Resources

Atlas 201 eWorkshop (English)

Watch this exclusive workshop to get a full overview on how to migrate from a relational database to MongoDB followed by hands-on exercises and direct access to our expert panel. During this time, you will learn how to: Migrate from a relational databases to MongoDB How to build design patterns using MongoDB How to create aggregation pipelines How to use Atlas Vector Search and AI for context aware search

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Modernize Your Apps with MongoDB Relational Migrator Webinar Hong Kong

As more and more organizations seek to improve performance, scalability, and developer productivity, many are turning to MongoDB as a solution. However, migrating legacy apps from relational databases to MongoDB can be a daunting task. That's where MongoDB Relational Migrator comes in. In this session, we explored how Relational Migrator can help reduce risk and effort throughout the various stages of a migration project, including data modeling, data migration, and application code modernization. Language: Cantonese

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Building Next Generation Applications Using Generative AI

With everyone jumping on the generative AI bandwagon, the real competitive advantage will come from businesses using their own data in conjunction with Large Language Models (LLMs). But doing so will require new skills. And it will no doubt usher in new concerns about data security and governance. MongoDB Senior Vice President Product Management, Andrew Davidson, was joined by Fern Halper, VP and Sr. Research Director for Advanced Analytics at TDWI for an informal chat about building and deploying generative AI applications. The discussion was followed by a live Q&A. Topics included: An overview of generative AI and the state of market adoption Use cases that leverage a company’s internal data The importance of vector databases in generative AI How to build and deploy a generative AI application while protecting company data Modern platforms to support AI and generative AI

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Why componentization is essential in a competitive market with MongoDB, Capgemini and Temenos

In this episode of FF Virtual Arena, Fintech Finance hosted Temenos, MongoDB, and Capgemini to find out why componentization and tech partnerships are essential today. This session brings together industry experts who have worked with the best in banking space to help them innovate and leverage the advantages of componentization. Some of the key takeaways discussions include: Adding components is not just about upgrading legacy systems but also finding new revenue streams Banks are increasingly looking at moving data around and leveraging rich data to deliver a better service How can you access data in real time and get a holistic view of customers What the impact of AI is on componentization Speakers: Doug Mackenzie, Chief Content Officer, Fintech Finance News Joerg Schmuecker: Managing Director, Financial Services and Insurance Industry Solutions at MongoDB Mark Ashton: Senior Director, Cloud Practice Lead and Enterprise Architect at Capgemini Financial Services Paul Carr: Global Head of Partner Ecosystem at Temenos

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What's new with MongoDB 7.0

In this exclusive webinar, "What's New with MongoDB 7.0” we covered the latest advancements in MongoDB, the leading NoSQL database. MongoDB 7.0 brings a range of exciting features to the table, including enhanced performance, streamlined migrations, a more user-friendly development experience, and stronger security. Whether you're a seasoned MongoDB user or just getting started, this event is your opportunity to stay on the cutting edge of data management technology. Learn how MongoDB 7.0 can empower your development teams and secure your data. Don't miss out on this informative session.

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Migrate to MongoDB Atlas on AWS: Iterate fast and react quickly

MongoDB Atlas is well integrated into the AWS environment, and works seamlessly with AWS products. In this webinar, you will learn more about common integration and reference architectures of MongoDB on AWS as well as: Tools to Migrate from a relational database to MongoDB Atlas on AWS such as the Relational Migrator How to Accelerate your shift to a modern developer data platform with Live Migrate. The session ends with a demo to show how easy it is to migrate to Atlas using Live Migrate.

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Building Generative AI Applications Using MongoDB Developer Platform Webinar Hong Kong

In this webinar, we talked about building modern Machine Learning driven applications (like real time fraud detection, hyper-personalization, chat bots) using MongoDB Atlas Developer Data Platform . We walked through how MongoDB Atlas integrates with leading analytical ML platforms to generative AI solutions (HuggingFace and OpenAI). We also talked about how you can leverage the power of large language models (LLMs), the transformative technology powering ChatGPT, on your private data to build transformative AI-powered applications using MongoDB and Atlas Vector Search. And using vector embeddings, you can leverage the power of LLMs for use cases like semantic search, a recommendation system, anomaly detection, and a customer support chatbot that are grounded in your private data. Language: Cantonese

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Atlas 101 eWorkshop (English)

Watch this exclusive workshop and get a full technical overview and demo of MongoDB Atlas followed by hands on exercises and direct access to our expert panel. During this time, you will learn how to: Create a database cluster using MongoDB Atlas Secure the database & Load sample data Create indexes and leverage them in your aggregation pipelines using Atlas Get started with MongoDB Charts and create visual representations of your data And so much more!

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Revving up the data engine: powering connected vehicles with MongoDB and AWS

  In the ever-evolving landscape of connected vehicles, rapid accumulation and analysis of data have become the driving force behind innovative mobility solutions. Enter modern developer data platforms, like MongoDB, offering a turbocharged experience for developers seeking to harness the full potential of connected vehicle systems. The time for disconnected vehicles is over. People are looking for smarter products that deliver exciting customer experiences where users can start a task on one device and continue it on the next, creating a seamless digital thread between products. In this talk, designed to accelerate your application from factory to finish line, we will navigate through the fascinating realm of connected vehicles, with a focus on must-have features, including high-speed data ingestion, automatic synchronization between user applications and the vehicle, and advanced query capabilities. Strap yourself in for an exciting conversation that will: Explore the current connected vehicle landscape, including strategies for navigating the industry’s biggest challenges Unpack how MongoDB's document-based model, together with cloud deployment on AWS, helps you tap into the potential of connected vehicle data Feature a demo of MongoDB Atlas, Realm, and Atlas Device Sync that provide you with the building blocks to build connected products quickly and show you how easy it is to integrate with the AWS cloud ecosystem.

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Building a Connected Value Chain with MongoDB and AWS

  Jump-start your digital transformation journey by learning about industrial IoT, immersive visualization, and AI, and discover how MongoDB and AWS bring all of these technologies together to allow for a seamless flow of data from connected vehicles to the factory floor and back. In this video we’ll demonstrate how our 3D factory digital twin - powered by MongoDB and AWS - simulates equipment performing complex maneuvers to uncover the most efficient processes and mimic the behavior of a real production process. We’ll also show how MongoDB Atlas facilitates uninterrupted data flow from a connected vehicle to the virtual factory through real-time data transmission. Explore the possibilities of this cutting-edge technology and learn how you can leverage MongoDB and AWS to build your own connected value chain and transform your manufacturing process. Key technologies covered in this session include: MongoDB Atlas, Realm, Atlas Device Sync, AWS IoT Core and Sagemaker.

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Generative AI with MongoDB Atlas and BigQuery: A Developer’s Guide

Join Stanimira Vlaeva, Developer Advocate at MongoDB, and Abirami Sukumaran, Developer Advocate at Google, for this developer-friendly webinar. Discover how to leverage Gen AI with MongoDB Atlas and BigQuery for generative natural language tasks. We will walk you through a practical use case, step-by-step, covering: Moving subsets of operational MongoDB Atlas data into BigQuery. Creating machine learning models in BigQuery ML. Using Generative AI models to perform generative natural language tasks, such as generating text, translating languages, and writing different kinds of creative content.

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AirAsia flies Superapp into the cloud

  AirAsia is a Malaysian low-cost airline that operates domestic and international flights to more than 165 destinations in 25 countries. It is the largest airline in Malaysia by fleet size and destinations served. AirAsia Launched Superapp in October 2020. The mobile app for Android and Apple originally focused on flights and related services, but as the Covid-19 pandemic severely restricted international travel, it was clear that AirAsia needed to broaden its scope. Adding services such as food delivery, taxis, and hotels to Superapp proved to be highly successful. To date, the app has been downloaded 40 million times, with 13 million monthly active users, and 15 product and service offerings. “Most of our services are on Google Kubernetes Engine (GKE), so everything we run is in containers,” says Danial Hui, Head of Software Engineering at AirAsia at MongoDB.local Kuala Lumpur. “For Superapp and the AirAsia.com website, all our applications are connected to APIs and microservices.” **With Superapp’s rapid rise in popularity, the previous database’s scalability and quota limits were causing problems. ** **“Superapp is really a collection of apps that work quite differently and have different database needs. We switched to MongoDB because it has integration and geospatial functions that work very well for us,” adds Hui. “Most of our microservices are now on MongoDB. It’s flexible, it’s agile, and it complements our microservice architecture.” ** “ We realized that as a growing company, we might not be able to invest so much energy, skill sets or resources into managing MongoDB,” Hui explains. “That was one of the main drivers of why we went for MongoDB Atlas. **Time to market was also an important factor. With AirAsia looking to scale to five countries in 15 months, representing a 1,000% growth rate, being able to automatically set up multiple clusters in different countries was a substantial benefit. ** Another key feature that attracted Hui was the multi-cloud capabilities of MongoDB Atlas. AirAsia’s cloud provider of choice is Google Cloud Platform, but in territories where demand for resources can be unusually high, such as Singapore, the ability to switch to AWS has been highly advantageous. “The multi-cloud aspect of MongoDB Atlas is excellent; it works seamlessly,” concludes Hui. “We only use it when we absolutely have to, but it ensures that we never have any issues.”

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