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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

Role Level Intermediate Responsibilities Design and develop data pipelines to ingest, process, and transform data. Implemented and managed data storage solutions using Azure services like Azure SQL Database , Azure Data Lake Storage, and Azure Cosmos DB.

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How to Become an Azure Data Engineer? 2023 Roadmap

Knowledge Hut

To provide end users with a variety of ready-made models, Azure Data engineers collaborate with Azure AI services built on top of Azure Cognitive Services APIs. You must be able to create ETL pipelines using tools like Azure Data Factory and write custom code to extract and transform data if you want to succeed as an Azure Data Engineer.

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Why the Data Journey Manifesto?

DataKitchen

We wrote the first version because, after talking with hundreds of people at the 2016 Strata Hadoop World Conference, very few easily understood what we discussed at our booth and conference session. I spent much time de-categorizing DataOps: we are not discussing ETL, Data Lake, or Data Science.

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15+ Must Have Data Engineer Skills in 2023

Knowledge Hut

Technical Data Engineer Skills 1.Python Python Python is one of the most looked upon and popular programming languages, using which data engineers can create integrations, data pipelines, integrations, automation, and data cleansing and analysis. Knowledge of requirements and knowledge of machine learning libraries.

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Forge Your Career Path with Best Data Engineering Certifications

ProjectPro

Azure Data Engineer Associate DP-203 Certification Candidates for this exam must possess a thorough understanding of SQL, Python, and Scala, among other data processing languages. Must be familiar with data architecture, data warehousing, parallel processing concepts, etc.

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Data Pipeline- Definition, Architecture, Examples, and Use Cases

ProjectPro

Generally, data pipelines are created to store data in a data warehouse or data lake or provide information directly to the machine learning model development. Keeping data in data warehouses or data lakes helps companies centralize the data for several data-driven initiatives.