Brief Introduction
Perform real-time data analytics, streaming, and batch processing using Hadoop 3Description
Big Data processing is creating a lot of buzz in the market, with organizations having to deal with large amounts of data on a daily basis. Processing such data and extracting actionable insights from it is a major challenge; that’s where Hadoop comes to the rescue. Apache Hadoop is an open source framework for distributed storage and processing of Big Data. If you’re a big data professional or a data analyst who wants to smoothly handle big data sets using Hadoop 3, then go for this course.
This comprehensive 2-in-1 course will get you started with exploring Hadoop 3 ecosystem using real-world examples. You will then be able to see how the structured, unstructured, and semi structured data can be processed with Hadoop. You will also learn to tackle some of the major problems faced in Big Data by making use of various Hadoop components and tools such as MapReduce, Yarn, Pig, HBase, and HDFS. Next, you will delve into Hive, Spark, and its related tools to perform real-time data analytics, streaming, and batch processing on your applications. Finally, you will learn how to extend your analytics solutions to the cloud.
Contents and Overview
This training program includes 2 complete courses, carefully chosen to give you the most comprehensive training possible.
The first course, Hands-On Big Data Processing with Hadoop 3, majorly focuses on the problem faced in Big Data and the solution offered by respective Hadoop component. You will learn to use different components and tools such as Mapreduce to process raw data and will learn how tools such as Hive and Pig aids in this process. You will then move on to data analysis techniques with Hadoop using tools such as Hive and will learn to apply them in a real world big data application. Next, you will learn how to perform real-time data analytics, streaming, and batch processing on your application. Finally, you will learn how to extend your analytics solutions to the cloud.
In the second course, Hands-On Big Data Analysis with Hadoop 3, you will start off by learning data analysis techniques with Hadoop using tools such as Hive. Furthermore, you will learn to apply these techniques in real-world big data applications. You will also delve into Spark and its related tools to perform real-time data analytics, streaming, and batch processing on your applications.
By the end of this course, you will have gained all the knowledge required to work with big data sets using Hadoop 3 with ease.
Meet Your Expert(s):
We have the best work of the following esteemed author(s) to ensure that your learning journey is smooth:
Sudhanshu Saxena is a renowned name in Big Data analytics, works as a Big Data Scientist & Speaker, Machine Learning Expert and Big-data Analytics trainer. After Completing Bachelor of technology, he holds an experience of 12+ years in corporate as Expert facilitator and corporate behavioral trainer, skilled in designing programs, content development, facilitating organizational development workshops. The expert lead a team of Data Scientists to solve the Business problems. Connected with more than 55 corporates and training bodies for Data science and training in Artificial intelligence for pan India. He has successfully mentor more than 5000 Hours online classes/Webinars for Big Data and Hadoop and various programs. Been a trainer for More than 33 corporate trainings, 350 classroom sessions in associations with different International training organizations. Has been a speaker for 36+ corporate session for Machine learning and Big Data Analytics and visualization. Being a part of highly revolutionary IT industry as realized the gap between industry trends, native technologies and understanding, he started to share his experience and knowledge towards native technology and analysis through practical experience. Presently he also provides consulting on Big data analytics, Hadoop, ML project for various MNCs.
Tomasz Lelek is a Software Engineer who programs mostly in Java and Scala. He is a fan of microservice architectures and functional programming. He dedicates considerable time and effort to being better every day. Recently, he's been delving into big data technologies such as Apache Spark and Hadoop. He is passionate about nearly everything associated with software development. He thinks that we should always try to consider different solutions and approaches to solving a problem. Recently, he was a speaker at several conferences in Poland - Confitura and JDD (Java Developer's Day) and also at Krakow Scala User Group.Conference. He was also a speaker at an international event in Dhaka. He is very enthusiastic and loves to share his knowledge.
Requirements
- Requirements
- Basic knowledge of Java is assumed.
Knowledge
- Learn each component of the Hadoop 3 ecosystem
- Learn data storage and data processing in Hadoop using UNIX commands
- Import the data and deal with structured data and query it through Hive
- Import the data from non RDBMs source and store in HDFS
- Deal with semi structured data and unstructured data through PIG
- Share and access data in a SQL-like interface for HDFS
- Analyze real-time events using Spark streaming
- Perform complex big data analytics using MapReduce
- Analyze data to perform complex processing with Hive and Pig
- Explore functional programming using Spark
- Learn how to import data using Sqoop
Packt Publishing
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