With 2.5 quintillion bytes of data being produced by humans every day, 95% of businesses citing the need to manage unstructured data as a problem for their business and 97.2% of organizations investing in big data & AI, there’s a necessity to understand what big data and its applications along with related tools. This course is aimed at enabling you to understand what big data is beginning form its 4Vs and learn distributed computing, Hadoop ecosystem, structured & unstructured data. Also, you shall learn to how big data landscape is changing and impacting your business with real-world use cases. Even more, you get to implement abstract data pipelines to execute ETL process on sample dataset after designing schema, ER diagrams to understand the development life cycle.
Schedule: Monday, Wednesday, Friday - 6pm - 9pm
Get trained by industry ExpertsOur courses are delivered by professionals with years of experience having learned first-hand the best, in-demand techniques, concepts, and latest tools.
Official Certification curriculumOur curriculum is kept up to date with the latest official Certification syllabus and making you getting ready to take the exam.
Tax CreditClaim up to 25% of tuition fees and education tax credit.
Discount on Certification VoucherUpto 50 percent discount voucher will be provided.
24/7 Lab accessOur students have access to their labs and course materials at any hour of the day to maximize their learning potential and guarantee success.
Introduction to Big Data and Applications
This modules provides an overview of the big data, understanding Big data ecosystem, setting up the environment like cloudera vm setup, GCP Cluster Fixes and Cluster Setup on Google Cloud.
This module explores the concepts of 4V's Volume, Variety, Velocity and Veracity and concepts lo HDFS and Hadoop commands and overview of the Yarn ecosystem.
This module provides Sqoop introduction, Managing Target Directories, Working with Parquet file format, Working with Avro File Format, Working with Different Compressions, Conditional Imports, Split-by and Boundary Queries, Field delimeters, Incremental Appends, Sqoop-Hive Cluster Fix, Sqoop Hive Import and Sqoop List Tables/Database
This module explores Hadoop Distributed File System (HDFS), HDFS Architecture and Components and Case Study Analyzing Uber Datasets using Hadoop Framework
This module provides a knowledge about Distributed Processing MapReduce Framework, Distributed Processing in MapReduce, Case Study Flipkart Dodged WannaCry, Ransomwar, MapReduce Terminologies, Map Execution Phases, MapReduce Jobs, Building a MapReduce Program and finally Creating a New Project
This module presents the idea of Hive SQL Over Hadoop Map reduce, Hive Case study, Hive Architecture, Hive Meta Store, Hive DDL and DML, Hive Data types, File Format Types, Hive Data Serialization, Hive Optimization Partitioning Bucketing Skewing, Hive Analytics UDF and UDAF, Assisted Practice Working with Hive Quer Editor and conepts of Apache Pig and Components of Pig.
This module explains the topics of NoSQL, HBase Overview, HBase Architecture, HBase Data Model, Connecting to HBase and Assisted Practice Data Upload from HDFS to HBase
This model presents the concepts of data ingestion into Big data using an ETL, Data Ingestion Overview, Apache Kafka, Kafka Data Model, Apache Kafka Architecture, Apache Flume, Apache Flume Model and Components in Flume’s Architecture.
This model presents the python concepts like Modes of Python, Applications of Python, Variables in Python, Operators in Python, Control Statements in Python, Loop Statements in Python, List Operations, Swap Two Strings , Merge Two Dictionaries, Python Functions, Object-Oriented Programming in Python, Access Modifiers, Object - Oriented Programming Concepts and Modules in Python.
This module covers the topics like types of Big data, Challenges is in Traditional Data Solution, Data Processing in Big Data, Distributed Computing and Its Challenges, MapReduce, Apache Storm and Its Limitations and General Purpose Solution Apache Spark.
This module explains the Spark Components, Spark Architecture, Spark Cluster in Real World, Intoduction to PySpark Shell, Submitting PySpark Job, Spark Web UI and Deployment of PySpark Job.
This module covers Spark SQL Spark SQL Architecture, Spark - Context, User - defined Functions, User - defined Aggregate, Functions, Apache Spark DataFrames, Spark DataFrames – Catalyst Optimizer, Interoperating with RDDs, PySpark DataFrames, Spark - Hive Integration, Create DataFrame Using PySpark to Process Records and UDF with DataFrame.
This module presents Traditional Computing Methods and Its Drawbacks, Spark Streaming Introduction, Real Time Processing of Big Data, Data Processing Architectures, Spark Streaming, Introduction to DStreams, Checkpointing, State Operations, Windowing Operation, Spark Streaming Source and Apache Spark Streaming
This module provides the knowledge of the Spark Structured Streaming, Batch vs Streaming, Structured Streaming Architecture, Use Case Banking, Transactions, Structured Streaming APIs, Usecase Spark Structured Streaming and Working with Spark Strutured Application.
This module presents the idea about the Graphs, Use Cases of GraphX, Spark GraphX, GraphX Operators, Graph Parallel System, Algorithms in Spark, Pregel API and Graph Frames
Interested in gaining IT knowledge and enter into real world IT domain, switching carears in IT or applying for entry level positions
Big Data and Applications Certification.
Upon completing this cerification course you will: