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Conflict of Interest

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High Risk Vendors

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High Risk Distributors

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High Risk Guests and Attendees

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Big Data & Hadoop Module 1

Hadoop (Big Data) Ecosystem

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Motivation for Hadoop

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Different types of projects by Apache

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Role of projects in the Hadoop Ecosystem

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Key technology foundations required for Big Data

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Limitations and Solutions of existing Data Analytics Architecture

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Comparison of traditional data management systems with Big Data management systems

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Evaluate key framework requirements for Big Data analytics

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Hadoop Ecosystem & Hadoop 2.x core components

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Explain the relevance of real-time data

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Explain how to use big and real-time data as a Business planning tool

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Ghost employees

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Employee falsified time entry

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Background Checks

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Segregation of Duties

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Big Data & Hadoop Module 2

Building Blocks

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Quick tour of Java

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Quick tour of Linux commands

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Introduction to Cloudera VM/Cloudera Manager(Apache Ambari)/Download & usage instruction

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Ghost Vendoors

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Duplicate vendor transactions

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Vendor Spend Analysis

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Vendor Price Variations

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Big Data & Hadoop Module 3

Hadoop Cluster -Architecutre - Configuration files

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Hadoop Master-Slave Architecture

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The Hadoop Distributed File System - data storage

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Explain different types of cluster setups(Fully distributed/Pseudo etc)

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Hadoop Cluster setup - Installation

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Hadoop 2.x Cluster Architecture

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A Typical enterprise cluster – Hadoop Cluster Modes

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Big Data & Hadoop Module 4

Data Integration using Sqoop, Flume & Talend

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Integrating Hadoop into an existing Enterprise

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Loading Data from an RDBMS into HDFS by Using Sqoop

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Managing Real-Time Data Using Flume

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Accessing HDFS from Legacy Systems with FuseDFS and HttpFS

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Introduction to Talend (community system)

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Data loading to HDFS using Talend

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Ghost Customers

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Unfavorable contracts terms

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Repeated orders followed by returns

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Excessive customer comission payments

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Big Data & Hadoop Module 5

Data Analysis using PIG

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Introduction to Hadoop Data Analysis Tools

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Introduction to PIG - MapReduce Vs Pig, Pig Use Cases

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Pig Latin Program & Execution

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Use Pig to automate the design and implementation of MapReduce applications

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Data Analysis using PIG

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Big Data & Hadoop Module 6

Data Analysis using HIVE

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Introduction to Hive - Hive Vs. PIG - Hive Use Cases

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Discuss the Hive data storage principle

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Explain the File formats and Records formats supported by the Hive environment

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Perform operations with data in Hive

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Hive QL: Joining Tables, Dynamic Partitioning, Custom MapReduce Scripts

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Hive Script, Hive UDF

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Ghost Customers

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Unfavorable contracts terms

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Repeated orders followed by returns

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Excessive customer comission payments

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Big Data & Hadoop Module 7

Data Analysis using Impala

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Introduction to Impala & Architecture

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How Impala executes Queries and its importance

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Hive vs. PIG vs. Impala

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Extending impala with User Defined functions

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Improving impala Performance

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Big Data & Hadoop Module 8

NoSql Database - HBASE

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Introduction to NoSQL Databases and Hbase

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HBase v/s RDBMS, HBase Components, HBase Architecture

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HBase Cluster Deployment

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Ghost Customers

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Unfavorable contracts terms

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Repeated orders followed by returns

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Excessive customer comission payments

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Big Data & Hadoop Module 9

Hadoop - Other Analytics Tools

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Introduction to the role of R in Hadoop Ecosystem

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Introduction to Jasper Reports & creating reports by integrating with Hadoop

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Role of Kafka & Avro in real projects

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Big Data & Hadoop Module 10

Hadoop Core Components - HDFS & Map Reduce(YARN)

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HDFS Overview & Data storage in HDFS

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Get the data into Hadoop from local machine (Data Loading Techniques) - vice versa

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MapReduce Overview (Traditional way Vs. MapReduce way)

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HDFS Overview & Data storage in HDFS

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Concept of Mapper & Reducer

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Understanding MapReduce program skeleton

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Running MapReduce job in Command line/Eclipse

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Develop MapReduce Program in JAVA

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Develop MapReduce Program with the streaming API

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Test and debug a MapReduce program in the design time

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How Partitioners and Reducers Work Together

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Writing Customer Partitioners Data Input and Output

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Creating Custom Writable and Writable Comparable Implementations