Alexis Kestler
Big data and Hadoop are two of the hottest technologies today. With the massive amounts of data being generated every second, organizations need ways to store, process and analyze all that information. This is where big data and Hadoop come in.
In this post, we‘ll first understand what big data and Hadoop are all about. Then we‘ll explore some of the best resources to learn these skills. Mastering big data and Hadoop can transform your career by opening up lucrative job opportunities. So let‘s get started!
What is Big Data?
Big data refers to large, complex datasets that are difficult to process using traditional data processing tools and techniques. These datasets are often unstructured or semi-structured, meaning they don‘t fit neatly into rows and columns like in a spreadsheet.
Some common characteristics of big data include:
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Volume: There‘s a huge amount of data being generated from various sources. We‘re talking petabytes and exabytes of data.
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Velocity: Data is being produced and processed at high speeds. For time-sensitive processes, we need technology that can handle real-time or near real-time data.
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Variety: Data comes in diverse formats like text, images, video, sensor data, logs, social media posts, and more.
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Veracity: With so much data of different types, it‘s a challenge to ensure high data quality and accuracy.
So in summary, big data has the 4 Vs – volume, velocity, variety and veracity. It enables organizations to gather valuable business insights from all this data through analytics. But first, we need ways to efficiently store and process all that information. This is where Apache Hadoop comes in.
What is Apache Hadoop?
Apache Hadoop is an open-source framework for storing and processing big data across clusters of commodity servers. The core components of Hadoop include:
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HDFS (Hadoop Distributed File System): This is responsible for storing huge datasets across machines in a distributed manner. It achieves reliability through replicating data across nodes.
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YARN (Yet Another Resource Negotiator): This is responsible for job scheduling and cluster resource management.
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MapReduce: This is the data processing framework that runs jobs in parallel for faster processing on large datasets.
Hadoop enables cost-effective storage and processing for big data. It scales easily by simply adding more commodity servers. Other advantages include fault tolerance, flexibility to work with diverse data types and flexibility to code in different languages like Python, R, Scala, etc.
Some common use cases of Hadoop include log processing, social media analytics, fraud detection, recommendation engines, forecasting and more. Many top companies like Amazon, Facebook, Google and NASA use Hadoop for their big data needs.
Now that you know what big data and Hadoop are all about, let‘s look at some great resources to learn these skills in-depth.
Big Data and Hadoop Course on Udemy
Udemy has a fantastic Big Data and Hadoop basics course for beginners. In 7.5 hours of video content, you‘ll learn:
- Core concepts of big data and Hadoop
- Hadoop Distributed File System (HDFS)
- MapReduce
- Pig and Hive for querying data
- Building data pipelines
The course provides hands-on experience through demo HDFS commands, sample MapReduce jobs and more. You‘ll also learn about career opportunities and salary trends in big data.
To take this course, you‘ll need some basic SQL knowledge. Overall, it‘s a great introduction to big data and Hadoop fundamentals.
Big Data Hadoop Certification by Edureka
For a more comprehensive program, Edureka has a Big Data Hadoop Certification course. Spanning over 200 hours, this course will take you from beginner to expert in big data and Hadoop.
Some key topics covered include:
- HDFS, YARN, MapReduce, Pig, Hive, HBase, Spark, Oozie, Flume, Sqoop
- Real-time case studies and projects
- MongoDB, Cassandra, Apache Kafka
- Machine learning with Spark MLlib
- Lambda architecture
- Designing streaming data architecture
Edureka also preps you for Hadoop developer and admin roles by teaching you cluster configuration, security, troubleshooting and more. Their instructors are highly experienced professionals.
You‘ll get lifetime access to the course material including videos, projects, case studies and community support. Overall an in-depth course to become a Hadoop expert.
Cloudera Hadoop Training
Cloudera, a major Hadoop vendor, offers comprehensive Hadoop training through their website. Their courses on Hadoop development, data engineering, data warehousing and more are taught by certified experts.
You can take online instructor-led training or self-paced courses. Hands-on exercises give you practical experience with concepts like:
- Storage and processing with HDFS and MapReduce
- Using HBase, Impala, Hive and Spark
- Building data pipelines and ETL workflows
- Hadoop security, governance and administration
Cloudera also offers training for different experience levels. Their Fundamentals for Apache Hadoop course is good for beginners. Overall great for learning Hadoop from one of the leaders in this space.
Big Data Specialization on Coursera
For those looking for a university-backed credential, check out this Big Data Specialization offered by UC San Diego on Coursera.
It‘s a 6 course program covering:
- Introduction to Big Data
- Big Data Modeling and Management Systems
- Big Data Integration and Processing
- Machine Learning with Big Data
- Graph Analytics for Big Data
- Big Data – Project
The courses teach you key technologies like Apache Spark, Kafka, Hadoop, MongoDB and Neo4j. Real-world case studies are used throughout to illustrate concepts. You‘ll get hands-on practice through interactive exercises and quizzes.
The specialization culminates in a capstone project where you‘ll apply your skills to solve a big data problem. Upon completing the program, you‘ll earn a certificate to showcase your learning.
LinkedIn Learning Hadoop Course
For a quick yet comprehensive overview of Hadoop, checkout LinkedIn Learning‘s Hadoop course.
In just 4 hours, you‘ll get a solid grounding in concepts like:
- HDFS, YARN
- Developing and optimizing MapReduce jobs
- Using Hive and Pig for data analysis
- Utilizing Spark and machine learning on Hadoop
Each section has hands-on demos to reinforce your learning. LinkedIn Learning also offers courses dedicated just to Hive, Spark, HBase and more for deeper dives.
A nice perk is that each completed course gets you a certificate to showcase your new skill. LinkedIn Learning comes with a 1 month free trial so you can access all their courses.
Hadoop: The Definitive Guide Book
Books are still one of the best ways to deeply learn a complex technology like Hadoop. A leading resource is Hadoop: The Definitive Guide by Tom White.
Now in its 4th edition, this best-seller provides comprehensive coverage of the Hadoop stack. Some key topics include:
- In-depth tour of MapReduce, HDFS and YARN
- Data ingestion with Sqoop and Flume
- Data processing with Spark, Pig and Hive
- HBase for storage, Zookeeper for coordination
- Security, governance, troubleshooting and more
Advanced concepts like machine learning on Hadoop, Graph computation and cloud deployment are also covered. This is a great resource for gaining true mastery over Hadoop and big data.
Big Data Foundation Course on Cognitive Class
For a free online course, checkout IBM‘s Big Data Foundation course offered through Cognitive Class. It‘s 8 hours long and covers:
- Fundamentals of big data and Hadoop
- Storage with HDFS
- Data wrangling with Pig and Hive
- Processing data with Spark
- Building machine learning models
You‘ll get access to free labs and hands-on tutorials using IBM Watson Studio. The course is self-paced and you can take assessments to earn a certificate.
Since it‘s offered by IBM, you‘ll gain skills relevant to enterprise contexts. This free course is great for dipping your toes in the water before taking more advanced programs.
YouTube Crash Course by Edureka
If you prefer learning through videos, Edureka has an 8 hour Hadoop crash course available for free on YouTube. It provides a solid overview of concepts like:
- Introduction to big data and Hadoop
- HDFS, YARN, MapReduce architecture
- Data ingestion using Sqoop and Flume
- Using Pig and Hive for analysis
- Oozie workflow scheduler
- HBase for database operations
- Spark for fast in-memory processing
The instructor explains each topic clearly with useful diagrams and code examples. Subtitles are also available in English. This free video course is a great way to efficiently grasp the basics.
Big Data Engineer Nanodegree Program by Udacity
For a more comprehensive program focused on building job-ready skills, check out Udacity‘s Big Data Engineer Nanodegree.
Spanning ~200 hours, key topics include:
- Designing data models, warehouses and data lakes
- Building pipelines for data ingestion and processing
- Scaling big data processing through Spark and Hadoop
- Optimizing data workflows using Airflow
- Deploying end-to-end big data solutions on AWS
You‘ll get hands-on practice through real-world projects in collaboration with companies like Amazon and IBM. Their knowledgeable mentors provide guidance and code reviews.
Overall an intensive program that prepares you for data engineering roles focusing on big data and Hadoop.
Big Data Course on edX
Another free online course option is edX‘s Big Data Fundamentals by The University of Adelaide. It covers:
- Introduction to big data
- Hadoop and MapReduce
- Tools like Pig, Hive, HBase, Spark
- Algorithms like PageRank and k-means clustering
- Data mining and warehousing
- Real-world big data applications
You‘ll get practical knowledge through interactive exercises using Hortonworks virtual sandbox. Subtitles are available in various languages.
A verified certificate is available for a fee that you can showcase on your CV. Overall a free course that‘s great for big data beginners.
Final Thoughts
With the exponential growth in data, gaining big data and Hadoop skills can boost your career as a data professional. But where do you start learning these complex technologies?
In this post, we explored structured courses, books, videos and other resources for learning big data and Hadoop – from basics to advanced level. Platforms like Udemy, Edureka, Coursera and EdX offer comprehensive courses. Tools like Hortonworks and IBM Cloud provide free sandboxes for hands-on practice. Resources like YouTube crash courses allow quick learning.
So what are you waiting for? Skill up with one of these resources and ride the big data career wave!
