Big Data Basics: Understand the Ecosystem

Categories: BIG DATA

About Course

Big Data Basics: Understand the Ecosystem is an introductory course designed to help you grasp the fundamental concepts, technologies, and components of the modern Big Data landscape. You’ll learn how large-scale data is stored, processed, and analyzed using tools like Hadoop, Spark, NoSQL databases, and cloud-based data lakes.

This course is ideal for students, early-career professionals, and anyone interested in data engineering, data science, or cloud analytics. No coding or prior data experience required — just curiosity and a desire to explore how Big Data transforms industries.

What is Big Data? Volume, Variety, Velocity, and Veracity
Overview of the Big Data ecosystem
Understanding Hadoop architecture (HDFS, YARN, MapReduce)
Introduction to Apache Spark and in-memory processing
Basics of NoSQL databases (MongoDB, Cassandra, HBase)
Concepts of data lakes, data warehouses, and ETL pipelines
Role of cloud platforms (AWS, Azure, GCP) in Big Data
Real-world Big Data use cases in finance, healthcare, and retail
How Big Data supports AI, ML, and advanced analytics

Course Content

Module 1: Big Data Fundamentals
Defining Big Data and its importance The 4 Vs of Big Data

Module 2: Hadoop Ecosystem
HDFS architecture YARN and MapReduce overview Tools: Hive, Pig, Oozie, Flume

Module 3: Apache Spark Basics
What is Spark and how it differs from Hadoop Spark Core, SQL, and streaming modules

Module 4: NoSQL Databases
Key-value stores, document databases, columnar databases Use cases and comparisons with RDBMS

Module 5: Data Storage & Pipelines
Data lakes vs. data warehouses ETL and ELT pipeline design basics

Module 6: Big Data in the Cloud
Introduction to AWS EMR, Azure HDInsight, Google DataProc Scalability and cost benefits of cloud-based Big Data

Module 7: Applications & Industry Use Cases
Big Data in healthcare, e-commerce, banking, and IoT Final mini-project: Build a mock Big Data solution architecture

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Big Data Basics: Understand the Ecosystem

About Course

What Will You Learn?

Course Content

Module 1: Big Data Fundamentals
Defining Big Data and its importance The 4 Vs of Big Data

Module 2: Hadoop Ecosystem
HDFS architecture YARN and MapReduce overview Tools: Hive, Pig, Oozie, Flume

Module 3: Apache Spark Basics
What is Spark and how it differs from Hadoop Spark Core, SQL, and streaming modules

Module 4: NoSQL Databases
Key-value stores, document databases, columnar databases Use cases and comparisons with RDBMS

Module 5: Data Storage & Pipelines
Data lakes vs. data warehouses ETL and ELT pipeline design basics

Module 6: Big Data in the Cloud
Introduction to AWS EMR, Azure HDInsight, Google DataProc Scalability and cost benefits of cloud-based Big Data

Module 7: Applications & Industry Use Cases
Big Data in healthcare, e-commerce, banking, and IoT Final mini-project: Build a mock Big Data solution architecture

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About Course

What Will You Learn?

Course Content

Module 1: Big Data Fundamentals Defining Big Data and its importance The 4 Vs of Big Data

Module 2: Hadoop Ecosystem HDFS architecture YARN and MapReduce overview Tools: Hive, Pig, Oozie, Flume

Module 3: Apache Spark Basics What is Spark and how it differs from Hadoop Spark Core, SQL, and streaming modules

Module 4: NoSQL Databases Key-value stores, document databases, columnar databases Use cases and comparisons with RDBMS

Module 5: Data Storage & Pipelines Data lakes vs. data warehouses ETL and ELT pipeline design basics

Module 6: Big Data in the Cloud Introduction to AWS EMR, Azure HDInsight, Google DataProc Scalability and cost benefits of cloud-based Big Data

Module 7: Applications & Industry Use Cases Big Data in healthcare, e-commerce, banking, and IoT Final mini-project: Build a mock Big Data solution architecture

Student Ratings & Reviews

Trending Courses

Trending College Workshops

Company

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Categories

Module 1: Big Data Fundamentals
Defining Big Data and its importance The 4 Vs of Big Data

Module 2: Hadoop Ecosystem
HDFS architecture YARN and MapReduce overview Tools: Hive, Pig, Oozie, Flume

Module 3: Apache Spark Basics
What is Spark and how it differs from Hadoop Spark Core, SQL, and streaming modules

Module 4: NoSQL Databases
Key-value stores, document databases, columnar databases Use cases and comparisons with RDBMS

Module 5: Data Storage & Pipelines
Data lakes vs. data warehouses ETL and ELT pipeline design basics

Module 6: Big Data in the Cloud
Introduction to AWS EMR, Azure HDInsight, Google DataProc Scalability and cost benefits of cloud-based Big Data

Module 7: Applications & Industry Use Cases
Big Data in healthcare, e-commerce, banking, and IoT Final mini-project: Build a mock Big Data solution architecture