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Data Collection for Machine Learning: Steps, Methods, and Best Practices

AltexSoft

Commonly, the entire flow is fully automated and consists of three main steps — data extraction, transformation, and loading ( ETL or ELT , for short, depending on the order of the operations.) Dive deeper into the subject by reading our article Data Integration: Approaches, Techniques, Tools, and Best Practices for Implementation.

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A Beginners Guide to Spark Streaming Architecture with Example

ProjectPro

Managing, processing, and streamlining large datasets in real-time is a key functionality of big data analytics in an enterprise to enhance decision-making. Data analytics also helps organizations understand their customers better, narrow down their target audiences, and improve marketing campaigns.

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Hadoop MapReduce vs. Apache Spark Who Wins the Battle?

ProjectPro

This blog helps you understand the critical differences between two popular big data frameworks. Hadoop and Spark are popular apache projects in the big data ecosystem. Apache Spark is an improvement on the original Hadoop MapReduce component of the Hadoop big data ecosystem.

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Hadoop Ecosystem Components and Its Architecture

ProjectPro

HDFS in Hadoop architecture provides high throughput access to application data and Hadoop MapReduce provides YARN based parallel processing of large data sets. Table of Contents Big Data Hadoop Training Videos- What is Hadoop and its popular vendors?

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