Real Time Logistics Transportation Shipping with Apache Kafka
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Real-Time Logistics, Shipping, and Transportation with Apache Kafka

Logistics, shipping, and transportation require real-time information to build efficient applications and innovative business models. Data streaming enables correlated decisions, recommendations, and alerts. Kafka is everywhere across the industry. This blog post explores several real-world case studies from companies such as USPS, Swiss Post, Austrian Post, DHL, and Hermes. Use cases include cloud-native middleware modernization, track and trace, and predictive routing and ETA planning.
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Real-Time Supply Chain Control Tower with Apache Kafka
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A Real-Time Supply Chain Control Tower powered by Kafka

A modern supply chain requires just-in-time production, global logistics, and complex manufacturing processes. This blog post explores a solution that ingests all information flows into a unified central nervous system. The idea of the Supply Chain Control Tower becomes a reality: An integrated data cockpit with real-time access to all levels and systems of the supply chain.
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The Heart of the Data Mesh Beats Real Time with Apache Kafka
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The Heart of the Data Mesh Beats Real-Time with Apache Kafka

If there were a buzzword of the hour, it would undoubtedly be “data mesh”! This new architectural paradigm unlocks analytic and transactional data at scale and enables rapid access to an ever-growing number of distributed domain datasets for various usage scenarios. The data mesh addresses the most common weaknesses of the traditional centralized data lake or data platform architecture. And the heart of a decentralized data mesh infrastructure must be real-time, reliable, and scalable. Learn how the de facto standard for data streaming, Apache Kafka, plays a crucial role in building a data mesh.
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Best Practices for Data Analytics with AWS Azure Googel BigQuery Spark Kafka Confluent Databricks
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Best Practices for Building a Cloud-Native Data Warehouse or Data Lake

The concepts and architectures of a data warehouse, a data lake, and data streaming are complementary to solving business problems. Unfortunately, the underlying technologies are often misunderstood, overused for monolithic and inflexible architectures, and pitched for wrong use cases by vendors. Let’s explore this dilemma in a blog series. This is part 5: Best Practices for Building a Cloud-Native Data Warehouse or Data Lake.
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Case Studies for Cloud Native Analytics with Data Warehouse Data Lake Data Streaming Lakehouse
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Case Studies: Cloud-native Data Streaming for Data Warehouse Modernization

The concepts and architectures of a data warehouse, a data lake, and data streaming are complementary to solving business problems. Unfortunately, the underlying technologies are often misunderstood, overused for monolithic and inflexible architectures, and pitched for wrong use cases by vendors. Let’s explore this dilemma in a blog series. This is part 4: Case Studies for cloud-native data streaming and data warehouses.
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Data Warehouse and Data Lake Modernization with Data Streaming
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Data Warehouse and Data Lake Modernization: From Legacy On-Premise to Cloud-Native Infrastructure

The concepts and architectures of a data warehouse, a data lake, and data streaming are complementary to solving business problems. Unfortunately, the underlying technologies are often misunderstood, overused for monolithic and inflexible architectures, and pitched for wrong use cases by vendors. Let’s explore this dilemma in a blog series. This is part 3: Data Warehouse Modernization: From Legacy On-Premise to Cloud-Native Infrastructure.
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Data Warehouse vs Data Lake vs Data Streaming Comparison
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Data Warehouse vs. Data Lake vs. Data Streaming – Friends, Enemies, Frenemies?

The concepts and architectures of a data warehouse, a data lake, and data streaming are complementary to solving business problems. Unfortunately, the underlying technologies are often misunderstood, overused for monolithic and inflexible architectures, and pitched for wrong use cases by vendors. Let’s explore this dilemma in a blog series. This is part 1: Data Warehouse vs. Data Lake vs. Data Streaming – Friends, Enemies, Frenemies?
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Kafka in Healthcare - Open API and Omnichannel Data Streaming
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Open API and Omnichannel with Apache Kafka in Healthcare

IT modernization and innovative new technologies change the healthcare industry significantly. This blog series explores how data streaming with Apache Kafka enables real-time data processing and business process automation. Real-world examples show how traditional enterprises and startups increase efficiency, reduce cost, and improve the human experience across the healthcare value chain, including pharma, insurance, providers, retail, and manufacturing. This is part five: Open API and Omnichannel. Examples include Care.com and Invitae.
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Cybersecurity in Crypto and FinTech with Data Streaming and Apache Kafka
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Apache Kafka in Crypto and FinServ for Cybersecurity and Fraud Detection

The insane growth of the crypto and fintech market brings many unknown risks and successful cyberattacks to steal money and crypto coins. This post explores how data streaming with the Apache Kafka ecosystem enables real-time situational awareness and threat intelligence to detect and prevent hacks, money loss, and data breaches. Enterprises stay compliant with the law and keep customers happy in any innovative Fintech or Crypto application.
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Real Time Analytics and Machine Learning with Apache Kafka in Healthcare
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Real Time Analytics with Apache Kafka in the Healthcare Industry

IT modernization and innovative new technologies change the healthcare industry significantly. This blog series explores how data streaming with Apache Kafka enables real-time data processing and business process automation. This is part four: Real-Time Analytics. Examples include Cerner, Celmatix, CDC/Centers for Disease Control and Prevention.
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