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Streaming Data Product Lifecycle Management

Confluent

Learn how modern data management approaches like data mesh and event-driven architecture (EDA) are used to manage data, key advantages, and how they’re used.

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Troubleshooting Kafka In Production

Data Engineering Podcast

Summary Kafka has become a ubiquitous technology, offering a simple method for coordinating events and data across different systems. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Introducing RudderStack Profiles. Data lakes are notoriously complex.

Kafka 245
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Reducing The Barrier To Entry For Building Stream Processing Applications With Decodable

Data Engineering Podcast

Summary Building streaming applications has gotten substantially easier over the past several years. Despite this, it is still operationally challenging to deploy and maintain your own stream processing infrastructure. It’s the only true SQL streaming database built from the ground up to meet the needs of modern data products.

Process 182
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Tackling Real Time Streaming Data With SQL Using RisingWave

Data Engineering Podcast

Summary Stream processing systems have long been built with a code-first design, adding SQL as a layer on top of the existing framework. RisingWave is a database engine that was created specifically for stream processing, with S3 as the storage layer. Want to see Starburst in action?

SQL 173
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How to Package and Price Embedded Analytics

Just by embedding analytics, application owners can charge 24% more for their product. This framework explains how application enhancements can extend your product offerings. How much value could you add? Brought to you by Logi Analytics.

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The Modern Data Streaming Pipeline: Streaming Reference Architectures and Use Cases Across 7 Industries 

Snowflake

This is driving the importance of streaming data and analytics, which play a crucial role in making better-informed decisions that likely lead to faster, better outcomes. While traditional systems store and process data in batches, streaming data refers to data that is continuously generated from a variety of sources.

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An Overview Of The Sate Of Data Orchestration In An Increasingly Complex Data Ecosystem

Data Engineering Podcast

Summary Data systems are inherently complex and often require integration of multiple technologies. This offers a single location for managing visibility and error handling so that data platform engineers can manage complexity. With Materialize, you can!

BI 208