Hadoop Big Data Analytics & Projects Mastery

EDUCBA via Coursera Specialization

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Provider

Coursera Specialization
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Duration & workload

4 weeks, 10 hours a week

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Overview

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This specialization provides an advanced, project-driven learning path into Big Data analytics using the Hadoop ecosystem. Learners gain hands-on experience with Hive, Pig, and MapReduce through industry-inspired projects across domains like social media, telecom, healthcare, and e-commerce. Each course builds from data ingestion and transformation to optimization and insight generation, empowering learners to design scalable workflows and analyze massive datasets efficiently. By the end, participants will be equipped to apply Hadoop tools to solve authentic enterprise-level data challenges and showcase their capabilities through portfolio-ready projects.

Syllabus

Course 1: Hadoop Projects: Analyze Big Data with Hive & Pig
Course 2: Big Data Analytics with Hive, Pig & MapReduce
Course 3: Big Data with Hadoop: Apply MapReduce, Pig & Hive
Course 4: Hadoop Projects: Apply MapReduce, Pig & Hive
Course 5: Hadoop Projects: Analyze & Optimize Big Data

Courses

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9 hours 20 minutes
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By the end of this course, learners will be able to design Hive databases, manage complex tables, process XML data with Pig, execute MapReduce jobs, and analyze large-scale social media datasets to extract meaningful insights. The course begins with foundational concepts of Hive, including databases, partitions, and bucketing, then advances into table optimization and constraints for schema design. Learners will gain practical experience in ingesting data with Sqoop, processing it using MapReduce, and applying location- and author-based analytics to real-world datasets. Finally, the course explores Pig scripting for XML processing and Hive complex data types for advanced bookmarking dataset analysis. This course is unique because it combines two hands-on case studies: one from the telecom industry and another from social media analytics, offering a blend of foundational Hive knowledge and advanced Hadoop ecosystem tools. Designed for professionals, students, and data enthusiasts, the course emphasizes practical application over theory, ensuring learners can confidently apply big data technologies to solve real business problems.
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8 hours 7 minutes
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By the end of this course, learners will be able to analyze real-world sensor datasets, preprocess JSON files, apply Hadoop MapReduce operations, implement data flows with Apache Pig, and execute SQL-like queries using Apache Hive. They will also interpret insights on demographics, income, and social indicators to support evidence-based decision-making. This hands-on project-based course equips learners with the essential Big Data skills required to process and analyze large-scale sensor data. Unlike theoretical introductions, it focuses on live project scenarios where learners design workflows, troubleshoot errors, and generate meaningful outcomes. Through case studies such as gender ratios, income tax predictions, and child labor analysis, learners understand how analytics can directly inform strategic and policy decisions. What makes this course unique is its integrated approach—learners gain practical exposure to MapReduce, Pig, and Hive in a single structured project. This ensures that participants not only master the technical tools but also develop the ability to transform raw data into actionable insights that drive real-world impact.
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9 hours 54 minutes
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By the end of this course, learners will be able to analyze, transform, and optimize large-scale datasets using Hadoop’s distributed ecosystem. They will gain hands-on experience with MapReduce, Pig, and Hive across multiple real-world projects, including log processing, sales analytics, tourism survey insights, faculty data management, e-commerce performance, and salary analysis. This course emphasizes practical implementation over theory, guiding learners step-by-step through data cleaning, schema design, query optimization, and report generation in a cloud-scale environment. Through integrated projects, learners will learn how to build, execute, and automate data workflows while ensuring reliability and scalability in HDFS. Unlike traditional Hadoop courses, this program delivers a comprehensive, project-driven learning path, helping participants bridge the gap between conceptual understanding and professional application. Ideal for data engineers, analysts, and IT professionals, this course empowers learners to confidently apply Hadoop tools in solving complex business and analytical challenges across industries.
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10 hours 51 minutes
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By the end of this course, learners will be able to design, implement, and analyze real-world Big Data projects using Hadoop’s core components — HDFS, Hive, Pig, and MapReduce. They will apply data processing techniques to customer complaints, health surveys, traffic violations, and loan datasets to extract valuable business insights. This hands-on, project-based course guides learners through every stage of Big Data analysis — from importing and transforming data to executing distributed computations and exporting results to relational databases. Learners will master essential Hadoop workflows such as writing MapReduce programs, developing Hive queries, integrating Pig scripts, and using Sqoop for seamless SQL data transfer. What makes this course unique is its real-world project orientation that combines four complete Hadoop case studies into one comprehensive learning experience. Each module provides step-by-step implementation practice to build confidence and technical proficiency. Upon completion, learners will be equipped to manage large datasets, optimize performance, and apply Hadoop-based solutions in enterprise environments.
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6 hours 4 minutes
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By the end of this course, learners will be able to prepare raw YouTube datasets, apply MapReduce for large-scale processing, implement Pig Latin scripts for metadata analysis, and execute HiveQL queries to generate structured insights. The course blends practical scenarios with hands-on tools from the Hadoop ecosystem, empowering learners to analyze real-world data efficiently. This project-based course offers a unique opportunity to practice Big Data analytics using actual YouTube data. Unlike theoretical courses, it emphasizes end-to-end implementation — from data preparation and transformation to query execution and output interpretation. Learners will gain practical skills in Hadoop, MapReduce, Pig, and Hive, making them proficient in handling complex datasets and extracting valuable insights. By completing this course, learners will not only master essential Hadoop tools but also build a portfolio-ready project that demonstrates Big Data analysis skills applicable to industry scenarios such as video analytics, recommendation systems, and large-scale reporting. This makes the course ideal for students, professionals, and data enthusiasts aiming to strengthen their expertise in Big Data.