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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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Redefining Data Engineering: GenAI for Data Modernization and Innovation – RandomTrees

RandomTrees

Over the years, the field of data engineering has seen significant changes and paradigm shifts driven by the phenomenal growth of data and by major technological advances such as cloud computing, data lakes, distributed computing, containerization, serverless computing, machine learning, graph database, etc.

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DataOps Architecture: 5 Key Components and How to Get Started

Databand.ai

Data silos: Legacy architectures often result in data being stored and processed in siloed environments, which can limit collaboration and hinder the ability to generate comprehensive insights. This requires implementing robust data integration tools and practices, such as data validation, data cleansing, and metadata management.

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What is ELT (Extract, Load, Transform)? A Beginner’s Guide [SQ]

Databand.ai

Often, the extraction process includes checks and balances to verify the accuracy and completeness of the extracted data. The Load Phase After the data is extracted, it’s loaded into a data storage system in the load phase. The data is loaded as-is, without any transformation.

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Power BI Developer Roles and Responsibilities [2023 Updated]

Knowledge Hut

Data Transformation and ETL: Handle more complex data transformation and ETL (Extract, Transform, Load) processes, including handling data from multiple sources and dealing with complex data structures. Ensure compliance with data protection regulations. Define data architecture standards and best practices.

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Top ETL Use Cases for BI and Analytics:Real-World Examples

ProjectPro

If you're wondering how the ETL process can drive your company to a new era of success, this blog will help you discover what use cases of ETL make it a critical component in many data management and analytic systems. Business Intelligence - ETL is a key component of BI systems for extracting and preparing data for analytics.

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20+ Data Engineering Projects for Beginners with Source Code

ProjectPro

This project is an opportunity for data enthusiasts to engage in the information produced and used by the New York City government. In this project, you will explore the usage of Databricks Spark on Azure with Spark SQL and build this data pipeline. Upload it to Azure Data lake storage manually.