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The Challenge of Data Quality and Availability—And Why It’s Holding Back AI and Analytics

Striim

Without high-quality, available data, companies risk misinformed decisions, compliance violations, and missed opportunities. Why AI and Analytics Require Real-Time, High-Quality Data To extract meaningful value from AI and analytics, organizations need data that is continuously updated, accurate, and accessible.

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Being Data Driven At Stripe With Trino And Iceberg

Data Engineering Podcast

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex. Can you describe what role Trino and Iceberg play in Stripe's data architecture? Can you describe what role Trino and Iceberg play in Stripe's data architecture?

Data Lake 147
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What is an AI Data Engineer? 4 Important Skills, Responsibilities, & Tools

Monte Carlo

AI data engineers are data engineers that are responsible for developing and managing data pipelines that support AI and GenAI data products. Essential Skills for AI Data Engineers Expertise in Data Pipelines and ETL Processes A foundational skill for data engineers?

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How HomeToGo Is Building a Robust Clickstream Data Architecture with Snowflake, Snowplow and dbt

Snowflake

Over the course of this journey, HomeToGo’s data needs have evolved considerably. After we had a successful trial period that checked all the boxes, we started our migration in autumn 2021 — together with moving all our data transformation management into the OSS version of dbt.

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Centralize Your Data Processes With a DataOps Process Hub

DataKitchen

Data organizations often have a mix of centralized and decentralized activity. DataOps concerns itself with the complex flow of data across teams, data centers and organizational boundaries. It expands beyond tools and data architecture and views the data organization from the perspective of its processes and workflows.

Process 98
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Visionary Data Quality Paves the Way to Data Integrity

Precisely

Read Quality data you can depend on – today, tomorrow, and beyond For many years Precisely customers have ensured the accuracy of data across their organizations by leveraging our leading data solutions including Trillium Quality, Spectrum Quality, and Data360 DQ+. What does all this mean for your business?

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Data Engineering Weekly #161

Data Engineering Weekly

Here is the agenda, 1) Data Application Lifecycle Management - Harish Kumar( Paypal) Hear from the team in PayPal on how they build the data product lifecycle management (DPLM) systems. 3) DataOPS at AstraZeneca The AstraZeneca team talks about data ops best practices internally established and what worked and what didn’t work!!!