Name: Build Fully Managed Data Pipelines with MongoDB Atlas and Confluent
Start: 2021-09-21T16:00:00Z
End: 2021-09-21T16:00:32.000Z
Location: BrightTALK

As empresas modernas mantêm seus dados em constante movimento. Descubra como conectar facilmente seus aplicativos, sistemas e toda a sua organização com processamento e fluxos de dados em tempo real.

Não perca a oportunidade de ouvir o co-fundador do Confluent e Apache Kafka, Jun Rao, e as histórias de sucesso de clientes da Confluent:

• Core Banking com Itaú-Unibanco
• Arquitetura Orientada a Eventos com SulAmérica

Conecte toda a sua organização com processamento e fluxos de dados em tempo real

Las empresas modernas tienen sus datos en constante movimiento. Descubre cómo conectar fácilmente tus aplicaciones, sistemas y toda tu organización con flujos y procesamiento de datos en tiempo real.

Escuche al cofundador de Apache Kafka y Confluent: Jun Rao, al igual que los casos de éxito de los clientes de Confluent:

• SulAmérica y la Arquitectura Orientada a Eventos
• Lifemiles y su Programa de Lealtad al Cliente

Conecte toda su empresa con flujos y procesamiento de datos en tiempo real

What is the future of Kafka beyond messaging? Join Tim Berglund, Head of OSS Kafka Developer Community, to talk about what the future holds for Kafka. This talk will cover some of the concepts and capabilities of ksqlDB, which allows many interesting forward-thinking use cases. We’ll show how you can apply transformations to a stream of events from one Kafka topic to another. We will also be discussing using ksqlDB connectors to bring in data from other systems and use that data to join and enrich streams.

The Future of Kafka

Building modern cloud applications requires companies to unlock their data from every aspect of their business with real-time access. Confluent Cloud integrated with Azure Cosmos DB enables companies to automate and integrate data and events across any system, at any scale in near real-time. Connecting Confluent Cloud with Cosmos DB allows companies to streamline infrastructure, increase development velocity, unveil new use cases, and analyze their data.

Join this webinar with Confluent and Microsoft experts to:
- Learn how companies are unlocking their data with Kafka
- Understand integration strategies that you can adopt
- See a demo of the Cosmos DB connector and how it can safely deliver data and events in real-time

Unlock Data by Connecting Confluent Cloud with Azure Cosmos DB

Insurance companies have always been data centric businesses. Disruption is the new normal as digital native insurance companies gain traction in the market. One challenge facing all property and casualty insurers is the many forms of fraud that raise premium prices. The FBI estimates that around $40 Billion is lost annually* to fraud related to property and casualty insurance. Capturing events in real time and looking through an event driven lens can dramatically impact one's ability to detect and remediate fraud.

Apache Kafka® is recognized as the world’s leading real-time, fault-tolerant, highly-scalable event streaming platform. It is adopted across thousands of companies worldwide to collect different types of events - member profile updates, claim submissions, etc. -  into Kafka in real-time. This architecture enables applications, data platforms and organizations to react to events in real-time. This can improve customer experience, drive revenue and reduce costs across the business.

In this talk, we’ll discuss the power of events to reimagine your data and how to achieve digital transformation with Apache Kafka and Confluent, in either a self-managed or fully-managed cloud offering. We’ll also look at different types of insurance fraud and how real time event streaming can enable different approaches to reducing them.

Industry Forum Series - Insurance

Microservices architecture enables organizations to evolve their systems away from the slow and unresponsive shared-state architectures of the past. Event-driven microservices decouple systems, teams, and products, and streamlines application development. Take a a deep dive into how you can use Confluent Cloud to explore event-driven architectures and how they are being applied across industries.

Legacy Modernization Forum Series - Microservices

Hear from KeyBank and how they are leveraging Confluent Platform and Google’s Business Application Platform (Google Cloud’s Anthos and Apigee) to drive ongoing digitization initiatives such as real-time fraud detection, lead management, and microservices.

Preparing for KeyBank's Digital Banking Future with Google and Confluent

For many organizations, Apache Kafka® is the backbone and source of truth for data systems across the enterprise. Protecting your event streaming platform is critical for data security and often required by governing bodies. This session will review security categories and the essential features of Kafka and Confluent Platform that enable you to secure your event streaming platform, including
 

Kafka Brokers and Confluent Servers

Role Based Access Control (RBAC)

Encryption

Alerts and Monitoring

Data Governance & Compliance

Production Safe Confluent Cloud

Multi-cloud computing is revolutionizing the way businesses operate, allowing organizations full agility, cost efficiency, security, and flexibility to leverage the best components for each use case. Hybrid and multi-cloud seeing the fastest adoption than any other technology in this domain. Learn what multi-cloud computing is complete with definitions and examples, how it works, pros and cons, and how to start streamlining multi-cloud deployments.

Multi-Cloud: Kafka Everywhere

As a fully managed service available in the biggest cloud providers, including Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP), Confluent Cloud can be self-serve and is deployable within seconds. This session will discuss and illustrate and you can easily point your client applications at Confluent Cloud, and the rest is taken care of: load is automatically distributed across brokers, consumer groups automatically rebalance when a consumer is added or removed, the state stores used by applications using the Kafka Streams APIs are automatically backed up to Confluent Cloud with changelog topics, and failures are automatically mitigated. Confluent Cloud abstracts away the details of operating the platform—no more choosing instance types, storage options, network optimizations, and number of nodes. It is as elastic as your workload, and you pay only for the resources that you use. In true serverless fashion, you just need to understand your data requirements.

Best Practices for Deploying Apps in Confluent Cloud

Episode 2 of the Legacy Modernization Forum Series

Mainframes are still hard at work processing over 70 percent of the world’s most essential computing transactions every day. However, high cost, monolithic architectures and missing experts are key challenges for mainframe applications.

Come join us and learn how mainframe offloading with Apache Kafka and its ecosystem can be used to keep a more modern data store in real-time sync with the mainframe, enabling microservices and delivering the data to other systems such as data warehouses and search indexes.

Mainframe Offload & Integration (Ep 2: Legacy Modernization Series)

Episode 2 of the Confluent Cloud Series

As companies adopt the cloud, they may discover that migrating to the cloud is not a simple, one-time project - it's a much harder task than building a greenfield cloud-native application. They need to build a seamless bridge between on-prem and cloud deployments.

Confluent Cloud is fully managed Apache Kafka® with complete, enterprise event streaming components. It accelerates developers building event streaming applications, liberates them from operations burden, and enables mobility between multi-cloud and on-prem deployments.

By attending this talk, you will learn:

--What is Bridge to Cloud?
--How to get started Confluent's fully managed Kafka service and connect data systems, process. real-time data streams with KSQL, monitor performance, and data governance.
--Intro on how to design, configure, manage, and monitor event streaming applications
--Intro to how to set up and run Confluent Cloud, complete with Bridge-to-Cloud examples.

Bridge to Cloud: Confluent Platform to Confluent Cloud (Episode 2: Cloud Series)

Last year, U.S. Citizenship and Immigration Services (USCIS) adopted a new strategy to accelerate our transition to a digital business model. This eProcessing strategy connects previously siloed technology systems to provide a complete digital experience that will shorten decision timelines, increase transparency, and more efficiently handle the 8 million requests for immigration benefits the agency receives each year.

To pursue this strategy effectively, we had to rethink and overhaul our IT landscape, one that has much in common with those other large enterprises in both the public and private sectors. We had to move away from antiquated ETL processes and overnight batch processing. And we needed to move away from the jumble of ESB, message queues, and spaghetti-stringed direct connections that were used for interservice communication.

Today, eProcessing is powered by real-time event streaming with Apache Kafka and Confluent Platform. We are building out our data mesh with microservices, CDC, and an event-driven architecture. This common core platform has reduced the cognitive load on development teams, who can now spend more time on delivering quality code and new features, less on DevSecOps and infrastructure activities. As teams have started to align around this platform, a culture of reusability has grown. We’ve seen a reduction in duplication of effort -- in some cases by up to 50% -- across the organization from case management to risk and fraud.

How USCIS Powered a Digital Transition to eProcessing with Kafka

Episode 1 of the Legacy Modernization Forum Series

In the face of heightened demands for greater scalability, improved resiliency and continuous stream processing, traditional messaging and legacy architectures are being disrupted by real-time event streaming and its ability to meet these new demands.

Join us for an interactive discussion to explore Apache Kafka, the foundation of Confluent Cloud and Confluent Platform, and compare it to traditional messaging queues.

Evolving from Messaging to Event Streaming (Ep 1: Legacy Modernization Series)

The Oak Ridge Leadership Facility (OLCF) in the National Center for Computational Sciences (NCCS) division at Oak Ridge National Laboratory (ORNL) houses world-class high-performance computing (HPC) resources and has a history of operating top-ranked supercomputers on the TOP500 list, including the world's current fastest, Summit, an IBM AC922 machine with a peak of 200 petaFLOPS. With the exascale era rapidly approaching, the need for a robust and scalable big data platform for operations data is more important than ever. In the past when a new HPC resource was added to the facility, pipelines from data sources spanned multiple data sinks which oftentimes resulted in data silos, slow operational data onboarding, and non-scalable data pipelines for batch processing. Using Apache Kafka as the message bus of the division's new big data platform has allowed for easier decoupling of scalable data pipelines, faster data onboarding, and stream processing with the goal to continuously improve insight into the HPC resources and their supporting systems. This talk will focus on the NCCS division's transition to Apache Kafka over the past few years to enhance the OLCF's current capabilities and prepare for Frontier, OLCF's future exascale system; including the development and deployment of a full big data platform in a Kubernetes environment from both a technical and cultural shift perspective. This talk will also cover the mission of the OLCF, the operational data insights related to high-performance computing that the organization strives for, and several use-cases that exist in production today.

Enabling Insight to Support World-Class Supercomputing

The banking and financial services industries are under pressure to adapt to supporting real-time payments along with new and updated standards like ISO 20022, RTP and FedNow. There are common challenges for banks looking to modernize their legacy payment systems in order to handle real-time payments. These challenges require firms to re-evaluate the tools in their toolbox and build a more modern, flexible and scalable payment system without a big-bang rip and replace.

Intelligence, the logic of encoding, decoding and transforming payment types and formats, and orchestrating interactions with bank systems, so that massive payment volumes can be processed with sub-second SLAs. The systems should be flexible to model processes that may be unique to every organization and to facilitate the building of value-added payment services.

The delivery system needs to be able to reliably move data from multiple channels and multiple technologies (files, RDBMS, message queues etc) into and out of the Brains of the Operation to process real-time payments and integrate systems across the bank. The platform needs to be secure, scalable and 100% reliable by design - The Central Nervous System – Confluent, Kafka.
 
What You Will Learn By Attending? 
--How financial institutions are choosing the right technology in developing their next-generation payment architectures in support of real-time corporate payment processing, on and off the cloud
--What is critical in deploying the payment solution, where do you start when building your next generation environment and addressing emerging issues within the banking industry?
--What is Apache Kafka® and why this is quickly becoming the most pervasive technology in core banking transformation. 

Agility is vital, so join us to learn how to clear settlements in seconds vs. days and set your company up for success with the real-time payment journey

The Race to Real-Time: Real-Time Payments and Event Streaming

As part of our Confluent Industry Series, we are excited to invite you to join the Retail Forum. In this era of omni-channel retail, consumers are creating more data than ever before. For a retailer, real-time streaming data across the business can help drive insights into customer behaviors and improve business outcomes.

The future of retail is data, and that future requires the ability to process and use data events in real time. The essence of this effort is event streaming, the continuous, centralized processing of data so it can be used to trigger all kinds of events in real time.

In this session industry luminary and author Kai Waehner will share real-world use cases and architectures from Walmart and other enterprises to improve the Supply Chain Management (SCM) optimization along with industry insights, use cases and share best practices. Confluent delivers an event streaming platform that helps retailers connect all their data in real time.

The Ongoing Disruption of Retail - A Shift to Real-Time Data Streaming

Today’s data sources are fast-moving and dispersed, which can leave businesses and engineers struggling to deliver data and applications in real-time. While this can be hard, we know it doesn’t have to be - because we’ve already made it easy.

With source and sink connectors deployed with just a few clicks, Confluent and MongoDB Atlas are making it simple to stream data from any source directly into MongoDB, regardless of which cloud you use. Our fully managed solution, built on Apache Kafka, brings forward the best of the multi-cloud document database service, MongoDB Atlas, by filling it with real-time data. Together, we can set your data in motion, and with that, help you build fast moving applications enriched with historical context and gain insights that give your business a competitive advantage.

Join this webinar to learn:

- What challenges exist with disconnected data sources and legacy systems
- How businesses are leveraging best-in-class streaming and database technologies to address modern business expectations
- How to build robust and reactive modern data pipelines and applications with a fully managed service

Build Fully Managed Data Pipelines with MongoDB Atlas and Confluent

Apache Kafka

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Build Fully Managed Data Pipelines with MongoDB Atlas and Confluent

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Confluent North America