Online Classroom Batches Preferred
Weekdays Regular
(Class 1Hr - 1:30Hrs) / Per Session
Weekdays Regular
(Class 1Hr - 1:30Hrs) / Per Session
Weekend Regular
(Class 3hr - 3:30Hrs) / Per Session
Weekend Fasttrack
(Class 4:30Hr - 5:00Hrs) / Per Session
No Interest Financing start at ₹ 5000 / month
Skills You Will Gain
- Big Data, HDFS
- YARN, Spark
- MapReduce
- PIG, HIVE
- Mahout, Spark MLLib
- Solar, Lucene
- Zookeeper
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Big Data Hadoop Course Curriculam
Trainers Profile
Trainers are certified professionals with 11+ years of experience in their respective domains as well as they are currently working with Top MNCs. As all Trainers from Big Data Hadoop Certification Course are respective domain working professionals so they are having many live projects, trainers will use these projects during training sessions.
Pre-requisites
Following is sufficient for basics of Big Data Hadoop technologies :
Syllabus of Big Data Hadoop Online Course Download syllabus
- What is Big Data?
- What technologies support big data?
- What is Hadoop?
- Why Hadoop?
- History of Hadoop
- Use cases of Hadoop
- RDBMS vs Hadoop
- Ecosystem tour
- Vendor comparison
- Hardware Recommendations & Statistics
- Significance of HDFS in Hadoop
- Features of HDFS
- 5 daemons of Hadoop
- Data Storage in HDFS
- Accessing HDFS
- Fault tolerance
- Download Hadoop
- Installation and set-up of Hadoop
- HDFS Federation
- Map Reduce Architecture
- How Map Reduce works
- Developing Map Reduce
- Map Reduce Programming Model
- Creating Input and Output Formats in Map Reduce Jobs
- Data localization in Map Reduce
- Combiner (Mini Reducer)
- Hadoop I/O
- Distributed cache
- Introduction to Apache Pig
- Map Reduce Vs. Apache Pig
- SQL vs. Apache Pig
- Different data types in Pig
- Modes of Execution in Pig
- Grunt shell
- Loading data
- Exploring Pig
- Latin commands
- Hive introduction
- Hive architecture
- Hive vs RDBMS
- HiveQL and the shell
- Managing tables (external vs managed)
- Data types and schemas
- Partitions and buckets
- Architecture and schema design
- HBase vs. RDBMS
- HMaster and Region Servers
- Column Families and Regions
- Write pipeline
- Read pipeline
- HBase commands
- Introduction
- SQOOP syntax
- Database connection
- Importing data
- Introduction
- Flume syntax
- Database connection
- Importing data
- Introduction to Apache Spark
- Apache Spark Framework
- Playing with RDD’s
- Using Spark Shell
- Writing Spark Applications
- DataFrames and DataSets
- DataFrame Operations
- Creating & Saving DataFrames from Data Sources
- Transformations & Actions
- Caching & Persisting
- Spark SQL
- Introduction to Cloud Computing
- On-premises vs cloud setup
- Major cloud providers of Bigdata
- What is EMR?
- HDFS vs S3
- Overview and working of AWS Glue jobs
- AWS Glue
- AWS Redshift
- AWS Athena
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Big Data Hadoop Training Objectives
- An in-depth description of the Big Data Hadoop technology, its components, and how you can utilise it for effective data analysis are all covered in the Big Data Hadoop certification course, an online training programme. Topics covered in the course include the Hadoop architecture, HDFS, MapReduce, HBase, Hive, Pig, Sqoop, Flume, and Oozie.
- Hadoop primarily uses two programming languages: Java and Python. Java is the most popular language for Hadoop due to its strong object-oriented programming capabilities, efficient memory management and versatility. Python is also popular for its easy to use syntax and its ability to handle large data sets. In addition, Scala, C++, and Ruby are also used with Hadoop.
- Big Data Hadoop can be quite challenging. It requires knowledge of distributed computing and the HDFS file system, as well as an understanding of how to use Hadoop’s core components like MapReduce, Hive, Pig, and Spark.
- Yes, those who work with Big Data Hadoop can earn a very competitive salary. Depending on the job role, individuals may receive an average annual salary of between $ 90,000 and $ 150,000.
- Organizations use Big Data Hadoop to store, process, and analyze vast amounts of data quickly and economically. Big Data Hadoop can help organizations make better decisions, improve customer service, and gain competitive insights.
- People who ought to enroll in the Big Data Hadoop course should have a basic understanding of computer science and programming languages such as Java, Scala, and Python. Additionally, they should have some knowledge of distributed computing and the HDFS file system.
- It is used in a wide variety of industries, including manufacturing, healthcare, finance, retail, media, and more. Companies use Hadoop to store, process, and analyse large datasets with the help of tools such as MapReduce, Hive, Pig, and Spark.
- Big Data Hadoop is used to store and process large datasets that are too large or too complex for traditional database management systems. Hadoop is a distributed storage and computing platform that is designed to scale up from a single server to thousands of machines, processing large amounts of data quickly and reliably.
- The demand for Big Data Hadoop courses is increasing as businesses become more reliant on Big Data and Hadoop technologies. It is a valuable skill that can open up a lot of job opportunities and is a great way to get started in the field of Big Data.
- Introduction to Big Data and Hadoop.
- Hadoop Fundamentals.
- Advanced Hadoop Administration.
- Big Data Analytics with Hadoop.
- Hadoop Performance Tuning.
Exam & Certification
- Participate and Complete One batch of Big Data Hadoop Training Course
- Successful completion and evaluation of any one of the given projects
- Complete 85% of the Big Data Hadoop course
- Successful completion and evaluation of any one of the given projects
- Oracle Certified Associate (OCA)
- Oracle Certified Professional (OCP)
- Oracle Certified Expert (OCE)
- Oracle Certified Master (OCM)
- Learn About the Certification Paths.
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