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Introduction to Data Engineering- ETL, Star Schema and Airflow

Analytics Vidhya

This article was published as a part of the Data Science Blogathon A data scientist’s ability to extract value from data is closely related to how well-developed a company’s data storage and processing infrastructure is.

ETL 295
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AWS Glue for Handling Metadata

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction AWS Glue helps Data Engineers to prepare data for other data consumers through the Extract, Transform & Load (ETL) Process. It provides organizations with […].

AWS 370
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Essential data engineering tools for 2023: Empowering for management and analysis

Data Science Dojo

Data engineering tools are software applications or frameworks specifically designed to facilitate the process of managing, processing, and transforming large volumes of data. Essential data engineering tools for 2023 Top 10 data engineering tools to watch out for in 2023 1.

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How data engineers tame Big Data?

Dataconomy

Data engineers play a crucial role in managing and processing big data. They are responsible for designing, building, and maintaining the infrastructure and tools needed to manage and process large volumes of data effectively. What is data engineering?

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Remote Data Science Jobs: 5 High-Demand Roles for Career Growth

Data Science Dojo

Key Skills Proficiency in SQL is essential, along with experience in data visualization tools such as Tableau or Power BI. Strong analytical skills and the ability to work with large datasets are critical, as is familiarity with data modeling and ETL processes. This role builds a foundation for specialization.

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Big Data – Lambda or Kappa Architecture?

Data Science Blog

Big Data Analytics stands apart from conventional data processing in its fundamental nature. In the realm of Big Data, there are two prominent architectural concepts that perplex companies embarking on the construction or restructuring of their Big Data platform: Lambda architecture or Kappa architecture.

Big Data 130
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Why using Infrastructure as Code for developing Cloud-based Data Warehouse Systems?

Data Science Blog

In the contemporary age of Big Data, Data Warehouse Systems and Data Science Analytics Infrastructures have become an essential component for organizations to store, analyze, and make data-driven decisions. So why using IaC for Cloud Data Infrastructures? appeared first on Data Science Blog.