BIG DATA + HADOOP ECOSYSTEM (DATA SCIENCE) COMPLETE COURSE IN LAHORE

Pny offers the outstanding Big +Hadoop Ecosystem (Data Science) Complete Course in Arfa Technology Lahore. Learning Objectives: In this module, you will understand what Big Data is, the limitations of the traditional solutions for Big Data problems, how Hadoop solves those Big Data problems, Hadoop Ecosystem, Hadoop Architecture, HDFS, Anatomy of File Read and Write & how MapReduce works. Topics: •Introduction to Big Data & Big Data Challenges •Limitations & Solutions of Big Data Architecture •Hadoop & its Features •Hadoop Ecosystem •Hadoop Components •Hadoop Storage: HDFS (Hadoop Distributed File System) •Hadoop Processing: MapReduce Framework •Different Hadoop Distributions Module 2: Installation Setup and Data Ingestion Learning Objectives: In this module, you will learn Data Loading Techniques using Sqoop & Flume, and how to import data from a relational database into HDFS. Topics: •SQOOP Import: Import data from a table in a relational database into HDFS •Free Form Query Imports: Import the results of a query from a relational database into HDFS •Importing Data into Hive: Import a table from a relational database into a new or existing Hive table •SQOOP: Insert or update data from HDFS into a table in a relational database •Flume Agent: Given a Flume configuration file, start a Flume agent Module 3: Data Transformation Learning Objectives: In this module, you will learn Data Transformation Techniques using PIG. •Write and execute a Pig script •Load data into a Pig relation without a schema •Load data into a Pig relation with a schema •Load data from a Hive table into a Pig relation •Use Pig to transform data into a specified format •Transform data to match a given Hive schema •Group the data of one or more Pig relations •Use Pig to remove records with null values from a relation •Store the data from a Pig relation into a folder in HDFS •Store the data from a Pig relation into a Hive table •Sort the output of a Pig relation •Remove the duplicate tuples of a Pig relation •Join two datasets using Pig •Perform a replicated join using Pig Module 4: Data Analysis Learning Objectives: In this module, you will learn Data Analysis Techniques using HIVE, and how to import data from a file into HDFS. •Write and execute a Hive query •Define a Hive-managed table •Define a Hive external table •Define a partitioned Hive table •Define a Hive table from a select query •Specify the delimiter of a Hive table •Load data into a Hive table from a local directory •Load data into a Hive table from an HDFS directory •Load data into a Hive table as the result of a query •Update a row in a Hive table •Delete a row from a Hive table •Insert a new row into a Hive table •Join two Hive tables Module 5: Apache Spark and ETL Tools Learning Objectives: In this module, you will learn about Apache Spark, and some conventional ETL tools like Informatica and Talend. •Spark – Architecture, Execution and Related Concepts •Functional Programming in Spark •Running a Spark Application •Introduction to ETL and ETL Tools •Basics of Informatica •Designing first job in Informatica •Various transformation functions of Informatica •Introduction to Talend Module 6: Final Project Learning Objectives: In this module, you will work on a project that will help you summarize all the topics covered in training and will help you in achieving Hadoop Certified Developer certification. Views: 2