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Data Lake Explained: A Comprehensive Guide to Its Architecture and Use Cases

AltexSoft

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. What is a data lake?

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Top 10 Azure Data Engineer Job Opportunities in 2024 [Career Options]

Knowledge Hut

They use many data storage, computation, and analytics technologies to develop scalable and robust data pipelines. Role Level Intermediate Responsibilities Design and develop data pipelines to ingest, process, and transform data. Develop data models, data governance policies, and data integration strategies.

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Data Engineering Weekly #161

Data Engineering Weekly

The migration enhanced data quality, lineage visibility, performance improvements, cost reductions, and better reliability and scalability, setting a robust foundation for future expansions and onboarding. This approach helps maintain accuracy, relevance, and compliance in generative AI applications.

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DataOps Architecture: 5 Key Components and How to Get Started

Databand.ai

A DataOps architecture is the structural foundation that supports the implementation of DataOps principles within an organization. It encompasses the systems, tools, and processes that enable businesses to manage their data more efficiently and effectively. As a result, they can be slow, inefficient, and prone to errors.

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[O’Reilly Book] Chapter 1: Why Data Quality Deserves Attention Now

Monte Carlo

Data pipelines can handle both batch and streaming data, and at a high-level, the methods for measuring data quality for either type of asset are much the same. In many ways, the cloud makes data easier to manage, more accessible to a wider variety of users, and far faster to process.

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The Evolution of Table Formats

Monte Carlo

As organizations seek greater value from their data, data architectures are evolving to meet the demand — and table formats are no exception. Apache ORC (Optimized Row Columnar) : In 2013, ORC was developed for the Hadoop ecosystem to improve the efficiency of data storage and retrieval.

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Forge Your Career Path with Best Data Engineering Certifications

ProjectPro

GCP Data Engineer Certification The Google Cloud Certified Professional Data Engineer certification is ideal for data professionals whose jobs generally involve data governance, data handling, data processing, and performing a lot of feature engineering on data to prepare it for modeling.