When will I have access to the lectures and assignments?

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

What will I get if I subscribe to this Specialization?

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Hadoop Projects: Analyze & Optimize Big Data

kurs ist nicht verfügbar in Deutsch (Deutschland)

Wir übersetzen es in weitere Sprachen. Sehen Sie sich die Sprachen an, die wir anbieten.

Hadoop Projects: Analyze & Optimize Big Data

Dieser Kurs ist Teil von Spezialisierung „Hadoop Big Data Analytics & Projects Mastery“

Dozent: EDUCBA

Bei enthalten

Mehr erfahren

4 Module

Verschaffen Sie sich einen Einblick in ein Thema und lernen Sie die Grundlagen.

1 Woche zu vervollständigen

unter 10 Stunden pro Woche

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

4 Module

Verschaffen Sie sich einen Einblick in ein Thema und lernen Sie die Grundlagen.

1 Woche zu vervollständigen

unter 10 Stunden pro Woche

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

Was Sie lernen werden

Process and optimize large datasets using Hadoop tools.
Apply MapReduce, Pig, and Hive in real-world data projects.
Build scalable data workflows for analytics and reporting.

Kompetenzen, die Sie erwerben

Kategorie: Database Design
Kategorie: Data Preprocessing
Kategorie: Data Pipelines
Kategorie: Scalability
Kategorie: Analytics
Kategorie: Ad Hoc Reporting
Kategorie: Data Cleansing
Kategorie: Distributed Computing
Kategorie: Big Data
Kategorie: Data Processing
Kategorie: Data Management
Kategorie: Data Transformation
Kategorie: Data Analysis

Werkzeuge, die Sie lernen werden

Kategorie: Apache Hadoop
Kategorie: Query Languages
Kategorie: Apache Hive

Wichtige Details

Zertifikat zur Vorlage

Zu Ihrem LinkedIn-Profil hinzufügen

Bewertungen

16 Aufgaben

Unterrichtet in Englisch

91%

of learners achieved a positive career outcome

Erfahren Sie, wie Mitarbeiter führender Unternehmen gefragte Kompetenzen erwerben.

Weitere Informationen zu Coursera für Unternehmen

Logos von Petrobras, TATA, Danone, Capgemini, P&G und L'Oreal

Erweitern Sie Ihre Fachkenntnisse

Dieser Kurs ist Teil der Spezialisierung Spezialisierung „Hadoop Big Data Analytics & Projects Mastery“

Wenn Sie sich für diesen Kurs anmelden, werden Sie auch für diese Spezialisierung angemeldet.

Lernen Sie neue Konzepte von Branchenexperten
Gewinnen Sie ein Grundverständnis bestimmter Themen oder Tools
Erwerben Sie berufsrelevante Kompetenzen durch praktische Projekte
Erwerben Sie ein Berufszertifikat zur Vorlage

In diesem Kurs gibt es 4 Module

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.

Moduldetails

This module introduces learners to the core principles of Hadoop-based data processing through log and sales data projects. Learners will explore how to clean, process, and analyze streaming log files using MapReduce, Pig, and Hive. The module builds essential technical foundations in distributed file handling and practical data management workflows, setting the stage for advanced Hadoop applications.

Das ist alles enthalten

13 Videos4 Aufgaben

13 VideosInsgesamt 105 Minuten

Introduction to Log Processing8 Minuten
Summarizing Log Files6 Minuten
MapReducing Programme9 Minuten
Execute MapReduce Program9 Minuten
Big Data Technology10 Minuten
Executing Big Data Tool10 Minuten
Writing Map Reduce Program7 Minuten
Array List Searching7 Minuten
Processing Files In Map Reduce6 Minuten
Conclusion7 Minuten
Introduction to Sales Data Analysis Using Hadoop- HDFS10 Minuten
Working with Problem Statement 18 Minuten
Working with Problem Statement 28 Minuten

4 AufgabenInsgesamt 60 Minuten

Building the Foundation – Log & Sales Data Projects30 Minuten
Understanding Log Data Processing in Hadoop10 Minuten
Exploring Big Data Tools and File Operations10 Minuten
Beginning Sales Data Analysis Using Hadoop10 Minuten

This module advances learners’ analytical and problem-solving skills through real-world sales and tourism survey projects. By leveraging Hadoop’s distributed ecosystem, learners will gain hands-on experience using MapReduce, Hive, and Pig to aggregate, join, and filter multi-source datasets for business intelligence and demographic insights.

Das ist alles enthalten

10 Videos4 Aufgaben

10 VideosInsgesamt 77 Minuten

Working with Problem Statement 39 Minuten
Working with Problem Statement 47 Minuten
Working with Problem Statement 56 Minuten
Introduction to Tourism Survey Analysis Using HDFS10 Minuten
Average of Money Spend By Tourist in our Country7 Minuten
Join Country and Nationality8 Minuten
Total no. of Tourist Less than 187 Minuten
Change the Country Name Column6 Minuten
Number of Males from Australia7 Minuten
Tourism Survey General Detail and Spending Details10 Minuten

4 AufgabenInsgesamt 60 Minuten

Advancing Data Analysis – Sales & Tourism Projects30 Minuten
Solving Complex Sales Data Problems with MapReduce10 Minuten
Tourism Data Analytics and Insights10 Minuten
Advanced Filtering and Transformation in Tourism Analysis10 Minuten

This module focuses on educational and faculty data management projects using Hadoop’s distributed storage and processing tools. Learners will master schema design, data transformation, and optimization in Hive and Pig while enhancing database management efficiency through structural modifications and automation.

Das ist alles enthalten

7 Videos4 Aufgaben

7 VideosInsgesamt 51 Minuten

Introduction to Faculty Data Management Using HDFS7 Minuten
Education Industry6 Minuten
Adding New Column in Faculty Database Management8 Minuten
Changing Column Name and Data Type7 Minuten
Drop Column From Table and Add New Column9 Minuten
Introduction to E-Commerce Sales Analysis Using Hadoop6 Minuten
Customer Detail not from USA8 Minuten

4 AufgabenInsgesamt 80 Minuten

Managing and Transforming Educational Data30 Minuten
Faculty Data Management Using HDFS10 Minuten
Modifying Faculty Database Structures30 Minuten
Introduction to E-Commerce Data Analysis10 Minuten

The final module integrates real-world Hadoop use cases in e-commerce and employee salary analytics. Learners will apply distributed querying, filtering, and aggregation techniques to gain actionable insights from diverse data sources. The module emphasizes end-to-end analysis and reporting within Hadoop’s scalable architecture.