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How to Become an Azure Data Engineer? 2023 Roadmap

Knowledge Hut

The demand for data-related professions, including data engineering, has indeed been on the rise due to the increasing importance of data-driven decision-making in various industries. Becoming an Azure Data Engineer in this data-centric landscape is a promising career choice.

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Azure Data Engineer Certification Path (DP-203): 2023 Roadmap

Knowledge Hut

The demand for knowledgeable data engineers that can plan, create, and maintain sophisticated data infrastructure is growing as the amount of data created by enterprises continues to increase dramatically. The success of our career as an Azure Data Engineer depends on our ability to master several different talents.

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15+ Must Have Data Engineer Skills in 2023

Knowledge Hut

The contemporary world experiences a huge growth in cloud implementations, consequently leading to a rise in demand for data engineers and IT professionals who are well-equipped with a wide range of application and process expertise. Data Engineer certification will aid in scaling up you knowledge and learning of data engineering.

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Azure Data Engineer Prerequisites [Requirements & Eligibility]

Knowledge Hut

Within the Microsoft Azure ecosystem, the role of an Azure data engineer stands out as one of the most sought-after positions. What Does an Azure Data Engineer Do? Azure Data engineers collaborate with Azure AI services built on top of Azure Cognitive Services APIs to offer end customers a variety of pre-built models.

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What is a Data Pipeline?

Grouparoo

Origin The origin of a data pipeline refers to the point of entry of data into the pipeline. This includes the different possible sources of data such as application APIs, social media, relational databases, IoT device sensors, and data lakes. Destinations can vary depending on the use case of the pipeline.

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What is Data Extraction? Examples, Tools & Techniques

Knowledge Hut

This data can be structured, semi-structured, or entirely unstructured, making it a versatile tool for collecting information from various origins. The extracted data is then duplicated or transferred to a designated destination, often a data warehouse optimized for Online Analytical Processing (OLAP).

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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.