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15+ Must Have Data Engineer Skills in 2023

Knowledge Hut

With a plethora of new technology tools on the market, data engineers should update their skill set with continuous learning and data engineer certification programs. What do Data Engineers Do? Big resources still manage file data hierarchically using Hadoop's open-source ecosystem.

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5 Reasons Why ETL Professionals Should Learn Hadoop

ProjectPro

While the initial era of ETL ignited enough sparks and got everyone to sit up, take notice and applaud its capabilities, its usability in the era of Big Data is increasingly coming under the scanner as the CIOs start taking note of its limitations. Thus, why not take the lead and prepare yourself to tackle any situation in the future?

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Solutions Architect Job Roles in 2024 [Career Options]

Knowledge Hut

Responsibilities: Define data architecture strategies and roadmaps to support business objectives and data initiatives. Design data models, schemas, and storage solutions for structured and unstructured data. Evaluate and recommend data management tools, database technologies, and analytics platforms.

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Hadoop Developer Job Responsibilities Explained

ProjectPro

The better a hadoop developer knows the data, the better they know what kind of results are possible with that amount of data. Concisely, a hadoop developer plays with the data, transforms it, decodes it and ensure that it is not destroyed. Understanding the usage of various data visualizations tools like Tableau, Qlikview, etc.

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

ProjectPro

It can also consist of simple or advanced processes like ETL (Extract, Transform and Load) or handle training datasets in machine learning applications. In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline. ETL is the acronym for Extract, Transform, and Load.

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Sqoop vs. Flume Battle of the Hadoop ETL tools

ProjectPro

Sqoop in Hadoop is mostly used to extract structured data from databases like Teradata, Oracle, etc., and Flume in Hadoop is used to sources data which is stored in various sources like and deals mostly with unstructured data. The complexity of the big data system increases with each data source.

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Difference between Pig and Hive-The Two Key Components of Hadoop Ecosystem

ProjectPro

Just before we jump on to a detailed discussion on the key components of the Hadoop Ecosystem and try to understand the differences between them let us have an understanding on what is Hadoop and what is Big Data. What is Big Data and Hadoop? 11) Pig supports Avro whereas Hive does not. 11) Pig supports Avro whereas Hive does not.

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