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Metadata Management And Integration At LinkedIn With DataHub

Data Engineering Podcast

The key to those solutions is a robust and flexible metadata management system. LinkedIn has gone through several iterations on the most maintainable and scalable approach to metadata, leading them to their current work on DataHub. What were you using at LinkedIn for metadata management prior to the introduction of DataHub?

Metadata 100
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Directory Tables : Access Unstructured Data

Cloudyard

They are used to provide Snowflake access to unstructured datafiles and supports both of internal or external stage Query a directory table helps to retrieve the snowflake hosted file URL for each file present in stage. Directory tables metadata should be refreshed automatically when underlying stage gets updated.

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Async APIs - don't confuse your events, commands and state by David Hope

Scott Logic

I’ve coloured the data entities according to their types and we see there’s a few different patterns like events and state which we’ll discuss in a moment. I’ll use the term message in this blog as a generic term for asynchronous communication that may be state or commands or events.

AWS 52
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Demystifying event streams: Transforming events into tables with dbt

dbt Developer Hub

Let’s discuss how to convert events from an event-driven microservice architecture into relational tables in a warehouse like Snowflake. Quality problems lead to first responders unable to check into disaster sites or parents unable to access ESA funds. So our solution was to start using an intentional contract: Events.

Kafka 52
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A Look Back at the Gartner Data and Analytics Summit

Cloudera

Here are a couple of the biggest takeaways we had from our time at the event. In those discussions, it was clear that everyone understood the need to treat data estates more cohesively as a whole—that means bringing more attention to security, data governance, and metadata management, the latter of which has become increasingly popular.

Metadata 106
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Addressing The Challenges Of Component Integration In Data Platform Architectures

Data Engineering Podcast

Summary Building a data platform that is enjoyable and accessible for all of its end users is a substantial challenge. Developing event-driven pipelines is going to be a lot easier - Meet Functions! Memphis Logo]([link] Developing event-driven pipelines is going to be a lot easier - Meet Functions!

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Kubernetes Prometheus: Definition, Architecture, Pros & Cons

Knowledge Hut

Simply put, every item in a Kubernetes Prometheus store is a metric event that comes with a timestamp. Events are recorded in real time by Prometheus. Any event that is pertinent to your program can be included in this list, including memory usage, network activity, and specific inbound requests.