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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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ConsoleMe: A Central Control Plane for AWS Permissions and Access

Netflix Tech

ConsoleMe: A Central Control Plane for AWS Permissions and Access By Curtis Castrapel , Patrick Sanders , and Hee Won Kim At AWS re:Invent 2020, we open sourced two new tools for managing multi-account AWS permissions and access. They are the one-stop-shop for cloud permissions and access. This happened for us at Netflix.

AWS 100
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Solving The Persistent Challenges of Data Modeling

The Modern Data Company

Manages information about data access and monitors data quality. It’s a combination of the data itself, the metadata (information about the data), code (the set of instructions on how to process or analyze the data), and infrastructure (the technological framework that supports it all).

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Introducing Vector Search on Rockset: How to run semantic search with OpenAI and Rockset

Rockset

To highlight these new capabilities, we built a search demo using OpenAI to create embeddings for Amazon product descriptions and Rockset to generate relevant search results. In the demo, you’ll see how Rockset delivers search results in 15 milliseconds over thousands of documents.

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Our product vision for analytics in the age of AI

ThoughtSpot

As a result, end users expect faster response times and easier access to meaningful insights. Not only does ThoughtSpot not store your sample data or metadata, or use this information for model training, but we are also investing in bring-your-own and host-your-own model capabilities for both generative AI and machine learning models.

BI 89
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Snowflake and S3 Data Lake

Cloudyard

Moreover, We will use the below architecture to showcase the Demo where convert the existing Data Lake to Snowflake Deployment. DMS For this Demo we launched RDS service for ORACLE in AWS and created some tables. Kinesisdest:Bucket to hold Streaming data i.e. JSON file Externalbucketstream:Bucket to hold In frequent access data.

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Exploring Innovations in Data Integrity

Precisely

In the same way that big cloud-platform providers offer simplified access to infrastructure, and data cloud providers like Databricks and Snowflake have vastly simplified access to data and analytics, modern data integrity tools must streamline and automate data integrity processes.