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Big Data Foundation Course
Gain a comprehensive understanding of the foundational principles and strategies involved with big data analytics using Hadoop, Spark, Hive, and more.
Beginner
Online
6 Weeks
Quick facts
particular | details | |
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Medium of instructions
English
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Mode of learning
Self study, Virtual Classroom
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Mode of Delivery
Video and Text Based
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Course overview
Big Data Foundation Course online certification is created by Board Infinity, an online educational infrastructure targeting job applicants and learners that will enable them to grow and succeed by allowing people to function effectively. Big Data Foundation Course online classes by Board Infinity are for learners who are seeking a comprehensive training initiative to enhance their knowledge and skills in big data so that they can become skilled big data specialists from the ground up.
The Big Data Foundation Course syllabus features more than 14 hours of prerecorded video lessons that aim to help learners comprehend market dynamics, uncertain relations, and client preferences, and discover trends that enable companies to make data-driven decisions. Learners will also learn how to use tools like Hadoop, Hive, Apache Spark, MySQL, Apache Pig, PySaprk, Sqoop, MapReduce, and others to methodically extract information and analyze data sets that are too huge and complex.
The highlights
- Certificate of completion
- Self-paced course
- 14 hours of pre-recorded video content
- Case studies
- Assignments
- Projects
Program offerings
- Online course
- Mentoring from experts
- Learning resources. accessible on mobile devices
Course and certificate fees
certificate availability
certificate providing authority
What you will learn
After completing the Big Data Foundation Course online training, learners will develop an understanding of the fundamentals concepts of big data to perform big data analytics. Learners will study how to use Hive for e-commerce data analysis and will learn the basics of Hadoop, Sqoop, MySQL, and Apache Spark. Learners will be introduced to MapReduce, Spark Streaming, Spark SQL, Spark Graph X, and PySpark, as well as the Apache Pig ETL tools.
The syllabus
Week 1: Introduction to Big data analytics
Week 2: Introduction to the Hadoop Ecosystem
- What is Hadoop?
- Core components of Hadoop (HDFS and Mapreduce)
- Architecture of HDFS
- Mapreduce programming paradigm
- YARN architecture
- Word count programming using mapreduce technique
- Read/Write process in HDFS
- Practical: Word count programming using mapreduce technique"
Week 3: Introduction to Apache pig: ETL TOOL in Hadoop
- Pig architecture
- User-Defined Functions
- Practical: Real life case study on IPL dataset
Week 4: Hive database
- Hive architecture
- Advantages of Hive
- Data types in hive
- Query statements: Insert update and delete commands in Hive
- Practical: E-commerce data analysis using Hive
Week 5: SQOOP: Data ingestion tool
- Introduction to sqoop
- Importance of sqoop
- Sqooping data from mysql database to HDFS
Week 6: Apache spark
- What is spark
- How it is different from conventional Map Reduce
- Architecture of Spark
- RDD, DAG
- Overview of Spark SQL, Spark Streaming, Spark MLLib, Spark Graph X
- Execute one spark program and explain it's DAG
- Data Frame and Dataset in spark
- Overview of Catalyst Optimizer and Memory management in spark
- Overview of Pyspark
- One spark streaming program in spark if time permits.
- Overview of MLLib.
Instructors
Mr Sumit Ganguly
Team Leader
Cognizant
B.E /B.Tech
Mr Raghu Raman A V
Data and Cloud Expert
Dell
Articles
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