Browsing Tag

Real Time

46 posts
Apache Kafka 4.0 - The Business Case for Data Streaming at Enterprise Scale
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  • 7 minute read

Apache Kafka 4.0: The Business Case for Scaling Data Streaming Enterprise-Wide

Apache Kafka 4.0 represents a major milestone in the evolution of real-time data infrastructure. Used by over 150,000 organizations worldwide, Kafka has become the de facto standard for data streaming across industries. This article focuses on the business value of Kafka 4.0, highlighting how it enables operational efficiency, faster time-to-market, and architectural flexibility across cloud, on-premise, and edge environments. Rather than detailing technical improvements, it explores Kafka’s strategic role in modern data platforms, the growing data streaming ecosystem, and how enterprises can turn event-driven architecture into competitive advantage. Kafka is no longer just infrastructure—it’s a foundation for digital business
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Retail Media with Data Streaming using Apache Kafka and Flink
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  • 1.9K views
  • 8 minute read

Retail Media with Data Streaming: The Future of Personalized Advertising in Commerce

Retail media is reshaping digital advertising by using first-party data to deliver personalized, timely ads across online and in-store channels. As retailers build retail media networks, they unlock new revenue opportunities while improving ad effectiveness and customer engagement. The key to success lies in real-time data streaming, which enables instant targeting, automated bidding, and precise attribution. Technologies like Apache Kafka and Apache Flink make this possible, helping retailers like Albertsons enhance ad performance and maximize returns. This post explores how real-time streaming is driving the evolution of retail media
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How Data Streaming and AI Help Telcos - Top 5 Trends from MWC 2025
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  • 7 minute read

How Data Streaming and AI Help Telcos to Innovate: Top 5 Trends from MWC 2025

As the telecom and tech industries rapidly evolve, real-time data streaming is emerging as the backbone of digital transformation. For MWC 2025, McKinsey outlined five key trends defining the future: IT excellence, sustainability, 6G, generative AI, and AI-driven software development. This blog explores how data streaming powers each of these trends, enabling real-time observability, AI-driven automation, energy efficiency, ultra-low latency networks, and faster software innovation. From Dish Wireless’ cloud-native 5G network to Verizon’s edge AI deployments, leading companies are leveraging event-driven architectures to gain a competitive advantage. Whether you’re tackling network automation, sustainability challenges, or AI monetization, data streaming is the strategic enabler for 2025 and beyond. Read on to explore the latest use cases, industry insights, and how to future-proof your telecom strategy.
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Online Model Training and Model Drift in Machine Learning with Apache Kafka and Flink
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  • 5 minute read

Online Model Training and Model Drift in Machine Learning with Apache Kafka and Flink

The rise of real-time AI and machine learning is reshaping the competitive landscape. Traditional batch-trained models struggle with model drift, leading to inaccurate predictions and missed opportunities. Platforms like Apache Kafka and Apache Flink enable continuous model training and real-time inference, ensuring up-to-date, high-accuracy predictions. This blog explores TikTok’s groundbreaking AI architecture, its use of data streaming for real-time recommendations, and how businesses can leverage Kafka and Flink to modernize their ML pipelines. I also examine how data streaming complements platforms like Databricks, Snowflake, and Microsoft Fabric to create scalable, adaptive AI systems.
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Top 10 Real Time Innovations in FinServ with Data Streaming using Apache Kafka and Flink
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  • 10 minute read

How Data Streaming with Apache Kafka and Flink Drives the Top 10 Innovations in FinServ

The financial industry is rapidly shifting toward real-time, intelligent, and seamlessly integrated services. From IoT payments and AI-driven banking to embedded finance and RegTech, financial institutions must process vast amounts of data instantly and securely. Data Streaming with Apache Kafka and Apache Flink provides the backbone for real-time payments, fraud detection, personalized financial insights, and compliance automation. This blog post explores the top 10 emerging financial technologies and how data streaming enables them, helping banks, fintechs, and central institutions stay ahead in the future of finance.
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Data Streaming with Apache Kafka and Flink as Backbone for Real Time Cybersecurity at McAfee
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  • 5 minute read

The Role of Data Streaming in McAfee’s Cybersecurity Evolution

In today’s digital landscape, cybersecurity faces mounting challenges from sophisticated threats like ransomware, phishing, and supply chain attacks. Traditional defenses like antivirus software are no longer sufficient, prompting the adoption of real-time, event-driven architectures powered by data streaming technologies like Apache Kafka and Flink. These platforms enable real-time threat detection, prevention, and response by processing massive amounts of security data from endpoints and systems. A success story from McAfee highlights how transitioning to an event-driven architecture with Kafka in Confluent Cloud has enhanced scalability, operational efficiency, and real-time protection for millions of devices. As cybersecurity threats evolve, data streaming proves essential for organizations aiming to secure their digital assets and maintain trust in an interconnected world.
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Dynamic Pricing with Data Streaming using Apache Kafka and Flink
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  • 8 minute read

A New Era in Dynamic Pricing: Real-Time Data Streaming with Apache Kafka and Flink

In the age of digitization, the concept of pricing is no longer fixed or manual. Instead, companies increasingly use dynamic pricing — a flexible model that adjusts prices based on real-time market changes to enable real-time responsiveness, giving companies the tools they need to respond instantly to demand, competitor prices, and customer behaviors. This blog post explores the fundamentals of dynamic pricing, its link to data streaming, and real-world examples across different industries such as retail, logistics, gaming and the energy sector.
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How Intersport uses Apache Kafka as Database with Compacted Topic in Retail
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  • 6 minute read

How the Retailer Intersport uses Apache Kafka as Database with Compacted Topic

Compacted Topic is a feature of Apache Kafka to persist and query the latest up-to-date event of a Kafka Topic. The log compaction and key/value search is simple, cost-efficient and scalable. This blog post shows in a success story of Intersport how some use cases store data long term in Kafka with no other database. The retailer requires accurate stock info across the supply chain, including the point of sale (POS) in all international stores.
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From Smart Factory to Cloud with Data Streaming
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  • 4 minute read

Data Streaming from Smart Factory to Cloud

A smart factory organizes itself without human intervention to produce the desired products. This blog post explores how data streaming powered by Apache Kafka helps connect and move data to the cloud at scale in real-time, including a case study from BMW and a simple lightboard video about the related enterprise architecture.
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