double quote Supercharge your career growth in Big Data

Free Big Data Analytics Online Course

Big Data Analytics Course

Learn big data from basics in this free online training. Big data course is taught hands-on by experts. Understand all about hadoop, hive, apache kafka, spark. Go from beginners level to advance in this big data course.

Instructor:

Mr. Sajan Kedia
4.54
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Ratings

Intermediate

Level

28.5 Hrs

Learning hours

136.8K+
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Learners

Skills you’ll Learn

About this Free Certificate Course

The Big Data course will introduce you to prominent big data tools, with a few demonstrations and case studies for each of these tools. The course shall focus on working with each of these tools for analytics purposes. It shall begin with a briefing on Hadoop, discussing the framework and its different versions. You will learn about the Hive tool to work with SQL and illustrations, the Spark tool for steaming and analyzing, the RDD and PySpark concepts, working and functioning.

 

In the latter part of the Mastering Big Data Analytics course, you will understand working with Apache Kafka and advanced Spark concepts. The course also includes projects you can work with and five assessments to evaluate your gains on each topic. Complete the course for free and avail your certificate. We allude to the attached materials for reference. 

 

After this free, self-paced, intermediate's guide to Big Data Analytics, you can enroll in the Data Science and Big Data Analytics course and embark on your career with the professional Post Graduate certificate. Learn various concepts in depth with millions of aspirants across the globe!

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Course Outline

Hadoop - Master your Big Data

Hadoop is an Apache suite framework for distributed processing of massive datasets spread across computer clusters. 

Hive - Big Data SQL

Hive is an Apache suite software project built for data query and analysis, providing an SQL-like interface to query data stored across databases. 

Spark - Stream and Analyze the Big Data

Spark is an open-source Apache suite tool that provides a unified analytics engine for large-scale data processing and an interface for cluster programming. 

Apache Kafka - A Distributed Streaming Platform

Kafka is an open-source Apache suite platform for distributed event streaming and high-performance pipelining.

Advanced Spark

Advanced Spark is responsible for managing, shuffling, and optimizing catalysts for resources to work with huge data sets.

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Projects
Yellow Taxi trip analysis using Hive
The NYC taxi trip Analysis project is as elite as it sounds. The dataset is well designed to put your big data skills to the ultimate test. The project will untie your potential to hone as well as master exploratory data analysis on the given dataset. The ultimate aim of the project is to derive the highest possible revenue figures using Hadoop and Hive.
Sentiment Analysis on Twitter in Real Time
With over 500 million tweets wrapped up in 280 words, Twitter is the home to one of the crispest and concisely written content on the web. From space tweets to ( Lebron James’ on chicken nuggets OR Donald Trump’s infamous ‘covfefe’ tweet), it hosts ideas, comments, and sentiments with minimum jargons and more information. This makes it an ideal platform for Sentiment Analysis using Machine Learning. This project will enable you to run analysis on real-time tweet data, derive opinions and understand trends on a gamut of trending topics across the globe, and obtain a riveting visual plot using PySpark

Our course instructor

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Mr. Sajan Kedia

Data Scientist, Myntra

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136.7K+ Learners
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1 Courses

Sajan did B.Tech. & M.Tech. in Computer Science from IIT BHU. During Masters, he worked on Data Mining & published research papers on the topic. He has worked with IBM Research Labs on NLP part of IBM Watson AI Project. After that, he worked with an AdTech startup as Senior Data Scientist, where he was working on Building Real-Time Machine Learning Models on TBs of Ad stream data.

Currently, he is leading the Data Science Team of Pricing at Myntra, building AI systems for the personalised price. He has very good expertise in Big Data technologies, Machine learning, and NLP. His hobbies are trekking, traveling, adventure and fitness activities.

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What our learners say about the course

Find out how our platform helped our learners to upskill in their career.

4.54
Course Rating
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What our learners enjoyed the most

Ratings & Reviews of this Course

Reviewer Profile
Vishesh Jain

5.0

“Big Data Analytics Course: An Amazing Experience”
I would like to thank the tutor for his excellent teaching on the Big Data Analytics course. Every topic covered in the course was amazing and informative. He has a great way of explaining complex concepts in a clear and concise manner. He was always patient and willing to answer any questions that I had. I found the course to be very valuable and I would highly recommend it to anyone interested in learning about big data analysis. Thank you again for your excellent teaching. I hope this feedback is helpful. Please let me know if you have any other questions.
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Preet Patel

5.0

“Engaging and Informative Learning Experience”
I thoroughly enjoyed the depth of the curriculum and the well-structured quizzes and assignments. The instructor did an excellent job breaking down complex concepts, making them easy to follow. The course not only improved my skills but also provided practical tools that I can immediately apply in my work. Overall, a highly valuable experience.
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Norman Tavengwa

5.0

“The Online Big Data Course Enhanced My Skills in Hadoop, Spark, and Data Processing”
The online Big Data course was a transformative journey that deepened my understanding of data processing and analytics. I learned essential tools like Hadoop and Spark, gaining hands-on experience through practical assignments and real-world projects. The interactive lectures facilitated engaging discussions, allowing me to collaborate with peers and gain diverse insights. I particularly appreciated the focus on scalability and performance optimization in big data systems.
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Vishal Zala

5.0

“A Bit Tough but the Instructor Taught So Well!”
I really enjoyed the course. It was well-organized, starting from basics and moving to advanced topics. The instructors were knowledgeable. I highly recommend this course for anyone interested in big data!
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Manthan Patel

4.0

“A Very Good Experience: Easy to Learn and Great Content”
My experience with the Big Data Analytics program on Great Learning was truly rewarding. The course is well-structured, offering a blend of theoretical knowledge and hands-on experience with real-world projects. It covers the essential tools and technologies used in the industry, such as Hadoop and Spark, which have significantly boosted my confidence in working with large datasets. The platform's mentorship and support system were also excellent. I appreciated the interactive sessions with industry experts and the timely assistance from program managers.
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Vishal Randhawa

5.0

“Insightful Learning Experience in Spark and Kafka”
I particularly enjoyed the hands-on approach to learning, which allowed me to apply theoretical concepts directly to practical scenarios. The curriculum was well-structured, making it easy to follow along and build upon my existing knowledge. The instructor was knowledgeable and engaging, providing valuable insights and answering questions effectively. Overall, the experience enhanced my skills in Spark and Kafka significantly.
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Devarsh Soni

5.0

“An In-Depth Course on Big Data Frameworks”
This course provides an in-depth understanding of big data frameworks and tools like Hadoop and Spark. With well-structured modules, it covers data processing, analysis, and visualization techniques. The practical exercises and case studies help in mastering real-world applications. Overall, it's a valuable course for anyone looking to enhance their big data skills.
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Ayoub BOUHATOUS

5.0

“A Pleasant and Useful Course”
The course is easy to follow, clear, and explains each concept with examples, making it easy to understand.
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Het raghuvanshi

5.0

“Learning About Big Data and Exploring Big Data”
The online Big Data workshop was insightful! The hands-on approach with tools like Hadoop and Spark really enhanced my understanding. Highly recommend for anyone looking to boost their data skills!
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Reviewer Profile
PRIYANKA PATHAK

5.0

“Engagement and Interaction: Opportunities for Active Participation”
Comprehensive Content: The course covered a wide range of topics, providing a thorough understanding of the subject matter. Engaging Teaching Style: The instructor's teaching methods were dynamic and engaging, making complex concepts easier to understand. Hands-On Experience: Practical exercises, labs, or projects allowed for hands-on learning, reinforcing theoretical knowledge. Real-World Applications: Case studies and examples from industry illustrated how the concepts apply in real-world situations. Collaborative Environment:
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Big Data Analytics Course

28.5 Learning Hours . Intermediate

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Frequently Asked Questions

What prerequisites are required to learn the “Mastering Big Data Analytics” course?

Big Data Analytics is an intermediate-level course, and you will need to have a thorough understanding of computer science to start with the course. You will also have to do a little homework, so we suggest you learn the basics of Data Science and Analytics before diving into this course.

How long does it take to complete this free Big Data Analytics course?

The Big Data Analytics free certificate course is 19-hours long. You can learn it at your convenience since the course is self-paced.

Will I have lifetime access to this free course?

Yes, once you enroll in the course, you will have lifetime access to this Great Learning Academy's free course. You can log in and learn at your leisure. 

What are my next learning options after this Mastering with Big Data Analytics course?

Once you complete this free course, you can opt for a Master's in Data Science that will aid in advancing your career growth in this leading field.

Is it worth learning Big Data Analytics?

 Yes, it is beneficial to learn Big Data Analytics. Data is only increasing every second, and with this rapid growth, humans can't process such massive data without using technology.  Big data analytics is one key method to deal with such massive data. So the demand for data science and big data analytics professionals will only grow in the future, making it the best learning option. 

What are Big Data tools used for?

Big Data tools process and extract valuable insights from the vast data pool. These big data tools make it easier and faster to perform data-related operations to organize, store and load them for any organizational purposes. 

Why is Big Data Analytics so popular?

Big data involves various tools for analytics purposes, making it a popular tool. Hadoop is used for distributed processing of enormous data sets across different clusters; Hive reads, writes, and manages a large set of data using SQL in distributed storage; Spark is a unified engine to process extensive data sets and provides an interface for program clusters, and Apache Kafka is a tool used for high-performance data pipelines and streaming analytics.

Will I get a certificate after completing this free Big Data Analytics course?

Yes, you will get a certificate of completion for the Big Data Analytics course after completing all the modules and cracking the assessment/quiz. All the assessments test your knowledge of the subject and badges your skills. 

What knowledge and skills will I gain upon completing this course?

You will gain the foundational knowledge of how to use big data tools such as Apache Hive, Hadoop, Spark, PySpark, and Apache Kafka. You will also learn the advanced concepts in Spark. With these concepts and a good hold on prominent big data tools, you can effectively analyze and work with any size of data. 

How much does this “Mastering Big Data Analytics” course cost?

 It is an entirely free course from Great Learning Academy. Anyone interested in learning big data tools for analytics and understanding big data concepts can start with this course. You can also refer to the attached materials for additional knowledge. 

Is there any limit on how many times I can take this free course?

 Once you enroll in the Big Data Analytics course, you have lifetime access to it. So, you can log in anytime and learn it for free online at your convenience. 

Can I sign up for multiple courses from Great Learning Academy at the same time?

Yes, you can enroll in as many courses as you want from Great Learning Academy. There are no strictures to the number of courses you can enroll in at once, but since the courses offered by Great Learning Academy are free, we suggest you learn one by one to get the best out of the subject. 

Why choose Great Learning Academy for this free Big Data Analytics course?

Great Learning is a global educational technology platform committed to developing skilled professionals. Great Learning Academy is a Great Learning project that provides free online courses to assist people in succeeding in their careers. Great Learning Academy's free online courses have helped over 4 million students from 140 countries. It's a one-stop destination for all of a student's needs.

This course is free and self-paced. It also includes solved problems, demonstrated codes, case studies, hands-on projects, and presented examples to help you comprehend the numerous areas that fall under the subject. It also awards you a certificate to showcase your skills. The course is conducted by topic experts and carefully tailored to cater to beginners and professionals.

Who is eligible to take this course?

Anybody interested in learning big data tools and understanding big data analysis with a basic knowledge of computer science, data science, and big data can take up the course. So, enroll in our course today and learn it for free online.

What are the steps to enroll in this Mastering Big Data Analytics course?

Enrolling in Great Learning Academy's Mastering Big Data Analytics is a simple and straightforward approach. You will have to sign-up with your E-Mail ID, enter your user details, and then you can start learning at your own pace. 

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Big Data Analytics Course

Big Data Analytics is the statistical analysis of a large volume of data sets in parallel, distributed environments. This course on Big Data gives you a complete understanding of emerging Big data technology and career growth in Big data. It is well designed for beginners as well as professionals.

Big data has significantly impacted industries today, and it is a cutting-edge technology used in every business field.

Nowadays, companies are using big data technologies to make their businesses more informative and make business decisions by enabling data analysts and other professionals to analyze high volumes of data. 

Introduction to Big Data

Let‘s talk about data first, before going to the term 'Big Data'.

What is data?

Data plays a very essential and significant role in this technological world. It is defined as any piece of information that refers to or represents conditions, ideas, or objects. Examples are alphabets, symbols, numbers, etc. Data can be students' information, or it can be pictures posted on social media. Data is limitless, present everywhere in the surroundings, and it is increasing day by day.

Now, What is Big Data?

It is defined as the large amount of data that cannot be processed and stored with the traditional system, i.e., Relational Database Management System. Today, we deal with heterogeneous data developed at an alarming rate by multiple sources. This data consists of structured, unstructured, & semi-structured data that can be used for research or analysis.

Why is there a need for Big Data?

Data is growing day by day, so it has become difficult to store and process these huge amounts of data.
Therefore, the following points describe the need for big data.

  • * Large Volume of Data 
  • * Heterogeneous Data (which is structured, unstructured, and semi-structured data)
  • * Traditional Database Systems cannot maintain this vast amount of data.
  • * Building a single system is complex and not cost-effective.
  • * The Relational Database Management System is very expensive.

5 V’s of Big Data :

The 5 V’s of Big Data are as follow:

1.Volume - It refers to the amount of data that deals with the enormous size of Petta bytes. Credit card transactions or tweets in a day are common examples of the high volume of data. Thus, Big data helps in storing and processing this high volume of data.

2.Variety- It is defined as the type of data ‘generating and transferring.

Data present in three formats which are as follow:

  • i. Structured Data - The data which exists in a tabular format with a relationship between the different rows and columns. It has a fixed structure or schema.
  • Examples of structured data are SQL databases or Excel files. This data is the most traditional form of data storage.
  • ii. Semi-Structured Data - Semi-structured data is raw data, which does not exist in tabular format i.e rows and columns. JSON, XML,, and some NoSQL databases like MongoDB that store data in ‘JSON format’ are the common examples of semi-structured data. 
  • iii. Unstructured Data - Unstructured data is schema-less, highly unpredictable, and cannot be represented in a specific deterministic format.

Common examples of unstructured data are audio, video files, images, or NoSQL databases

3.Velocity- It refers to the speed at which large volumes of data are being generated, collected, and analyzed. Every day the number of emails, Twitter messages, photos, videos-clips, etc are lighting speeds around the world. Every second of everyday data is increasing.

4.Veracity- It refers to the uncertainty of available data i.e data is valid or not. It arises due to the high volume of data that produces incompleteness and inconsistency. It is the quality or trustworthiness of data that is how accurate is all data?

5.Value - It refers to the worth of the data being taken out. Also, turning data into value. Having an endless amount of data is one thing, but unless it can be turned into the value it is feckless. Therefore, Valuable data is needed.

Big Data Technologies

There are various frameworks in big data technologies to solve the problems of Big Data Storage and processing. Such frameworks are Apache Hadoop, Apache Kafka, Apache Spark, Apache Samza, Apache Hive, etc. Let’s take a look at these frameworks:

Big Data Frameworks

  • Apache Hadoop - Apache Hadoop is an open-source framework that allows the storage and processing of a enormous volume of data in a distributed & parallel order.
  • Apache Kafka - Apache Kafka is a batch processing framework with a streaming platform.
  • Apache Spark - Apache Spark is a data processing framework. It is 100 times faster to process data than MapReduce.
  • Apache Samza - Apache Samza is a streaming data processing tool.
  • Apache Hive - Apache Hive is a distributed Data Warehouse software.
  • Apache Cassandra - Apache Cassandra is a decentralized NoSQL Database Management system.

Applications of Big Data -

Today Big data is everywhere. It is almost in every sector. It has become an essential part of the analysis and is required for the growth of businesses.

Big data has a large range of applications. Following are the applications of Big Data.

1) Social Networking sites

All social networking sites like- Facebook, Linkedin, Twitter, Instagram, etc are generating a huge amount of heterogeneous data on a day to day basis because these all websites include billions of users worldwide. 

2) Share Market

Share Market produces a high-volume of data through its daily transaction worldwide.

3) Weather Station

Big data technologies play a vital role in weather forecasting. A massive volume of data is provided on the climate, and an average is extracted to predict the weather. This can be lucrative to predict natural calamities such as floods etc.

4) E-commerce sites 

Sites like Amazon, Flipkart, Myntra, Bigbasket produce large amounts of logs from which customers buying trends can be traced.

5) Telecom company

Big Data has a very great impact on Telecom companies. Big telecom giants like Airtel, Jio, and Vi observe the customer trends and releases their plans accordingly. These big companies store information about their million users.

6) Fraud Detection

Big data technologies help in fraud detection and prevention. It also helps in risk analysis and management

7) Healthcare 

Big data technology is very important to the healthcare sector. All the information of patients, their health plans, their insurance plans, and their other records are stored and processed with big data. By analyzing huge volumes of structured & unstructured data, healthcare providers can give lifesaving diagnoses or treatments immediately.

8) Public Sector

Big data technology also plays an important role in the government as well as the public sector. It gives a lot of facilities in power investigation, economic promotion, etc.

Government has a record of more than 1.21 billion citizens with UID or Aadhaar cards. This large volume of data is analyzed and stored to find useful information from the data.

Banking, Educations, Agriculture, Advertising and Marketing, Insurance and Travel, and Tourism are the other common applications of Big Data.

Big Data has proved one of the fast-growing technologies in today’s world. It is a boon because it can also be merged with other technologies like machine learning, artificial intelligence (AI), and other cloud technologies.

 

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