Data Data Pipeline Pipeline-centric 
Snowflake
APRIL 17, 2024
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. This allows your applications to handle large data sets and complex workflows efficiently.
Cloudera
NOVEMBER 21, 2024
As advanced analytics and AI continue to drive enterprise strategy, leaders are tasked with building flexible, resilient data pipelines that accelerate trusted insights. A New Level of Productivity with Remote Access The new Cloudera Data Engineering 1.23 Why Cloudera Data Engineering? Jupyter, PyCharm, and VS Code).
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Data Engineering Podcast
JUNE 30, 2024
Petr shares his journey from being an engineer to founding Synq, emphasizing the importance of treating data systems with the same rigor as engineering systems. He discusses the challenges and solutions in data reliability, including the need for transparency and ownership in data systems. Want to see Starburst in action?
Ascend.io
AUGUST 29, 2023
A star-studded baseball team is analogous to an optimized “end-to-end data pipeline” — both require strategy, precision, and skill to achieve success. Just as every play and position in baseball is key to a win, each component of a data pipeline is integral to effective data management.
Ascend.io
MAY 31, 2023
In the modern world of data engineering, two concepts often find themselves in a semantic tug-of-war: data pipeline and ETL. Fast forward to the present day, and we now have data pipelines. Data Ingestion Data ingestion is the first step of both ETL and data pipelines.
Data Engineering Podcast
APRIL 7, 2019
Summary How much time do you spend maintaining your data pipeline? This was a fascinating conversation with someone who has spent his entire career working on simplifying complex data problems. They have built an easy to use platform that lets you leverage your company’s single sign on for your data platform.
Cloudera
SEPTEMBER 17, 2020
For enterprise organizations, managing and operationalizing increasingly complex data across the business has presented a significant challenge for staying competitive in analytic and data science driven markets. CDP data lifecycle integration and SDX security and governance. Enterprise Data Engineering From the Ground Up.
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