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.
Big Data with Hadoop: Apply MapReduce, Pig & Hive
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您将学到什么
Process and analyze sensor data using Pig, Hive, and MapReduce.
Preprocess JSON files and design end-to-end data workflows.
Generate insights from demographic and income-based datasets.
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最近已更新！
November 2025
作业
10 项作业
授课语言：英语（English）
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本课程是 Hadoop Big Data Analytics & Projects Mastery 专项课程 专项课程的一部分
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该课程共有3个模块
This module introduces the foundations of sensor data analysis and the principles of Big Data processing. Learners explore how raw data is collected, structured, and converted into usable formats, followed by an introduction to Hadoop MapReduce. The module covers real-world use cases including demographic analysis, income tax prediction, and child labor detection, helping learners understand how analytics can drive social and economic insights.
涵盖的内容
17个视频4个作业
This module focuses on Apache Pig, a high-level data flow language used for simplifying Big Data processing. Learners gain practical skills in Pig functions, relations, and data flow management while reducing the complexity of coding compared to MapReduce. Through hands-on use cases, students practice grouping, filtering, and aggregating sensor data to uncover patterns and generate meaningful ratios for analysis.
涵盖的内容
12个视频3个作业
This module explores Apache Hive, a data warehouse tool that enables SQL-like querying of large datasets. Learners examine Hive’s key features, its ability to query JSON data, and how it empowers non-programmers to analyze massive datasets efficiently. By completing Hive-based use cases, learners discover how to transform raw data into meaningful reports that support government and business decision-making.
涵盖的内容
7个视频3个作业
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