’s talk data!
Events Data + AI Summit Data + AI World Tour Data Intelligence Days Event Calendar Blog and Podcasts Databricks Blog Explore news, product announcements, and more Databricks Mosaic Research Blog Discover the latest in our Gen AI research Data Brew Podcast Let’s talk data!
As you continue to innovate and partner with us to advance the field of generative AI, we’ve curated a diverse range of sessions to support you at every stage of your journey. Second, we’ll delve into Amazon Bedrock , our fully managed service for building generative AI applications.
In this post, we explore how Principal used QnABot paired with Amazon Q Business and Amazon Bedrock to create Principal AI Generative Experience: a user-friendly, secure internal chatbot for faster access to information. As Principal grew, its internal support knowledge base considerably expanded.
AI-powered de-duplication offers an innovative way to scale this work quickly and efficiently, but its success depends on human expertise. And for all its effort, this process was inherently limited by scale. Authors Skip Prichard Drew Bordas Stacy Brunner Rebecca Bryant Susan Chaney Peter Collins Karen Coombs Ixchel M.
Although we maintain pre-built Amazon QuickSight dashboards for commonly tracked metrics, business users frequently require support for long-tail analytics—the ability to conduct deep dives into specific problems, anomalies, or regional variations not covered by standard reports.
We’ve already guided thousands of customers across industries from financial services to healthcare—including Formula 1, FOX, GovTech Singapore, Itaú Unibanco, Nasdaq, NFL, RyanAir, and S&P Global—from AI experimentation to full-scale deployment, driving millions of dollars in productivity gains and transforming customer experiences.
From robotic process automation (RPA) to AI-enhanced workflow management, these solutions enable businesses to lower costs, reduce errors, and scale operations without complicating processes. Blue Prism Blue Prism is known for its robust security and scalability, offering RPA solutions tailored for large-scale enterprises.
In the field of generative AI , latency and cost pose significant challenges. The commonly used large language models (LLMs) often process text sequentially, predicting one token at a time in an autoregressive manner. This approach can introduce delays, resulting in less-than-ideal user experiences.
The modern data stack is defined by its ability to handle large datasets, support complex analytical workflows, and scale effortlessly as data and business needs grow. With its decoupled compute and storage resources, Snowflake is a cloud-native data platform optimized to scale with the business.
Cato Networks is a leading provider of secure access service edge (SASE), an enterprise networking and security unified cloud-centered service that converges SD-WAN, a cloud network, and security service edge (SSE) functions, including firewall as a service (FWaaS), a secure web gateway, zero trust network access, and more.
Events Data + AI Summit Data + AI World Tour Data Intelligence Days Event Calendar Blog and Podcasts Databricks Blog Explore news, product announcements, and more Databricks Mosaic Research Blog Discover the latest in our Gen AI research Data Brew Podcast Let’s talk data!
Summary: “Data Science in a Cloud World” highlights how cloud computing transforms Data Science by providing scalable, cost-effective solutions for big data, Machine Learning, and real-time analytics. Advancements in data processing, storage, and analysis technologies power this transformation.
Amazon Q Business is a fully managed, generative AI-powered assistant designed to enhance enterprise operations. This integration empowers you to use advanced search capabilities and intelligent email management using natural language. A number of organizations use Gmail for their business email needs.
We spoke with Dr. Swami Sivasubramanian, Vice President of Data and AI, shortly after AWS re:Invent 2024 to hear his impressionsand to get insights on how the latest AWS innovations help meet the real-world needs of customers as they build and scale transformative generative AI applications. Q: What made this re:Invent different?
With ever expanding product catalogs and increasing diversity of brands, harnessing advanced search technologies is essential for success. To learn more about semantic search and how Amazon Prime Video uses it to help customers find their favorite content, see Amazon Prime Video advances search for sports using Amazon OpenSearch Service.
Amazon Bedrock is a fully managed service that makes foundation models (FMs) from leading AI startups and Amazon available through an API, so you can choose from a wide range of FMs to find the model that is best suited for your use case. This post is co-written with Mayur Patel, Nick Koenig, and Karthik Jetti from GoDaddy.
Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies such as AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon through a single API, along with a broad set of capabilities you need to build generative AI applications with security, privacy, and responsible AI.
Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies and AWS. This post demonstrates how Amazon Bedrock Knowledge Bases can help you scale your data management effectively while maintaining proper access controls on different management levels.
Although rapid generative AI advancements are revolutionizing organizational natural language processing tasks, developers and data scientists face significant challenges customizing these large models. To address these challenges, AWS has expanded Amazon SageMaker with a comprehensive set of data, analytics, and generative AI capabilities.
Enterprises adopting advanced AI solutions recognize that robust security and precise access control are essential for protecting valuable data, maintaining compliance, and preserving user trust. For example, you can use a chat playground to try a prompt with Anthropic’s Claude without having to write code.
Simple business questions can become multi-day ordeals, with analytics teams drowning in routine requests instead of focusing on strategic initiatives. Simple business questions can become multi-day ordeals, with analytics teams drowning in routine requests instead of focusing on strategic initiatives.
Additionally, we discuss the design from security and responsible AI perspectives, demonstrating how you can apply this solution to a wider range of industry scenarios. Understanding customer satisfaction and areas needing improvement from raw data is complex and often requires advancedanalytical tools.
By combining data analytics and their 11PB of data with advanced automation, Rocket speeds up everything from loan approval to servicing, while maintaining a personalized touch at scale. Rocket’s web and mobile app brings together home search, financing, and servicing in one seamless experience.
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Security teams in highly regulated industries like financial services often employ Privileged Access Management (PAM) systems to secure, manage, and monitor the use of privileged access across their critical IT infrastructure. Using this capability, security teams can process all the video recordings into transcripts.
Model distillation is the process of transferring knowledge from a more capable advanced model (teacher) to a smaller model (student), which is faster and more cost efficient to make the student model as performant as the teacher for a specific use-case. The teacher and student models should be from the same model provider.
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