DataOps for Engineers: Automating the Data Lifecycle on the Cloud
In the era of big data, organizations need agile, scalable, and efficient ways to manage their data pipelines. DataOps, a methodology that combines data engineering services, DevOps, and agile practices, is revolutionizing how enterprises handle the data lifecycle.
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POSTED BY
Bhawana Khater
Building Data Mesh Architecture: How It Impacts Data Engineering
As data ecosystems grow in complexity and volume, traditional centralized data architectures are hitting scalability limits. To address this challenge, organizations are adopting Data Mesh Architecture—a paradigm that decentralizes data ownership and promotes cross-functional collaboration through domain-driven design.
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POSTED BY
Nilabh Bajpai
Serverless Data Engineering: When & Why to Go Serverless
What if you could build, scale, and optimize your data pipelines without ever managing a single server? As businesses navigate the complexities of modern data infrastructures, data engineering has become central to building scalable and efficient systems.
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