Big Data Analysis Notes

Welcome to the Big Data Analysis repository! This collection of notes has been curated to provide a comprehensive guide to essential concepts and tools for big data analysis. Whether you are a beginner or an experienced data analyst, these resources aim to assist you in mastering the intricacies of big data analytics.

Table of Contents

Module 1. Big Data Introduction

• An introductory guide to the fundamentals of big data, outlining key concepts and challenges in the field.

Module 2. Hadoop

• Explore the Hadoop framework, an open-source tool for distributed storage and processing of large data sets.

Module 3. HDFS

• Delve into Hadoop Distributed File System (HDFS), understanding its architecture and functionalities.

Module 4. MapReduce

• Learn about the MapReduce programming model, a fundamental paradigm for processing and generating large data sets.

Module 5. NoSQL

• Discover NoSQL databases and their significance in managing unstructured or semi-structured data.

Module 6. Data Stream

• Gain insights into data stream processing, a critical aspect in handling continuous and real-time data flows.

Module 7. Data Stream Algorithms

• Explore algorithms tailored for data stream analytics, addressing challenges posed by dynamic and evolving data.

Module 8. Question Bank - Solved

• Access a collection of solved questions to reinforce your understanding and test your knowledge.

Module 9. Lab Exercises

• Engage in practical learning with lab exercises designed to apply theoretical knowledge in real-world scenarios.

Module 10. Practice Questions

• Sharpen your skills with a set of practice questions covering various aspects of big data analysis.

Feel free to explore and utilize these resources at your own pace. If you have any questions or suggestions, don't hesitate to reach out. Happy learning! 📚✨