Resources

July 24, 2024

Advanced Data Modeling

11 P.M. ET Take your data modeling expertise to the next level by attending the “Advanced Data Modeling” webinar. This session builds on the “Intro to Data Modeling” webinar and highlights the critical factors to consider when creating the model that aligns best with your application. You will learn: How your workload drives your schema Learn about Schema Design anti patterns How to enhance the power of the document model with schema design patterns How to migrate from a relational schema to a document based schema Register today to save your spot. We look forward to seeing you there!

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July 18, 2024

Continuously Updating Vector Embeddings for Gen AI Apps

12 P.M. ET Retrieval-augmented generation (RAG) lets us prompt generative AI large language models with enterprise data to produce answers founded on knowledge of the business’s operations and customers. But it’s a changing world, and keeping that data fresh and up-to-date is complex. This webinar shows how to continuously update the data used by RAG to ensure gen AI apps are always working with the latest data to produce the most accurate and current answers. The solution uses MongoDB Atlas Stream Processing and Atlas Vector Search to continuously update vector embeddings with data received from an Apache Kafka data pipeline. Join our Senior Consulting Engineer, David Sanchez as he walks developers through continuously updating, storing, and searching embeddings with a single interface. And it shows why the MongoDB document data model is so well suited to stream processing. The webinar details: How to set up and configure the environment. How to create vector search indices in Atlas. How to create a private and scalable embedding generator system using purpose-built LLMs. How to interactively run semantic queries. It also summarizes the key learnings of the exercise to help attendees apply the lessons learned to their own applications. We look forward to seeing you there!

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Building Powerful Gen AI Applications with Google Cloud and MongoDB

Wednesday, July 17 at 11 a.m. ET The application development landscape is evolving very rapidly. Today, users crave intuitive, context-aware experiences that reflect their intent and deliver relevant results even when queries aren't perfectly phrased. This level of hyper-personalization is now enabled through generative AI-powered applications. MongoDB Atlas and Google Cloud Vertex AI can help developers build and deploy gen AI-powered apps faster and at scale. MongoDB Atlas Vector Search indexes and stores high-dimensional vectors that can be used to uncover relationships within your data. It allows you to perform lightning-fast similarity searches, retrieving results based on meaning and context. Google Vertex AI is a comprehensive AI platform that houses an abundance of pre-trained models and tools, including the powerful Vertex AI PALM. This language model excels at extracting semantic representations from text data, generating those crucial vectors that fuel MongoDB Atlas Vector Search. Vector Search can be useful in a variety of contexts, such as natural language processing and recommendation systems. It is a powerful technique that can be used to find the meaning and intent behind searches. Join Matt Richmond, Senior Partner Solutions Architect at MongoDB and Bruce Sandell, Partner Solutions Architect at Google Cloud to learn how to: Simplify data management — Discover how MongoDB Atlas on Google Cloud eliminates database complexities. Free your team to focus on what truly matters: innovation. Unlock data's power — Learn how MongoDB's flexible platform empowers you to build modern, data-driven applications with ease. Dive into the world of generative AI and see how it can transform your business. Accelerate your cloud journey — See how MongoDB Atlas seamlessly integrates with Google Cloud, leveraging the power of Vertex AI to enhance development and drive growth. Take your cloud capabilities to the next level. The webinar will be recorded and all registrants will receive the recording. See you soon!

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Build Chatbots That Know Your Business

Thursday, July 25 at 12 p.m. ET The next frontier in generative AI is applying it to make businesses more efficient and more competitive: customer service, online sales, employee empowerment, manufacturing, and a host of other applications. And that requires AI-powered apps that understand your business and that access and apply your data to queries. To that end, Cohere has developed models optimized for enterprise generative AI, and MongoDB Atlas securely unifies operational, unstructured, and AI-related data to streamline building AI-enriched applications. Join us on Tuesday, July 25, at 12 p.m. ET to discover how this combo delivers the game-changing applications businesses need. Richmond Alake, Staff Developer Advocate, AI/ML at MongoDB and Cohere Senior Manager Solution Architect, David Stewart will show you how MongoDB Atlas and Cohere Command R+ work together to: Empower users with seamless semantic search on customer or operational data in MongoDB Atlas. Pass retrieved data to Cohere’s Command R+ generative model for retrieval-augmented generation (RAG). Develop and deploy a RAG-optimized user interface for your app. It’s the future of generative AI in business.

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July 30, 2024

Using HCP Terraform with MongoDB Atlas Vector Search

12 P.M. ET As AI-powered applications become mainstream, it becomes critical for developer workflows to safely provision applications and supporting infrastructure in production. Semantic search — enabled by MongoDB Atlas Vector Search — is a central element of many of these modern, AI-powered applications. Join Zuhair Ahmed, Sr. Product Marketing Manager at MongoDB and Kenan Fyfe, Alliances Manager at Hashicorp, for a discussion on integrating Atlas Vector Search with HashiCorp’s Terraform infrastructure-as-code solution. These tools let developers automate and scale their vector search workflows and incorporate sophisticated search capabilities with tools they are accustomed to. Attend our webinar with HashiCorp to learn how to: Deploy an Atlas dedicated cluster with Atlas Search Nodes using the HashiCorp Terraform Atlas Provider. Create collections with vector data and add vector search indexes in your Terraform configuration. Use MongoDB Shell to begin Atlas Vector Search queries.

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July 16, 2024

Enhance React Applications with Generative AI LLMs

12 P.M. ET Large language models (LLMs) like OpenAI’s GPT provide powerful natural language processing capabilities. Integrating those capabilities with React empowers developers to create dynamic, intelligent user interfaces that provide personalized user experiences. Enabling those user interfaces to remember earlier conversations and incorporate that memory as context in new interactions makes AI even more intelligent and human-like — and the application even more effective. Join Senior Developer Advocate Jesse Hall as he explores and explains how to achieve this in JavaScript and React. The app uses Next.js, LangChain, and MongoDB Vector Search to create an application that extends the benefits of LLMs by creating a memory store that enables the app to recall and use previous conversations. Adding this historical insight allows the chatbot to offer responses that are more relevant and tailored to the individual user. The webinar shows how to: Setup the environment and database. Create a naive RAG chain with a MongoDB vector store. Add a chat history to the RAG chain to improve answer relevance and accuracy.

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Building Gen AI-Enriched Apps with AWS & MongoDB Atlas

Join us for an exclusive webinar exploring the future of AI-driven applications. Learn how MongoDB, in collaboration with Amazon Web Services (AWS), empowers you to quickly and securely build gen AI-powered applications. And discover how to harness the full potential of gen AI by integrating MongoDB with Amazon SageMaker Canvas and Amazon Bedrock. You’ll learn from experts, and you’ll view practical demonstrations showcasing the integration of MongoDB Atlas and Amazon Bedrock. Here's what you'll Learn: How MongoDB's flexible data model enables agile development and iteration. How MongoDB Atlas Vector Search streamlines the machine learning workflow — from data preparation to deployment. How to harness the power of Amazon Bedrock to build scalable, enterprise-ready AI solutions. How other organizations are using MongoDB and AWS to create next-gen AI-powered applications. Join us across the globe at one of these times: May 21, 2024 at 10 A.M. GMT/3:30 P.M. IST: On-Demand May 22, 2024 at 12 P.M. ET: On-Demand June 5, 2024 at 9 A.M SGT / 11 A.M AEST: On-Demand Seize this opportunity to unlock the potential of gen AI with MongoDB and AWS. Register now to secure your spot and embark on a journey towards AI-driven innovation. Space is limited, so reserve your spot today!

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May 14, 2024

MongoDB Community Edition Masterclass

11AM (AEST) / 13.00 (NZST) Join us for a webinar tailored specifically for MongoDB Community Edition users, hosted by Mark Kirpichnikov, Solutions Architect at MongoDB. Discover AI tools, best practices, and optimisation techniques to maximise the performance and efficiency of your open-source MongoDB instance. In this webinar, we will: Share valuable insights for optimising your Community Edition deployment Provide actionable tips and techniques to fine-tune your MongoDB setup, improve query performance, and overall efficiency Explore how MongoDB Atlas simplifies database management Don’t miss this opportunity to hear from the experts and get your questions answered live. We look forward to seeing you there!

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Intro to Data Modeling

A frequently asked question in the MongoDB community is “I’m designing an application to do X, how do I model the data?” Choose from any of the following dates on the registration page: 9 A.M. SGT on Wednesday, July 17th 11 A.M. ET on Wednesday, July 17th 10 A.M. GMT on Thursday, July 18th 11 A.M. ET on Wednesday, August 28th 11 A.M. ET on Wednesday, September 25th In this webinar we will examine the most important considerations when making decisions about your data model, so that you can create the model that best fits your application. You will learn: The differences between data modeling in MongoDB vs. relational databases The key considerations for data modeling with MongoDB How to further enhance the power of the document model with schema design patterns Register today to save your spot. We look forward to seeing you there!

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Intro to MongoDB

Ready to begin your MongoDB Atlas adventures but not sure where to start? Join our Intro to MongoDB webinar to learn more! Choose from any of the following dates on the registration page: 11 A.M. ET on Wednesday, July 10th 11 A.M. ET on Wednesday, August 21st 11 A.M. ET on Wednesday, September 18th Senior Developer Advocate Jesse Hall will showcase the unique advantages of the document data model and show you how to deploy an Atlas cluster. Jesse will present a demo of how to get started with MongoDB Atlas and walk you through how to: Create your first cluster, add an IP address and set up a database user Load sample data using a Next.js e-commerce demo app Connect to the database Register today to save your spot. We look forward to seeing you there!

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Intro to Atlas Search

Atlas Search combines the power of Apache Lucene — the technology behind the world’s most popular search engines — with the efficiency, scale, and resilience of MongoDB Atlas to make it easier than ever to integrate fast, relevance-based search capabilities into all of your MongoDB applications. Join us for our Intro to Atlas Search where we’ll show you how to search through different data types, including text, numbers, dates, and geoJSON and demonstrate a variety of search capabilities. Choose from any of the following dates on the registration page: 11 A.M. ET on Wednesday, August 14th 11 A.M. ET on Wednesday, September 11th Don’t miss this opportunity to learn about Atlas Search and get your questions answered live. We look forward to seeing you there! Dates are subject to change

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Power-Up Your Queries: MongoDB's Aggregation Framework

In this webinar, we'll show you how MongoDB's aggregation framework allows you to write simple, and then increasingly complex, queries and aggregations against your datasets, helping you group, join, limit, skip, and bucket across documents in your collections. We'll introduce some of the ideas around data modeling patterns and indexing that will help you get the most out of storing and querying your data in MongoDB, and you'll learn powerful tools for writing and testing your queries. If you're already working with MongoDB, and are familiar with the document model, CRUD and query operations, and you're looking to build more complex queries to aggregate and analyze data, then this is the perfect webinar for you. We’ll be exploring these topics through various languages. Pick the one that suits you best: JavaScript - Wednesday, July 31st, 11 A.M. ET C#/.NET - Wednesday, September 4th, 11 A.M. ET Power-Up Your Queries in Python: On-Demand Power-Up Your Queries in Java: On-Demand Don’t miss this opportunity to power-up your queries and get your questions answered. We look forward to seeing you there! Dates are subject to change

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