Browsing Tag

Analytics

48 posts
Read More
  • 1.2K views
  • 13 minute read

Flink CEP and Agentic AI: Real-Time Pattern Detection as the Foundation for Autonomous Decisions

AI agents fail in production when they are connected directly to raw event streams. Flink CEP is the missing layer between your data streams and your Agentic AI architecture: it detects meaningful event sequences in real time, reduces hundreds of thousands of raw events to a handful of grounded actionable signals, and makes every autonomous decision deterministic, auditable, and trustworthy enough for enterprise production.
Read More
0
0
0
Shift Left Architecture 2.0 for the Era of Agentic AI with Kafka Flink Iceberg and MCP
Read More
  • 2.4K views
  • 10 minute read

The Shift Left Architecture 2.0: Operational, Analytical and AI Interfaces for Real-Time Data Products

The Shift Left Architecture moves data integration logic into an event-driven architecture where governed data products are built once and served to multiple consumers. The original pattern covered two interfaces: operational via Apache Kafka and analytical via Apache Iceberg. This post introduces the third: AI applications via MCP, powered by a real-time context engine that gives AI agents access to current operational data. Governance spans the full data stack through enterprise catalog tools. Together, the three interfaces turn a single data streaming investment into the foundation for operational, analytical, and AI-powered enterprise software.
Read More
0
0
0
Automotive Innovation with Data Streaming using Apache Kafka Flink Confluent at CARIAD Volkswagen Group VW
Read More
  • 9.7K views
  • 6 minute read

CARIAD’s Unified Data Platform: A Data Streaming Automotive Success Story Behind Volkswagen’s Software-Defined Vehicles

The automotive industry transforms rapidly. Cars are now software-defined vehicles (SDVs) that demand constant, real-time data flow. This post highlights the CARIAD success story inside the Volkswagen Group. CARIAD tackled data fragmentation. It built the Unified Data Ecosystem (UDE). Learn how Confluent’s data streaming platform, powered by Apache Kafka and Flink, serves as the central nervous system. This platform connects millions of vehicles and cloud services globally. The event-driven architecture helps CARIAD achieve faster development, meet compliance (like the EU Data Act), and reduce costs. The platform unlocks high-value use cases, such as predictive maintenance and AI-powered fleet management.
Read More
0
0
0
Data Streaming Lake Warehouse and Lakehouse with Confluent Databricks Snowflake using Iceberg and Tableflow Delta Lake
Read More
  • 19.8K views
  • 12 minute read

Databricks and Confluent Leading Data and AI Architectures – What About Snowflake, BigQuery, and Friends?

Confluent, Databricks, and Snowflake are trusted by thousands of enterprises to power critical workloads—each with a distinct focus: real-time streaming, large-scale analytics, and governed data sharing. Many customers use them in combination to build flexible, intelligent data architectures. This blog highlights how Erste Bank uses Confluent and Databricks to enable generative AI in customer service, while Siemens combines Confluent and Snowflake to optimize manufacturing and healthcare with a shift-left approach. Together, these examples show how a streaming-first foundation drives speed, scalability, and innovation across industries.
Read More
0
0
0
Data Streaming with Apache Kafka and Flink as Backbone for Real Time Cybersecurity at McAfee
Read More
  • 4.6K views
  • 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.
Read More
0
0
0
Lakehouse and Data Streaming - Competitor or Complementary
Read More
  • 12.0K views
  • 12 minute read

How Microsoft Fabric Lakehouse Complements Data Streaming (Apache Kafka, Flink, et al.)

In today’s data-driven world, understanding data at rest versus data in motion is crucial for businesses. Data streaming frameworks like Apache Kafka and Apache Flink enable real-time data processing. Meanwhile, lakehouses like Snowflake, Databricks, and Microsoft Fabric excel in long-term data storage and detailed analysis, perfect for reports and AI training. This blog post explores how these technologies complement each other in enterprise architecture.
Read More
0
0
0
The Shift Left Architecture
Read More
  • 37.3K views
  • 8 minute read

The Shift Left Architecture – From Batch and Lakehouse to Real-Time Data Products with Data Streaming

Data integration is a hard challenge in every enterprise. Batch processing and Reverse ETL are common practices in a data warehouse, data lake or lakehouse. Data inconsistency, high compute cost, and stale information are the consequences. This blog post introduces a new design pattern to solve these problems: The Shift Left Architecture enables a data mesh with real-time data products to unify transactional and analytical workloads with Apache Kafka, Flink and Iceberg. Consistent information is handled with streaming processing or ingested into Snowflake, Databricks, Google BigQuery, or any other analytics / AI platform to increase flexibility, reduce cost and enable a data-driven company culture with faster time-to-market building innovative software applications.
Read More
0
0
0
Data Streaming with Apache Kafka for Industrial IoT in the Automotive Industry at Brose
Read More
  • 5.3K views
  • 3 minute read

Apache Kafka in Manufacturing at Automotive Supplier Brose for Industrial IoT Use Cases

Data streaming unifies OT/IT workloads by connecting information from sensors, PLCs, robotics and other manufacturing systems at the edge with business applications and the big data analytics world in the cloud. This blog post explores how the global automotive supplier Brose deploys a hybrid industrial IoT architecture using Apache Kafka in combination with Eclipse Kura, OPC-UA, MuleSoft and SAP.
Read More
0
0
0
Streaming Analytics SQL API with Apache Kafka Confluent ClickHouse Tinybird
Read More
  • 19.4K views
  • 8 minute read

Apache Kafka and Tinybird (ClickHouse) for Streaming Analytics HTTP APIs

Apache Kafka became the de facto standard for data streaming. However, the combination of an event-driven architecture with request-response APIs is crucial for most enterprise architectures. This blog post explores how Tinybird innovates with a REST/HTTP layer on top of the open source analytics database ClickHouse in the cloud. Integrating Kafka with Tinybird, the benefits of fully managed services like Confluent Cloud, and customer stories from Factorial and FanDuel show why Kafka and analytics databases complement each other for more innovation and faster time-to-market.
Read More
0
0
0
When NOT to use Apache Kafka
Read More
  • 6.5K views
  • 3 minute read

When NOT to Use Apache Kafka? (Lightboard Video)

Apache Kafka is the de facto standard for data streaming to process data in motion. With its significant adoption growth across all industries, I get a very valid question every week: When NOT to use Apache Kafka? What limitations does the event streaming platform have? When does Kafka simply not provide the needed capabilities? How to qualify Kafka out as it is not the right tool for the job? This blog post contains a lightboard video that gives you a twenty-minute explanation of the DOs and DONTs.
Read More
0
0
1