What are the prerequisites for learning Hadoop & big data?

To effectively learn Hadoop and big data technologies, it's beneficial to have a solid understanding of certain concepts and skills. Here are some prerequisites that can help you get started:

1. Fundamental Programming Skills:

   • Proficiency in at least one programming language is essential. Java is commonly used in the Hadoop ecosystem, so having a good grasp of Java is highly recommended. Additionally, knowledge of Python is valuable for working with various big data tools and libraries.

2. Understanding of Core Computer Science Concepts:

   • Familiarity with basic computer science concepts like data structures, algorithms, and computer architecture is important for understanding the underlying principles of distributed computing.

3. Database and SQL Knowledge:

   • A basic understanding of databases and SQL (Structured Query Language) is beneficial. Many big data technologies, including Hadoop, involve working with large datasets stored in distributed file systems or databases.

4. Linux Command Line Skills:

   • A significant portion of big data tools are designed to run on Linux-based systems. Familiarity with the Linux command line is essential for navigating file systems, managing permissions, and executing commands.

5. Understanding of Distributed Systems:

   • Big data processing often involves distributed computing. A foundational knowledge of distributed systems, including concepts like parallel processing, fault tolerance, and scalability, is important.

6. Basics of Networking:

   • Understanding basic networking concepts, such as IP addresses, ports, and protocols, is beneficial when working with distributed systems.

7. Database and Data Modeling Concepts:

   • Knowing the basics of data modeling and database design is useful. This includes understanding concepts like normalization, denormalization, and relational database principles.

8. Data Handling and Analysis Skills:

   • While not mandatory, having some experience with data analysis and manipulation can be helpful. This might include using tools like Excel, R, or Python for data processing and analysis.

9. Educational Background:

   • While not a strict requirement, a background in computer science, information technology, or a related field can provide a solid foundation for learning big data technologies.

10. Curiosity and Problem-Solving Skills:

    • The ability to think analytically, solve problems, and a curiosity about large-scale data processing are crucial for success in the field of big data.

Once you have a good foundation in these prerequisites, you can start delving into specific big data technologies like Hadoop, Apache Spark, Apache Kafka, and others. Consider taking online courses, reading books and documentation, and working on hands-on projects to gain practical experience. Many online platforms, such as Coursera, edX, and Udacity, offer courses on big data technologies that can help you build your skills.