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What is data architecture? A framework to manage data

CIO

Data architecture definition Data architecture describes the structure of an organizations logical and physical data assets, and data management resources, according to The Open Group Architecture Framework (TOGAF). An organizations data architecture is the purview of data architects.

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From legacy to lakehouse: Centralizing insurance data with Delta Lake

CIO

Maintaining legacy systems can consume a substantial share of IT budgets up to 70% according to some analyses diverting resources that could otherwise be invested in innovation and digital transformation. This is where Delta Lakehouse architecture truly shines. This unified view makes it easier to manage and access your data.

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Comprehensive data management for AI: The next-gen data management engine that will drive AI to new heights

CIO

The challenges of integrating data with AI workflows When I speak with our customers, the challenges they talk about involve integrating their data and their enterprise AI workflows. The core of their problem is applying AI technology to the data they already have, whether in the cloud, on their premises, or more likely both.

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Fundamentals of Data Engineering

Xebia

The following is a review of the book Fundamentals of Data Engineering by Joe Reis and Matt Housley, published by O’Reilly in June of 2022, and some takeaway lessons. This book is as good for a project manager or any other non-technical role as it is for a computer science student or a data engineer.

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Scala returning to its origins: A tale of 4 chapters

Xebia

For example, events such as Twitters rebranding to X, and PySparks rise in the data engineering realm over Spark have all contributed to this decline. Martin Odersky has noted that the complexities of the language can discourage new users, emphasizing the need for simpler learning resources and libraries.

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What is Data Engineering: Explaining Data Pipeline, Data Warehouse, and Data Engineer Role

Altexsoft

If we look at the hierarchy of needs in data science implementations, we’ll see that the next step after gathering your data for analysis is data engineering. This discipline is not to be underestimated, as it enables effective data storing and reliable data flow while taking charge of the infrastructure.

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Make the leap to Hybrid with Cloudera Data Engineering

Cloudera

When we introduced Cloudera Data Engineering (CDE) in the Public Cloud in 2020 it was a culmination of many years of working alongside companies as they deployed Apache Spark based ETL workloads at scale. Each unlocking value in the data engineering workflows enterprises can start taking advantage of. Usage Patterns.