A Data Streaming Platform (DSP) is composed of six major inter-related components, covered in detail in this video. Each component has evolved over time to servce specific needs in the data streaming platform, but together form a whole that is greater than its sum.

While you can build your own DSP by following the outline in this video, you can also get started immediately with Confluent’s DSP today: [ Ссылка ]

A DSP provides a complete solution for unified end-to-end data streaming. It provides all the necessary capabilities to succeed in data streaming, incuding data connectivity, integration, discovery, security, and management. Ultimately, a DSP makes it easy for you to build, use, and share data all across your organization for any use case.

RELATED RESOURCES
► How to address bad data in your event streams - [ Ссылка ]
► Data best practices and CDC - [ Ссылка ]
► Kafka Connect 101 - [ Ссылка ]
► What is a Headless Data Architecture? - [ Ссылка ]
► How to Evolve your Schemas with Migration Rules - [ Ссылка ]
► How to Improve Data Quality with Domain Validation Rules - [ Ссылка ]
► Organize your data quickly and easily using Confluent Data Portal - [ Ссылка ]

CHAPTERS
00:00 - Introduction, a DSP’s Six Parts
00:30 - Pyramid Model of Data Streaming Evolution
00:46 - Apache Kafka (Part 1)
1:55 - Schema Registry (Part 2)
3:53 - Data Portal (Part 3)
5:44 - Connectors (Part 4)
7:30 - Stream Processor Flink (Part 5)
8:40 - Tableflow (Part 6)
10:33 - Conclusion

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ABOUT CONFLUENT
Confluent is pioneering a fundamentally new category of data infrastructure focused on data in motion. Confluent’s cloud-native offering is the foundational platform for data in motion – designed to be the intelligent connective tissue enabling real-time data, from multiple sources, to constantly stream across the organization. With Confluent, organizations can meet the new business imperative of delivering rich, digital front-end customer experiences and transitioning to sophisticated, real-time, software-driven backend operations. To learn more, please visit www.confluent.io.

#datastreaming #dsp #apachekafka #kafka #confluent

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