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DataOps Architecture: 5 Key Components and How to Get Started

Databand.ai

DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. It aims to streamline data ingestion, processing, and analytics by automating and integrating various data workflows. As a result, they can be slow, inefficient, and prone to errors.

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Upgrade your Modern Data Stack

Christophe Blefari

Historically, data pipelines were designed with an ETL approach, storage was expensive and we had to transform the data before using it. With the cloud, we got the—false—impression that resources were infinite and cheap, so we switched to ETL by pushing everything into a central data storage.

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Azure Data Engineer Job Description [Roles and Responsibilities]

Knowledge Hut

As an Azure Data Engineer, you will be expected to design, implement, and manage data solutions on the Microsoft Azure cloud platform. You will be in charge of creating and maintaining data pipelines, data storage solutions, data processing, and data integration to enable data-driven decision-making inside a company.

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A Complete Guide to Azure Data Engineer Certification (DP-203)

Knowledge Hut

This certification, often referred to as the Azure Data Engineer Associate certification, validates the competency of individuals in implementing Azure data solutions. It’s a testament to their ability to create scalable, efficient and secure data pipelines. What is the Azure Data Engineer Certification?

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4 Ways to Tackle Data Pipeline Optimization

Monte Carlo

Integrate data deduplication tools into your pipeline : These tools scan your datasets, identify and eliminate duplicate data, and help you save on storage space and reduce processing load. Regularly schedule deduplication processes to keep your data storage lean and efficient.

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ETL for Snowflake: Why You Need It and How to Get Started

Ascend.io

While Snowflake offers robust features that are particularly valuable for certain aspects of data handling, there are several reasons why a separate ETL tool might still be necessary or advantageous: Chaining Together Complex Data Transformations: Snowflake is highly efficient at handling data storage and basic to moderately complex transformations.

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

Knowledge Hut

Job Role 1: Azure Data Engineer Azure Data Engineers develop, deploy, and manage data solutions with Microsoft Azure data services. They use many data storage, computation, and analytics technologies to develop scalable and robust data pipelines.