Remove Data Pipeline Remove ETL Tools Remove Hadoop Remove Metadata
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Sqoop vs. Flume Battle of the Hadoop ETL tools

ProjectPro

Apache Hadoop is synonymous with big data for its cost-effectiveness and its attribute of scalability for processing petabytes of data. Data analysis using hadoop is just half the battle won. Getting data into the Hadoop cluster plays a critical role in any big data deployment.

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Mastering the Art of ETL on AWS for Data Management

ProjectPro

The process of data extraction from source systems, processing it for data transformation, and then putting it into a target data system is known as ETL, or Extract, Transform, and Load. ETL has typically been carried out utilizing data warehouses and on-premise ETL tools.

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15+ Must Have Data Engineer Skills in 2023

Knowledge Hut

Let us take a look at the top technical skills that are required by a data engineer first: A. Technical Data Engineer Skills 1.Python Python is ubiquitous, which you can use in the backends, streamline data processing, learn how to build effective data architectures, and maintain large data systems.

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Highest Paying Data Science Jobs in the World

Knowledge Hut

They deploy and maintain database architectures, research new data acquisition opportunities, and maintain development standards. Average Annual Salary of Data Architect On average, a data architect makes $165,583 annually. Average Annual Salary of Data Modeler A data modeler can earn $126,811 annually.

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The Good and the Bad of Apache Kafka Streaming Platform

AltexSoft

The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. cloud data warehouses — for example, Snowflake , Google BigQuery, and Amazon Redshift. Cloudera , focusing on Big Data analytics. The tool takes care of storing metadata about partitions and brokers.

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Data Scientist vs Data Engineer: Differences and Why You Need Both

AltexSoft

They’re integral specialists in data science projects and cooperate with data scientists by backing up their algorithms with solid data pipelines. Juxtaposing data scientist vs engineer tasks. One data scientist usually needs two or three data engineers. Managing data and metadata.

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What is ETL Pipeline? Process, Considerations, and Examples

ProjectPro

This guide provides definitions, a step-by-step tutorial, and a few best practices to help you understand ETL pipelines and how they differ from data pipelines. The crux of all data-driven solutions or business decision-making lies in how well the respective businesses collect, transform, and store data.

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