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Introducing Lakehouse Apps

databricks

Lakehouse Apps is a new way to build native applications for Databricks. Lakehouse Apps will offer the most secure way to build, distribute.

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Data Engineering Weekly #161

Data Engineering Weekly

2) Why High-Quality Data Products Beats Complexity in Building LLM Apps - Ananth Packildurai I will walk through the evolution of model-centric to data-centric AI and how data products and DPLM (Data Product Lifecycle Management) systems are vital for an organization's system. link] Nvidia: What Is Sovereign AI?

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Don’t Get Left Behind in the AI Race: Your Easy Starting Point is Here

Cloudera

Introducing the Enterprise AI Fast Start: Accelerating AI Applications for Enterprises The Enterprise AI Fast Start removes the complexity from getting started with AI and allows customers to have a much faster time to value for their AI use cases. Containerized Compute Sessions: Run your development and testing tasks with ease.

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Taking Charge of Tables: Introducing OpenHouse for Big Data Management

LinkedIn Engineering

Co-Authors: Sumedh Sakdeo , Lei Sun , Sushant Raikar , Stanislav Pak , and Abhishek Nath Introduction At LinkedIn, we build and operate an open source data lakehouse deployment to power Analytics and Machine Learning workloads. Figure 2 shows how OpenHouse fits into broader open source lakehouse deployments. GDPR purge). a catalog).

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Data Pipeline- Definition, Architecture, Examples, and Use Cases

ProjectPro

This blog will give you an in-depth knowledge of what is a data pipeline and also explore other aspects such as data pipeline architecture, data pipeline tools, use cases, and so much more. Step 1- Automating the Lakehouse's data intake. Step 2- Internal Data transformation at LakeHouse.

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20 Best Open Source Big Data Projects to Contribute on GitHub

ProjectPro

This blog will walk through the most popular and fascinating open source big data projects. It was built to serve as the front-end web infrastructure for Apache Spark, allowing it to connect with Spark apps without the need for additional modules or plugins. Refer to the Trino Open Source Repository Here: [link] 15.

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61 Data Observability Use Cases From Real Data Teams

Monte Carlo

In less than three years it has gone from an idea sketched out in a Barr Moses blog post to climbing the Gartner Hype Cycle for Emerging Technology. Data Warehouse (Or Lakehouse) Migration 34. One of the most common ways bad data is introduced is when a query is modified, updated, or changed.

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