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Manufacturing Issue 5.0 - May 2025 Follow the Stream Your Dedicated Community Content Scroll 

Unlocking New Data Streaming Use Cases!

Welcome to the fifth edition of the Follow the Stream content scroll! In this issue, we’ll focus on real-world use cases and the latest implementations of data streaming in the manufacturing and automotive industries. Featuring industry and 2025 data streaming trends, we’ll explore how industry leaders are leveraging real-time data for predictive maintenance, supply chain optimization, digital twins, and energy efficiency.
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Data Streaming Fundamentals

Data Streaming Crash Course 

Let's explore the basics of data streaming for manufacturing.

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Check out Confluent's Lightboard series on use cases in the manufacturing industry and why so many global manufacturing companies rely on data streaming. Learn how to get end-to-end visibility into an original equipment manufacturer (OEM) supply chain by leveraging data streaming for operational technology (OT) and IT data—and how it helps modernize and innovate the entire engineering and sales life cycle.
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Anchor: General-Updates

Industry in Motion: General Updates

2025 Data Streaming Report: Moving the Needle on AI Adoption, Speed to Market, & ROI

In the age of AI, real-time, contextual, and trustworthy data is crucial. The 2025 Data Streaming Report reveals how 4,175 IT leaders view data streaming platforms (DSPs) as pivotal for simplifying access to real-time data, accomplishing data-related goals, and enhancing AI adoption and innovation. With DSPs offering significant return on investment (ROI) and 44% of IT leaders reporting 5x returns, 90% are increasing their investments for faster innovation and data value gains. 
Key findings:
  • Data streaming ROI hits new highs.
  • DSPs emerge as business imperative.
  • DSPs enable AI success.
  • Shifting left maximizes data value.
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Available in German, French, Spanish, and Italian!

Introducing Apache Kafka® 4.0

Kafka 4.0 is here, and it’s a big leap forward. This release removes Apache ZooKeeper™, making Kafka simpler to run and scale with KRaft mode as the default. It also introduces a faster, more reliable consumer group protocol and early access to queue-style messaging. With cleaner APIs, updated Java requirements, and new features across Kafka Streams and Kafka Connect, the new version is built for the future of data streaming. 

The Data Streaming World Tour 2025 Is Hitting the Road!

Join for an opportunity to network with peers and ecosystem partners, hear directly from customers, learn from Confluent's team of Apache Kafka® experts, and roll up your sleeves in interactive demonstrations and hands-on labs.
Upcoming Dates: June 4: Calgary - RSVP June 5: Tokyo - RSVP June 5: Detroit - RSVP June 10: Rome - RSVP June 17: Cairo - RSVP June 17: Atlanta - RSVP June 18: Barcelona - RSVP
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Top Trends for Data Streaming With Apache Kafka® and Apache Flink® in 2025

"Apache Kafka® and Apache Flink® are leading open-source frameworks for data streaming that serve as the foundation for cloud services, enabling organizations to unlock the potential of real-time data. Over recent years, trends have shifted from batch-based data processing to real-time analytics, scalable cloud-native architectures, and improved data governance powered by these technologies. Looking ahead to 2025, the data streaming ecosystem is set to undergo even greater changes, featuring trends like Democratization of Kafka, BYOC Deployment Model, and Data Streaming Organizations.
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Anchor: Executives-Brief

Executive's Brief: Data Strategy & Leadership

The Practical Guide to Building Data Products for IT Leaders

The challenge of "analysis paralysis" occurs when organizations are presented with a wide range of data product options. Sorting through complex systems to determine the most valuable data solutions can be time-consuming and costly. But a simple, strategic framework can help quickly identify the most impactful data products, focusing on value rather than just cost. This approach allows for efficient decision-making and prioritization, whether starting a new project or optimizing an existing system. 
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Available in German, French, and Spanish!

Why Automotive and Manufacturing Companies Love Data Streaming

“For companies in automotive and manufacturing, data is no longer static—it’s a continuously evolving asset.” Automotive and manufacturing companies embrace data streaming because it enables real-time, seamless data flow across systems like production lines and supply chains. It eliminates silos, integrates IT and OT, and supports AI-driven optimizations. With continuous, up-to-date data, manufacturers can make faster decisions, improve efficiency, and shift data quality management upstream for more reliable insights.
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Available in German, French, and Spanish!

Data Accessibility: The Key to a Data-Driven Business Strategy

Easy access to data is essential for smarter decisions, efficient operations, and innovation. While many organizations struggle with siloed, hard-to-use data, BMW Group overcame these challenges with a strategic approach to data accessibility. Its solution involved creating a central hub for real-time data streaming that connects edge Internet of Things (IoT) data from production plants to cloud applications and services. 
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Building a Data-Driven Culture: How to Empower Teams With Insights

Leadership plays a crucial role in fostering a data-driven culture, beyond just providing the right tools. It requires an ongoing commitment to building systems and processes that turn data into actionable insights. Leaders must promote continuous learning, invest in infrastructure, support cultural changes, and reward data-driven decisions. By bridging the gap between technical and business teams, encouraging transparency, and celebrating data-driven successes, leaders create an environment where innovation thrives.
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Anchor: Customer-Experience

Data Streaming for Supply Chain Resilience

How Data Streaming Drives Supply Chain Success

Data streaming has emerged as a critical technology for modern supply chains, offering numerous benefits that drive significant business value, from improved decision-making to customer satisfaction and loyalty:
  • Enhanced Visibility & Transparency – Real-time, end-to-end supply chain visibility allows seamless monitoring and tracking of goods and materials.
  • Reduced Lead Times – Predictive analytics optimize inventory levels, reducing lead times and improving customer satisfaction.
  • Sustainability & Compliance – Efficient resource use minimizes waste and ensures regulatory compliance.
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Available in German, French, and Spanish!
Anchor: Architects-Blueprint

Architect's Blueprint: Data Systems Design

The Data Streaming Use Case Show: Manufacturing and Automotive

Join Kai Waehner, Global Field CTO at Confluent, for the debut episode of the Data Streaming Use Case Show, where he’s joined by experts from Siemens Digital Industries and Siemens Healthineers to unpack the stories, strategies, and insights of their data streaming journeys. This episode dives into how Siemens is building real-time data products and enabling smart factories through data streaming, featuring behind-the-scenes insights, customer stories, and a live lightboard session that breaks down enterprise architecture in action.
Watch First Episode
Available in Japanese and Korean!
Anchor: must-read

Leveraging Data Streaming for Proactive Equipment Maintenance: Predict and Prevent Failures

Condition monitoring and predictive maintenance continuously track equipment on the shop floor using IoT sensors and advanced analytics to collect real-time performance data, identify patterns, and predict maintenance needs. Analyzing this data in real time on a central platform allows for instant anomaly detection, which helps prevent breakdowns, reduce downtime, lower maintenance costs, and improve overall equipment effectiveness (OEE).
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Available in German, French, and Spanish!

3 Strategies for Achieving Data Efficiency in Modern Organizations

In today's digital age, data efficiency is essential for modern organizations to handle the exponential growth of data. Three strategies for achieving this are implementing no-copy and zero ETL solutions to minimize data duplication, shifting left data governance to address data quality issues closer to the source, and reducing data waste by processing data as close to the source as possible.
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Powering Track and Trace Use Cases With Data Streaming

Track-and-trace solutions use IoT devices and advanced applications to offer real-time monitoring of tools, equipment, and products across the supply chain, enhancing visibility and transparency. This approach ensures:
  • Improved Inventory Management – Accurate, real-time data optimizes inventory levels, reducing overstock and stockouts.
  • Loss Prevention – Continuous monitoring helps prevent losses due to theft, misplacement, or damage by providing timely alerts.
  • Increased Supply Chain Efficiency – Streamlined tracking processes reduce delays, leading to faster order fulfillment and improved responsiveness.
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Anchor: Developers-Desk

Developer's Desk: Building Applications

A Technical Guide: How to Optimize Data Ingestion into Lakehouses & Warehouses

In the rapidly evolving landscape of data management and processing, the concept of shifting left has emerged as a key strategy for enhancing data operations. Confluent’s guide outlines the principles, technical components, and governance practices essential to implementation of shifting left with a DSP. Designed for data and analytics professionals, it offers practical steps for enhancing data reliability and efficiency at scale as well as real-world examples demonstrating streamlined ingestion, enhanced governance, and simplified conversion of Kafka topics into Apache Iceberg™ tables.
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New Webinar! Getting Started with Apache Kafka® and Real-Time Data Streaming

This session is an in-depth look at how Apache Kafka supports modern data streaming platforms and real-time business transformation. It covers Kafka’s architecture and a range of real-world use cases—from stock trading and fraud detection to transportation—highlighting how organizations are leveraging data streaming to improve agility and foster innovation.
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Processing Without Pause: Continuous Stream Processing and Apache Flink®

The second episode of Confluent’s new podcast “Life Is But a Stream” dives even deeper into the fundamentals of data streaming to explore stream processing—what it is, the best tools and frameworks, and its real-world applications. Anna McDonald, Confluent’s Distinguished Technical Voice of the Customer, and Abhishek Walia, Staff Customer Success Technical Architect at Confluent, break down what stream processing is, how it differs from batch processing, and why tools such as Flink are game changers. 
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Building Streaming Data Pipelines, Part 1: Data Exploration With Tableflow

Tableflow enables seamless querying of Kafka topics by syncing them to Iceberg tables, making real-time data exploration easier using standard SQL tools such as Trino and PopSQL. In this example, sensor data from the U.K. Environment Agency is ingested into Kafka, exposed via Tableflow, and analyzed by joining related datasets to build a denormalized view. This process lays the groundwork for building streaming data pipelines with a clear understanding of the underlying data.
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Ready to break up with ZooKeeper? KRaft, you had me at hello.

KRaft introduces a modern architecture for Kafka by replacing ZooKeeper with a built-in consensus protocol, streamlining metadata management and simplifying operations. Confluent’s new webinar features two product demos—initial setup and migration to KRaft—along with a readiness checklist for deploying ZooKeeper-less Kafka in self-managed environments. With production-ready KRaft, organizations gain improved scalability, reduced operational complexity, and enhanced system reliability.
Watch Online Talk
Available in Japanese!

Learn About Data Streaming With Apache Kafka® and Apache Flink®

High-throughput low latency distributed event streaming platform. Available locally or fully-managed via Apache Kafka on Confluent Cloud.

High-performance stream processing at any scale. Available via Confluent Cloud for Apache Flink.

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Anchor: Innovation-Research

Data Streaming for Innovation & Research

IoT With Data Streaming for Innovative Consumer Experiences

Data streaming in consumer IoT enables real-time personalization and instant responses to user behavior, creating smoother, more engaging customer experiences. By processing data as it's generated, businesses can deliver timely insights, adapt services dynamically, and drive continuous innovation. This immediacy enhances customer satisfaction, operational efficiency, and overall competitiveness.
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Available in German, French, and Spanish!

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