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Why We Open-Sourced Our Data Observability Products

DataKitchen

Introducing DataKitchen’s Open Source Data Observability Software Today, we announce that we have open-sourced two complete, feature-rich products that solve the data observability problem: DataOps Observervability and DataOps TestGen. The Open Source Philosophy: Why Take This Road? The Data Journey.

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Introducing Objectiv: Open-source product analytics infrastructure

KDnuggets

Collect validated user behavior data that’s ready to model on without prepwork. Take models built on one dataset and deploy & run them on another.

Datasets 160
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Open Source Production Grade Data Integration With Meltano

Data Engineering Podcast

Summary The first stage of every data pipeline is extracting the information from source systems. There are a number of platforms for managing data integration, but there is a notable lack of a robust and easy to use open source option. The Meltano project is aiming to provide a solution to that situation.

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Making Email Better With AI At Shortwave

Data Engineering Podcast

When Andrew Lee started work on Shortwave he was focused on making email more productive. In this episode he shares the technical challenges that he and his team have overcome in integrating AI into their product, as well as the benefits and features that it provides to their customers. Want to see Starburst in action?

Data Lake 173
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3 Challenges of Building Complex Dashboards with Open Source Components

Speaker: Ryan MacCarrigan, Founding Principal, LeanStudio

Many product teams use charting components and open source code libraries to get dashboards and reporting functionality quickly. But what happens when you have a growing user base and additional feature requests?

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Establish A Single Source Of Truth For Your Data Consumers With A Semantic Layer

Data Engineering Podcast

Summary Maintaining a single source of truth for your data is the biggest challenge in data engineering. Datafold has recently launched data replication testing, providing ongoing validation for source-to-target replication. Validate consistency between source and target at any scale, and receive alerts about any discrepancies.

Data Lake 162
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Using Trino And Iceberg As The Foundation Of Your Data Lakehouse

Data Engineering Podcast

Multiple open source projects and vendors have been working together to make this vision a reality. It is an open-source, cloud-native orchestrator for the whole development lifecycle, with integrated lineage and observability, a declarative programming model, and best-in-class testability.

Data Lake 262
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New Study: 2018 State of Embedded Analytics Report

Why do some embedded analytics projects succeed while others fail? We surveyed 500+ application teams embedding analytics to find out which analytics features actually move the needle. Read the 6th annual State of Embedded Analytics Report to discover new best practices. Brought to you by Logi Analytics.

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Monetizing Analytics Features: Why Data Visualizations Will Never Be Enough

Think your customers will pay more for data visualizations in your application? Five years ago they may have. But today, dashboards and visualizations have become table stakes. Discover which features will differentiate your application and maximize the ROI of your embedded analytics. Brought to you by Logi Analytics.

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LLMs in Production: Tooling, Process, and Team Structure

Speaker: Dr. Greg Loughnane and Chris Alexiuk

Technology professionals developing generative AI applications are finding that there are big leaps from POCs and MVPs to production-ready applications. However, during development – and even more so once deployed to production – best practices for operating and improving generative AI applications are less understood.