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By Confluent Staff
Integrating OpenAI with BigQuery unlocks powerful possibilities for AI-powered data analysis and advanced insight generation. This guide explores how the OpenAI BigQuery integration enables businesses to transform their data warehouses into intelligent analytics powerhouses.
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By Confluent Staff
Predictive analytics is changing how businesses make decisions. Companies can use data, machine learning, and statistical modeling to forecast outcomes with better accuracy. So, how can predictive analytics techniques transform your business? Predictive analytics uses historical data to predict future events. It involves understanding the relationships within your data to predict what's next, impacting industries from retail and healthcare to finance and manufacturing.
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By Confluent Staff
Implementing predictive analytics in healthcare empowers healthcare providers to take a data-driven approach to anticipating future events and making informed decisions. It helps healthcare professionals forecast the progression of diseases, plan and optimize resource allocation, and ultimately shift from reactive to proactive care. This approach improves patient health outcomes and overall efficiency.
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By Arun Singhal
In the world of data processing and messaging systems, terms like "queue" and "streaming" often pop up. While they might sound similar, they serve different purposes, and can significantly impact how your system handles data. Let’s break down the differences in a straightforward way.
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By Varsha Nagele
We hosted our first-ever Confluent AI Day on October 23 in San Francisco and virtually. It was sponsored by Confluent, AWS, and MongoDB, with a vibrant gathering of talent and innovation. With 200 attendees, the full-day event brought together AI developers, technology leaders, and startup innovators to explore how data streaming powers generative AI (GenAI) applications.
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By Sandon Jacobs
Designing microservices using an event-driven approach has several benefits, including improved scalability, easier maintenance, clear separation of concerns, system resilience, and cost savings. With Apache Kafka as an event plane, services now have a durable, scalable, and reliable source of event data. From Kafka topics, a microservice can easily rebuild and restore the state of the data used to serve end users.
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By Nusair Haq
From humble beginnings, Apache Kafka steadily rose to prominence and now sits as the backbone of data streaming for thousands of organizations worldwide. From its robust API, cloud-native implementations like Confluent Cloud, and synergy with other technologies like Apache Flink, Kafka has grown to cover many use cases across a broad range of industries.
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By Chris Potter
In the fast-paced world of data, where volume, variety, and velocity are constantly pushing boundaries, organizations are facing unprecedented challenges in integrating and harnessing data at scale effectively. Gartner just published the 2024 Magic QuadrantTM for Data Integration Tools, which recognized Confluent as a Challenger. Previously, Confluent was positioned as a Niche player in the 2023 Magic Quadrant for Data Integration Tools.
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By Confluent Staff
In today’s fast-paced technological landscape, staying ahead means more than just keeping up with the latest trends—it requires a fundamental shift in how businesses operate in increasingly digital spaces. AppDirect, a digital-native company at the forefront of innovation, has fully embraced this digital paradigm, aligning itself with modern business approaches that enhance both operational efficiency and customer experience.
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By Confluent
Confluent Manager for Apache Flink provides a cloud-like management experience for on-premises Kubernetes environments.
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By Confluent
A short live demo on how to easily migrate from Zookeeper to Kraft with Confluent for Kubernetes (CFK) in 4 simple steps.
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By Confluent
Producer retries in Apache Kafka can make or break message delivery, especially during broker events like updates or failures. Use the idempotent producer, and configure delivery timeouts, in order to avoid common pitfalls that lead to lost messages or broken ordering.
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By Confluent
Picking the wrong partition key in Apache Kafka? That’s a fast track to performance headaches—think unbalanced loads, slowdowns, and broken message ordering. Choosing the right partitioning strategy keeps your data flowing smoothly and avoids hot partitions.
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By Confluent
Constantly starting and stopping Apache Kafka producers and consumers? That’s a recipe for high resource usage and inefficiency. Short-lived connections are heavy on resources, and can slow down your whole cluster. Keep them running to boost performance, cut latency, and get the most out of your Kafka setup.
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By Confluent
Default settings in Apache Kafka work when you’re getting started, but aren't suited for production. Sticking with defaults, like a seven-day retention policy, or a replication factor of one, can cause storage issues, or data loss in case of failure. Learn why optimizing retention periods, replication factors, and partitions, is crucial for better Kafka performance and reliability.
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By Confluent
Keeping your Apache Kafka clients up-to-date is critical for maximizing performance, security, and stability. In this video, we discuss why sticking with old versions could be putting you at risk, since it means you’re missing out on dozens of new features, and hundreds of bug fixes and security patches. Learn why upgrading is more than just a “nice-to-have”—it’s essential for a smoother and safer Kafka experience.
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By Confluent
Setting up network connections can often seem difficult or time consuming. This video provides a wayfinding introduction to help you get networking up and running for all cluster types on Confluent Cloud, showing you your networking options for each cluster type when running on AWS, Azure, or Google Cloud, respectively.
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By Confluent
In this short video, a Confluent Solutions Engineering will run through the high-level steps on how to get started with your migration. And even better, once you’re done watching, you can download our comprehensive migration kit for a step by step guide of everything I’ve talked about and more.
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By Confluent
Kafka Connectors provide a way to get data flowing between your sources and sinks, and Confluent Cloud. This video reviews your options and shows you how to get started quickly.
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By Confluent
This video provides a tour of the main Confluent Cloud interface, and shows you how to set up your first cluster.
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By Confluent
Traditional messaging middleware like Message Queues (MQs), Enterprise Service Buses (ESBs), and Extract, Transform and Load (ETL) tools have been widely used for decades to handle message distribution and inter-service communication across distributed applications. However, they can no longer keep up with the needs of modern applications across hybrid and multi cloud environments for asynchronicity, heterogeneous datasets and high volume throughput.
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By Confluent
Why a data mesh? Predicated on delivering data as a first-class product, data mesh focuses on making it easy to publish and access important data across your organization. An event-driven data mesh combines the scale and performance of data in motion with product-focused rigor and self-service capabilities, putting data at the front and center of both operational and analytical use-cases.
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By Confluent
When it comes to fraud detection in financial services, streaming data with Confluent enables you to build the right intelligence-as early as possible-for precise and predictive responses. Learn how Confluent's event-driven architecture and streaming pipelines deliver a continuous flow of data, aggregated from wherever it resides in your enterprise, to whichever application or team needs to see it. Enrich each interaction, each transaction, and each anomaly with real-time context so your fraud detection systems have the intelligence to get ahead.
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By Confluent
Many forces affect software today: larger datasets, geographical disparities, complex company structures, and the growing need to be fast and nimble in the face of change. Proven approaches such as service-oriented (SOA) and event-driven architectures (EDA) are joined by newer techniques such as microservices, reactive architectures, DevOps, and stream processing. Many of these patterns are successful by themselves, but as this practical ebook demonstrates, they provide a more holistic and compelling approach when applied together.
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By Confluent
Data pipelines do much of the heavy lifting in organizations for integrating, transforming, and preparing data for subsequent use in data warehouses for analytical use cases. Despite being critical to the data value stream, data pipelines fundamentally haven't evolved in the last few decades. These legacy pipelines are holding organizations back from really getting value out of their data as real-time streaming becomes essential.
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By Confluent
In today's fast-paced business world, relying on outdated data can prove to be an expensive mistake. To maintain a competitive edge, it's crucial to have accurate real-time data that reflects the status quo of your business processes. With real-time data streaming, you can make informed decisions and drive value at a moment's notice. So, why would you settle for being simply data-driven when you can take your business to the next level with real-time data insights??
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By Confluent
Data pipelines do much of the heavy lifting in organizations for integrating and transforming and preparing the data for subsequent use in downstream systems for operational use cases. Despite being critical to the data value stream, data pipelines fundamentally haven't evolved in the last few decades. These legacy pipelines are holding organizations back from really getting value out of their data as real-time streaming becomes essential.
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By Confluent
Shoe retail titan NewLimits relies on a jumble of homegrown ETL pipelines and batch-based data systems. As a result, sluggish and inefficient data transfers are frustrating internal teams and holding back the company's development velocity and data quality.
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Connect and process all of your data in real time with a cloud-native and complete data streaming platform available everywhere you need it.
Data streaming enables businesses to continuously process their data in real time for improved workflows, more automation, and superior, digital customer experiences. Confluent helps you operationalize and scale all your data streaming projects so you never lose focus on your core business.
Confluent Is So Much More Than Kafka:
- Cloud Native: 10x Apache Kafka® service powered by the Kora Engine.
- Complete: A complete, enterprise-grade data streaming platform.
- Everywhere: Availability everywhere your data and applications reside.
Apache Kafka® Reinvented for the Data Streaming Era