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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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How to learn data engineering

Christophe Blefari

Data engineering inherits from years of data practices in US big companies. Hadoop initially led the way with Big Data and distributed computing on-premise to finally land on Modern Data Stack — in the cloud — with a data warehouse at the center. Picking the right format for your data storage.

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Data – the Octane Accelerating Intelligent Connected Vehicles

Cloudera

The vehicle-to-cloud solution driving advanced use cases. Airbiquity, Cloudera, NXP, Teraki, and Wind River teamed to collaborate on The Fusion Project whose objective is to define and provide an integrated solution from vehicle edge to cloud addressing the challenges associated with a fragmented machine learning data management lifecycle.

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What Are the Best Data Modeling Methodologies & Processes for My Data Lake?

phData: Data Engineering

With many data modeling methodologies and processes available, choosing the right approach can be daunting. This blog will guide you through the best data modeling methodologies and processes for your data lake, helping you make informed decisions and optimize your data management practices. What is a Data Lake?

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

Knowledge Hut

This demonstrates the increasing need for Microsoft Certified Data Engineers. In this blog, I will explore Azure data engineer jobs and the top 10 job roles in this field where you can begin your career. As a result, organizations are looking to capitalize on cloud-based data solutions. Let’s get started.

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15+ Best Data Engineering Tools to Explore in 2023

Knowledge Hut

Here, we'll take a look at the top data engineer tools in 2023 that are essential for data professionals to succeed in their roles. These tools include both open-source and commercial options, as well as offerings from major cloud providers like AWS, Azure, and Google Cloud. What are Data Engineering Tools?

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Accenture’s Smart Data Transition Toolkit Now Available for Cloudera Data Platform

Cloudera

While this “data tsunami” may pose a new set of challenges, it also opens up opportunities for a wide variety of high value business intelligence (BI) and other analytics use cases that most companies are eager to deploy. . Traditional data warehouse vendors may have maturity in data storage, modeling, and high-performance analysis.