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Snowflake’s New Python API Empowers Data Engineers to Build Modern Data Pipelines with Ease

Snowflake

In today’s data-driven world, developer productivity is essential for organizations to build effective and reliable products, accelerate time to value, and fuel ongoing innovation. Recognizing this shift, Snowflake is taking a Python-first approach to bridge the gap and help users leverage the power of both worlds.

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Release Management For Data Platform Services And Logic

Data Engineering Podcast

Summary Building a data platform is a substrantial engineering endeavor. Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management This episode is supported by Code Comments, an original podcast from Red Hat. Data lakes are notoriously complex.

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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. Different roles and tasks in the business need their own ways to access and analyze the data in the organization. Dagster offers a new approach to building and running data platforms and data pipelines.

Data Lake 162
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Zenlytic Is Building You A Better Coworker With AI Agents

Data Engineering Podcast

Summary The purpose of business intelligence systems is to allow anyone in the business to access and decode data to help them make informed decisions. Unfortunately this often turns into an exercise in frustration for everyone involved due to complex workflows and hard-to-understand dashboards. Data lakes are notoriously complex.

Building 278
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Top Data Python Packages to Know in 2023

KDnuggets

These Python packages would improve your data workflow.

Python 114
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Data Migration Strategies For Large Scale Systems

Data Engineering Podcast

When that system is responsible for the data layer the process becomes more challenging. Sriram Panyam has been involved in several projects that required migration of large volumes of data in high traffic environments. Can you start by sharing some of your experiences with data migration projects?

Systems 130
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Managing Uber’s Data Workflows at Scale

Uber Engineering

At Uber’s scale, thousands of microservices serve millions of rides and deliveries a day, generating more than a hundred petabytes of raw data. Internally, engineering and data teams across the company leverage this data to improve the Uber experience.