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Improve Data Quality Through Engineering Rigor And Business Engagement With Synq

Data Engineering Podcast

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex. What does an on-call rotation for a data engineer/data platform engineer look like as compared with an application-focused team?

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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!!!

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Data Engineering Weekly #186

Data Engineering Weekly

Take Astro (the fully managed Airflow solution) for a test drive today and unlock a suite of features designed to simplify, optimize, and scale your data pipelines. Try For Free → Conference Alert: Data Engineering for AI/ML This is a virtual conference at the intersection of Data and AI.

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Creating Value With a Data-Centric Culture: Essential Capabilities to Treat Data as a Product

Ascend.io

Treating data as a product is more than a concept; it’s a paradigm shift that can significantly elevate the value that business intelligence and data-centric decision-making have on the business. Data pipelines Data integrity Data lineage Data stewardship Data catalog Data product costing Let’s review each one in detail.

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Building a Future in Banking and Capital Markets

The Modern Data Company

This means moving beyond product-centric thinking to a data-driven customer experience model that’s consistent across all channels. Next, the wealth management industry is also shifting away from a product focus to a client-centric model. DataOS is the world’s first operating system.

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Ripple's Centralized Data Platform

Ripple Engineering

  A lack of a centralized system makes building a single source of high-quality data difficult. The key aspect of any business-centric team in delivering products and features is to make critical decisions on ensuring low latency, high throughput, cost-effective storage, and highly efficient infrastructure.

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Data Engineering Weekly #125

Data Engineering Weekly

link] Tweet Search System (EarlyBird) Design [link] Google AI: Data-centric ML benchmarking - Announcing DataPerf’s 2023 challenges Data is the new code: it is the training data that determines the maximum possible quality of an ML solution. As the author points out, it is simply not a scalable approach.