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Big Data Analytics: Beginner

Big Data Analytics Track

Big Data Analytics:
Beginner

4.8 (1,230 reviews)

Introduction to Big Data Analytics: Beginner. Understand data fundamentals, key tools like Excel & SQL, and explore data collection, cleaning, and visualization techniques.

Created by Avanteia
12,580 Total Enrolled
15 September 2024 Last Updated
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Big Data Analytics Beginner Course
1 Month Duration
Certificate On Completion
Beginner Level
4 Modules Syllabus
1 Month Duration
English Language
Certificate Included
Introduction

Overview

Understand data fundamentals, key tools like Excel & SQL, and explore data collection, cleaning, and visualization techniques.

Big Data Hadoop Spark Python SQL Visualization
Goal

Learning Outcome

Understand core big data concepts, use basic big data technologies, manage data storage and processing, and perform introductory data analysis and visualization.

Curriculum

Syllabus

Click any module to expand and view topics and hands-on labs included.

  • What is Big Data? 5 Vs (Volume, Velocity, Variety, Veracity, Value)
  • Big Data ecosystem & career scope
  • Traditional databases vs Big Data systems
Hands-on Lab
Explore Kaggle datasets Exploratory data analysis using Python (Pandas + Matplotlib)
  • Data sources (logs, IoT, social media, sensors)
  • Batch vs Streaming data ingestion
  • ETL concepts (Extract, Transform, Load)
Hands-on Lab
Use Python requests + APIs to collect data Ingest streaming data using Kafka local setup
  • HDFS (Hadoop Distributed File System)
  • MapReduce programming model
  • Hadoop ecosystem (Hive, Pig, HBase, Sqoop)
Hands-on Lab
Install Hadoop single-node cluster (local VM or Docker) Run HDFS file operations (upload, list, read, delete) Execute a simple MapReduce word count job
  • Introduction to Hive & HQL (Hive Query Language)
  • Data warehousing concepts
  • Partitioning & Bucketing
Hands-on Lab
Install Apache Hive Run SQL queries on Hive tables (select, group by, join)
Results

What You Will Learn

Big Data Fundamentals

Understand the 5 Vs of Big Data, ecosystem components, and career opportunities in the field.

Data Collection & Ingestion

Collect data from APIs, handle batch and streaming ingestion, and understand ETL workflows.

Hadoop Ecosystem

Work with HDFS, run MapReduce jobs, and navigate the Hadoop ecosystem including Hive and Pig.

Data Warehousing & Hive

Use Hive Query Language for data warehousing, partitioning, and bucketing strategies.

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