🔥 Top 20 Hadoop Interview Questions 2023 | Big Data Hadoop Interview Questions | Simplilearn

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In this video " Top 20 Hadoop Interview Questions" we will cover the 20 most asked question in the hadoop and big data interviews.
Big Data in layman’s terms is a vast volume of high velocity data , think of hundreds of gigabytes of data flowing through in minutes. Obviously this can’t be stored and processed using traditional data processing systems. Now this is where Hadoop comes in. Hadoop is an open-source framework designed to handle big data. It provides a distributed file system (Hadoop Distributed File System - HDFS) and a distributed processing framework (MapReduce) that allows for parallel and scalable processing of large datasets across clusters of nodes. Hadoop's architecture enables fault tolerance and high availability, making it suitable for processing big data. Organizations and enterprises globally are on the lookout for skilled professionals who are able to handle such vast volumes of data, help structure and streamline the processing of this data. The salary of a Hadoop developer can vary based on factors like experience, location, company size, and industry but on average Hadoop developers earn anywhere between $80,000 and $150,000 per year which can go as high as 250,000$ for some experienced roles. It is therefore one of the best times for you to get yourself certified and skilled in the big data domain. With companies like Google, Adobe, Intuit,Oracle, Accenture, VISA, and many hiring hadoop developers you must get yourself enrolled in one of our amazing certification training programs to land yourself your dream job. Let me tell you about this global certification program.

00:00 Introduction to Big Data and Hadoop
Hadoop Developer Salary
Companies Hiring Hadoop Developer
Top 20 Hadoop Interview Questions

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About Post Graduate Program In Data Engineering
Fast-track your career as a Data Engineering professional with our Data Engineering course. This course covers Big Data and Data Engineering concepts, the Hadoop ecosystem, Apache Python basics, AWS EMR, Quicksight, Sagemaker, the AWS cloud platform, and Azure services.

✅ Skills Covered
- Real Time Data Processing
- Data Pipelining
- Big Data Analytics
- Data Visualization
- Provisioning data storage services
- Apache Hadoop
- Ingesting Streaming and Batch Data
- Transforming Data
- Implementing Security Requirements
- Data Protection
- Encryption Techniques
- Data Governance and Compliance Controls

✅ Tools Covered
- Amazon EMR
- Amazon RedShift
- MongoDB
- Python
- Apache spark
- Data Bricks
- SQL
- and more...

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