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What are the prerequisites for learning Hadoop & big data?

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Spark is a good choice if you're working with machine learning algorithms or large-scale data. If you're working with giant data sets and want to store and process them, Hadoop is a better option. Hadoop is more cost-effective and easily scalable than Spark.
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Spark is a good choice if you're working with machine learning algorithms or large-scale data. If you're working with giant data sets and want to store and process them, Hadoop is a better option. Hadoop is more cost-effective and easily scalable than Spark.
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Here are the key prerequisites for learning Hadoop and big data: 1. **Basic Programming Knowledge**: - Familiarity with programming languages like Java (Hadoop is primarily built on Java) or Python. 2. **Understanding of Databases**: - Basic knowledge of SQL and relational databases to...
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Here are the key prerequisites for learning Hadoop and big data: 1. **Basic Programming Knowledge**: - Familiarity with programming languages like Java (Hadoop is primarily built on Java) or Python. 2. **Understanding of Databases**: - Basic knowledge of SQL and relational databases to grasp data storage concepts. 3. **Linux Command Line Skills**: - Comfort with Linux commands, as Hadoop runs on Linux systems. 4. **Concepts of Distributed Computing**: - Understanding the fundamentals of distributed systems and their architectures. 5. **Data Processing Concepts**: - Familiarity with data processing methodologies and concepts, including ETL (Extract, Transform, Load). 6. **Mathematics and Statistics**: - A foundational understanding of statistics and data analysis principles can be beneficial. 7. **Familiarity with Big Data Concepts**: - Basic knowledge of what big data is and the challenges associated with it. ### Summary: Having a good grasp of programming, databases, Linux, and data processing concepts will significantly ease your learning journey in Hadoop and big data. read less
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