Big Data Foundation: Enable Your Big Data Analytics Capabilities

Nowadays, everyone says: Data is the new oil. But it could be valuable if we can use it. As we know that now almost all activities collect the data. From doing exercise, paying bills, watching movies, buying groceries and other things. Can we imagine, how big the data which are collected from those activities? How can we get insight from those kinds of data?  This course will help you to understand the foundation to Big Data. Before you jump into further steps in big data, Elon Musk said that if we want to grow a big tree of knowledge, we must make sure that the tree has the strong roots. So, it’s a crucial step in building further capabilities for facing the Big Data Analytics Era. 

After completion of this program, participants will be able to:
* Understand the Hadoop Ecosystem
* Understand differentiation between Hive and Impala
* Understand differentiation between ETL and ELT Process
* Conduct DDL, DML and DCL in big data environment
* Conduct basic analytics in big data using Hive and Impala DML
* Conduct efficient ways in Hive and Impala Query

**NOTE**
Day 2 duration is 4 hours (half-day)

Certificate of completion (supplied by PasarTrainer)

Training Material

Quiz Result

* More on Hue
* How to use Hue to query Hive & Impala
* How to use Hue to manage query
* How to use Hue to manage HDFS files
* Intro to oozie job creator on Hue

Module 7. Introduction to Hue

A multiple-choice test to assess the participants' proficiency level prior to enrolling in the training program.

Pre-Test (10 Questions - Closed Book)

* Hive & Impala Database
* Hive & Impala Table
* Hive & Impala View
* Storing query results to HDFS File

This module explains an overview of DDL in Big Data.

Module 8. Data Definition Language (DDL)

* Common problems of local file systems
* Explain data management in the Hadoop file system
* Cloudera manager overview
* HDFS client operational
* Hadoop services overview

This module explains an overview of Cloudera & Hadoop Ecosystem.

Module 1. Cloudera & Hadoop Ecosystem

A multiple-choice test to assess the participants' proficiency level after enrolling in the training program.

Post-Test (10 Questions - Closed Book)

* More on Hive
* Hive architecture
* Basic security concept on Hive
* Hive VS RDBMS comparisons
* Explain about Hive data models
* Benefits for using Hive instead of RDBMS
* Hive Do's and Don'ts

This module explains an overview of Hive Architecture.

Module 2. Hive Architecture

* Overview and HiveQL structure
* Accessing Hive using Beeline, JDBC, ODBC

This module explains an overview of HiveQL & Clients.

Module 3. HiveQL & Clients

* More on Impala
* Impala architecture
* Basic security concept on Impala
* Impala VS RDBMS comparisons
* Explain about Impala data models
* Benefits for using Impala instead of RDBMS
* Impala Do’s and Don’ts

This module explains an overview of Impala Architecture.

Module 4. Impala Architecture

* Overview and ImpalaQL structure
* Accessing Impala using Impala Shell, JDBC and ODBC

This module explains an overview of ImpalaSQL & Clients.

Module 5. ImpalaSQL & Clients

* Intro to ETL/ELT Process
* ETL/ELT process overview
* ETL/ELT data preparation
