Remove Big Data Tools Remove Data Storage Remove Structured Data
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Hadoop vs Spark: Main Big Data Tools Explained

AltexSoft

Master Nodes control and coordinate two key functions of Hadoop: data storage and parallel processing of data. Worker or Slave Nodes are the majority of nodes used to store data and run computations according to instructions from a master node. A powerful Big Data tool, Apache Hadoop alone is far from being almighty.

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Spark vs Hive - What's the Difference

ProjectPro

Apache Hive and Apache Spark are the two popular Big Data tools available for complex data processing. To effectively utilize the Big Data tools, it is essential to understand the features and capabilities of the tools. Spark SQL, for instance, enables structured data processing with SQL.

Hadoop 45
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30+ Data Engineering Projects for Beginners in 2025

ProjectPro

Project Idea : Build a data engineering pipeline to ingest and transform data, focusing on runs, wickets, and strike rates. Use the ESPNcricinfo Ball-by-Ball Dataset to process match data. Store raw data in AWS S3, preprocess it using AWS Lambda, and query structured data in Amazon Athena.

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Data Lake vs Data Warehouse - Working Together in the Cloud

ProjectPro

This means that a data warehouse is a collection of technologies and components that are used to store data for some strategic use. Data is collected and stored in data warehouses from multiple sources to provide insights into business data. Data from data warehouses is queried using SQL.

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DynamoDB vs. MongoDB- Battle of The Best NoSQL Databases

ProjectPro

DynamoDB's low latency and automatic scaling capabilities make it a good choice for high-traffic applications that require fast and reliable access to data. However, MongoDB can perform well for complex queries and can handle a variety of data types, including unstructured and semi-structured data.

NoSQL 40
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100+ Big Data Interview Questions and Answers 2025

ProjectPro

There are three steps involved in the deployment of a big data model: Data Ingestion: This is the first step in deploying a big data model - Data ingestion, i.e., extracting data from multiple data sources. Data Variety Hadoop stores structured, semi-structured and unstructured data.

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Top 10 Essential Data Engineering Skills

ProjectPro

FAQs on Data Engineering Skills Mastering Data Engineering Skills: An Introduction to What is Data Engineering Data engineering is the process of designing, developing, and managing the infrastructure needed to collect, store, process, and analyze large volumes of data. 2) Does data engineering require coding?