Big Data: SQL NoSQL Big Data and Hadoop

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Big Data: SQL NoSQL Big Data and Hadoop

Level: Intermediate
Modules: 131 Modules
Duration: 22 hours, 33 minutes
Students: 336

Overview

Uplift Your Career & Skill Up to Your Dream Job – Learning Simplified From Home!

Kickstart your career & boost your employability by helping you discover your skills, talents and interests with our special Big Data: SQL NoSQL Big Data and Hadoop Course. You’ll create a pathway to your ideal job as this course is designed to uplift your career in the relevant industry. It provides professional training that employers are looking for in today’s workplaces.

The Big Data: SQL NoSQL Big Data and Hadoop Course is one of the most prestigious training offered at StudyHub and is highly valued by employers for good reason. This Big Data: SQL NoSQL Big Data and Hadoop Course has been designed by industry experts to provide our learners with the best learning experience possible to increase their understanding of their chosen field.

This Big Data: SQL NoSQL Big Data and Hadoop Course, like every one of Study Hub’s courses, is meticulously developed and well researched. Every one of the topics is divided into elementary modules, allowing our students to grasp each lesson quickly.

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Certification

After studying the course materials of the Big Data: SQL NoSQL Big Data and Hadoop there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60.

Who is this course for?

This Big Data: SQL NoSQL Big Data and Hadoop course is ideal for

Students
Recent graduates
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Anyone interested in this topic
People already working in the relevant fields and want to polish their knowledge and skill.

Prerequisites

This Big Data: SQL NoSQL Big Data and Hadoop does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Big Data: SQL NoSQL Big Data and Hadoop was made by professionals and it is compatible with all PC’s, Mac’s, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection.

Career path

As this course comes with multiple courses included as bonus, you will be able to pursue multiple occupations. This Big Data: SQL NoSQL Big Data and Hadoop is a great way for you to gain multiple skills from the comfort of your home.

Course Curriculum

Section 01: Introduction
	Introduction	00:07:00
	Building a Data-driven Organization – Introduction	00:04:00
	Data Engineering	00:06:00
	Learning Environment & Course Material	00:04:00
	Movielens Dataset	00:03:00
Section 02: Relational Database Systems
	Introduction to Relational Databases	00:09:00
	SQL	00:05:00
	Movielens Relational Model	00:15:00
	Movielens Relational Model: Normalization vs Denormalization	00:16:00
	MySQL	00:05:00
	Movielens in MySQL: Database import	00:06:00
	OLTP in RDBMS: CRUD Applications	00:17:00
	Indexes	00:16:00
	Data Warehousing	00:15:00
	Analytical Processing	00:17:00
	Transaction Logs	00:06:00
	Relational Databases – Wrap Up	00:03:00
Section 03: Database Classification
	Distributed Databases	00:07:00
	CAP Theorem	00:10:00
	BASE	00:07:00
	Other Classifications	00:07:00
Section 04: Key-Value Store
	Introduction to KV Stores	00:02:00
	Redis	00:04:00
	Install Redis	00:07:00
	Time Complexity of Algorithm	00:05:00
	Data Structures in Redis : Key & String	00:20:00
	Data Structures in Redis II : Hash & List	00:18:00
	Data structures in Redis III : Set & Sorted Set	00:21:00
	Data structures in Redis IV : Geo & HyperLogLog	00:11:00
	Data structures in Redis V : Pubsub & Transaction	00:08:00
	Modelling Movielens in Redis	00:11:00
	Redis Example in Application	00:29:00
	KV Stores: Wrap Up	00:02:00
Section 05: Document-Oriented Databases
	Introduction to Document-Oriented Databases	00:05:00
	MongoDB	00:04:00
	MongoDB Installation	00:02:00
	Movielens in MongoDB	00:13:00
	Movielens in MongoDB: Normalization vs Denormalization	00:11:00
	Movielens in MongoDB: Implementation	00:10:00
	CRUD Operations in MongoDB	00:13:00
	Indexes	00:16:00
	MongoDB Aggregation Query – MapReduce function	00:09:00
	MongoDB Aggregation Query – Aggregation Framework	00:16:00
	Demo: MySQL vs MongoDB. Modeling with Spark	00:02:00
	Document Stores: Wrap Up	00:03:00
Section 06: Search Engines
	Introduction to Search Engine Stores	00:05:00
	Elasticsearch	00:09:00
	Basic Terms Concepts and Description	00:13:00
	Movielens in Elastisearch	00:12:00
	CRUD in Elasticsearch	00:15:00
	Search Queries in Elasticsearch	00:23:00
	Aggregation Queries in Elasticsearch	00:23:00
	The Elastic Stack (ELK)	00:12:00
	Use case: UFO Sighting in ElasticSearch	00:29:00
	Search Engines: Wrap Up	00:04:00
Section 07: Wide Column Store
	Introduction to Columnar databases	00:06:00
	HBase	00:07:00
	HBase Architecture	00:09:00
	HBase Installation	00:09:00
	Apache Zookeeper	00:06:00
	Movielens Data in HBase	00:17:00
	Performing CRUD in HBase	00:24:00
	SQL on HBase – Apache Phoenix	00:14:00
	SQL on HBase – Apache Phoenix – Movielens	00:10:00
	Demo : GeoLife GPS Trajectories	00:02:00
	Wide Column Store: Wrap Up	00:04:00
Section 08: Time Series Databases
	Introduction to Time Series	00:09:00
	InfluxDB	00:03:00
	InfluxDB Installation	00:07:00
	InfluxDB Data Model	00:07:00
	Data manipulation in InfluxDB	00:17:00
	TICK Stack I	00:12:00
	TICK Stack II	00:23:00
	Time Series Databases: Wrap Up	00:04:00
Section 09: Graph Databases
	Introduction to Graph Databases	00:05:00
	Modelling in Graph	00:14:00
	Modelling Movielens as a Graph	00:10:00
	Neo4J	00:04:00
	Neo4J installation	00:08:00
	Cypher	00:12:00
	Cypher II	00:19:00
	Movielens in Neo4J: Data Import	00:17:00
	Movielens in Neo4J: Spring Application	00:12:00
	Data Analysis in Graph Databases	00:05:00
	Examples of Graph Algorithms in Neo4J	00:18:00
	Graph Databases: Wrap Up	00:07:00
Section 10: Hadoop Platform
	Introduction to Big Data With Apache Hadoop	00:06:00
	Big Data Storage in Hadoop (HDFS)	00:16:00
	Big Data Processing : YARN	00:11:00
	Installation	00:13:00
	Data Processing in Hadoop (MapReduce)	00:14:00
	Examples in MapReduce	00:25:00
	Data Processing in Hadoop (Pig)	00:12:00
	Examples in Pig	00:21:00
	Data Processing in Hadoop (Spark)	00:23:00
	Examples in Spark	00:23:00
	Data Analytics with Apache Spark	00:09:00
	Data Compression	00:06:00
	Data serialization and storage formats	00:20:00
	Hadoop: Wrap Up	00:07:00
Section 11: Big Data SQL Engines
	Introduction Big Data SQL Engines	00:03:00
	Apache Hive	00:10:00
	Apache Hive : Demonstration	00:20:00
	MPP SQL-on-Hadoop: Introduction	00:03:00
	Impala	00:06:00
	Impala : Demonstration	00:18:00
	PrestoDB	00:13:00
	PrestoDB : Demonstration	00:14:00
	SQL-on-Hadoop: Wrap Up	00:02:00
Section 12: Distributed Commit Log
	Data Architectures	00:05:00
	Introduction to Distributed Commit Logs	00:07:00
	Apache Kafka	00:03:00
	Confluent Platform Installation	00:10:00
	Data Modeling in Kafka I	00:13:00
	Data Modeling in Kafka II	00:15:00
	Data Generation for Testing	00:09:00
	Use case: Toll fee Collection	00:04:00
	Stream processing	00:11:00
	Stream Processing II with Stream + Connect APIs	00:19:00
	Example: Kafka Streams	00:15:00
	KSQL : Streaming Processing in SQL	00:04:00
	KSQL: Example	00:14:00
	Demonstration: NYC Taxi and Fares	00:01:00
	Streaming: Wrap Up	00:02:00
Section 13: Summary
	Database Polyglot	00:04:00
	Extending your knowledge	00:08:00
	Data Visualization	00:11:00
	Building a Data-driven Organization – Conclusion	00:07:00
	Conclusion	00:03:00
Resources
	Resources – Big Data: SQL NoSQL Big Data and Hadoop	00:00:00
Assignment
	Assignment – Big Data: SQL NoSQL Big Data and Hadoop	00:00:00