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 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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Request Response Data Exchange with Apache Kafka vs CQRS and Event Sourcing
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When to use Request-Response with Apache Kafka?

How can I do request-response communication with Apache Kafka? That’s one of the most common questions I get regularly. This blog post explores when (not) to use this message exchange pattern, the differences between synchronous and asynchronous communication, the pros and cons compared to CQRS and event sourcing, and how to implement request-response within the data streaming infrastructure.
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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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JMS Message Queue vs Apache Kafka Comparison
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Comparison: JMS Message Queue vs. Apache Kafka

Comparing JMS-based message queue (MQ) infrastructures and Apache Kafka-based data streaming is a widespread topic. Unfortunately, the battle is an apple-to-orange comparison that often includes misinformation and FUD from vendors. This blog post explores the differences, trade-offs, and architectures of JMS message brokers and Kafka deployments. Learn how to choose between JMS brokers like IBM MQ or RabbitMQ and open-source Kafka or serverless cloud services like Confluent Cloud.
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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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Legacy Modernization and Hybrid Multi Cloud with Apache Kafka in Healthcare
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Legacy Modernization and Hybrid Multi-Cloud with 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. This is part two: Legacy modernization and hybrid multi-cloud. Examples include Optum / UnitedHealth Group, Centene, and Bayer.
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Data Streaming with Apache Kafka in the Healthcare Industry
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Apache Kafka in the Healthcare Industry

IT modernization and innovative new technologies change the healthcare industry significantly. This blog series explores real-world examples of data streaming with Apache Kafka to increase efficiency, reduce cost, and improve the human experience across the healthcare value chain including pharma, insurance, providers, retail, and manufacturing. This is part one: Overview.
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Apache Kafka Transactions API vs Big Data Lake and Batch Analytics
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Analytics vs. Transactions in Data Streaming with Apache Kafka

Workloads for analytics and transactions have very unlike characteristics and requirements. Many people think that Apache Kafka is not built for transactions and should only be used for big data analytics. This blog post explores when and how to use Kafka in resilient, mission-critical architectures and when to use the built-in Transaction API.
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