SQL, NoSQL, Big Data and Hadoop
4.4 (74 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
682 students enrolled

SQL, NoSQL, Big Data and Hadoop

A comprehensive journey through the world of database and data engineering concepts - from SQL, NoSQL to Hadoop
Bestseller
4.4 (74 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
682 students enrolled
Created by Michael Enudi
Last updated 1/2020
English
Current price: $13.99 Original price: $19.99 Discount: 30% off
5 hours left at this price!
30-Day Money-Back Guarantee
This course includes
  • 22 hours on-demand video
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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What you'll learn
  • Build an intuition from RDBMS system through NoSQL to the Big Data on the Cloud and Hadoop platform
  • Understand various distributed database classifications
  • Understand when and how to use Redis or Key-Value Stores
  • Understand when and how to use MongoDB or Document-oriented databases
  • Understand and use HBase as a Wide-Columnar Store
  • Understand and use Time series database (InfluxDB)
  • Understand and use Elasticsearch as a search engine
  • Understand and use Neo4J as a Graph Database Management System
  • Understand large scale distributed data storage and processing in Hadoop
  • Understand when and how to use and build Streaming architecture with Apache Kafka
  • Use Apache Hive and Understand where to use it in respect to big data platforms
  • Understand a number of SQL-on-Hadoop Engines and how they work
  • Understand how to use data engineering capabilities to enable a data-driven organization
Course content
Expand all 129 lectures 22:06:39
+ Relational Database Systems
12 lectures 02:08:41
SQL
04:47
Movielens Relational Model
14:52
Movielens Relational Model: Normalization vs Denormalization
15:33
MySQL
05:06
Movielens in MySQL: Database import
05:42
OLTP in RDBMS: CRUD Applications
17:05
Indexes
15:34
Data Warehousing
15:27
Analytical Processing
16:36
Transaction Logs
06:19
Relational Databases - Wrap Up
03:04
+ Database Classification
4 lectures 31:33
Distributed Databases
07:25
CAP Theorem
09:54
BASE
07:17
Other Classification
06:57
+ Key-Value Store
12 lectures 02:17:51
Introduction to KV Stores
02:21
Redis
03:57
Install Redis
07:07
Time Complexity of Algorithm
04:39
Data Structures in Redis : Key & String
20:16
Data Structures in Redis II : Hash & List
18:14
Data structures in Redis III : Set & Sorted Set
20:34
Data structures in Redis IV : Geo & HyperLogLog
10:33
Data structures in Redis V : Pubsub & Transaction
07:50
Modelling Movielens in Redis
11:23
Redis Example in Application
28:54
KV Stores: Wrap Up
02:03
+ Document-Oriented Databases
12 lectures 01:42:31
Introduction to Document-Oriented Databases
04:33
MongoDB
03:47
MongoDB installation
01:30
Movielens in MongoDB
13:12
Movielens in MongoDB: Normalization vs Denormalization
11:19
Movielens in MongoDB: Implementation
10:00
CRUD Operations in MongoDB
12:46
Indexes
15:30
MongoDB Aggregation Query - MapReduce function
09:19
MongoDB Aggregation Query - Aggregation Framework
15:39
Demo: MySQL vs MongoDB. Modeling with Spark
01:49
Document Stores: Wrap Up
03:07
+ Search Engine
10 lectures 02:14:52
Introduction to Search Engine Stores
05:12
Elasticsearch
08:34
Basic Terms Concepts and Description
12:48
Movielens in Elastisearch
11:41
CRUD in Elasticsearch
15:10
Search Queries in Elasticsearch
23:00
Aggregation Queries in Elasticsearch
14:08
The Elastic Stack (ELK)
11:44
Use case: UFO Sighting in ElasticSearch
28:47
Search Engines: Wrap Up
03:48
+ Wide Column Store
11 lectures 01:50:19
Introduction to Columnar databases
06:29
HBase
06:53
HBase Architecture
08:58
HBase Installation
08:46
Apache Zookeeper
06:27
Movielens Data in HBase
18:06
Performing CRUD in HBase
24:20
SQL on HBase - Apache Phoenix
13:43
SQL on HBase - Apache Phoenix - Movielens
10:08
Demo : GeoLife GPS Trajectories
01:46
Wide Column Store: Wrap Up
04:43
+ Time Series Databases
8 lectures 01:21:18
Introduction to Time Series
09:26
InfluxDB
02:50
InfluxDB Installation
06:34
InfluxDB Data Model
07:27
Data manipulation in InfluxDB
16:36
TICK Stack I
11:46
TICK Stack II
22:56
Time Series Databases: Wrap Up
03:43
+ Graph Databases
12 lectures 02:11:17
Introduction to Graph Databases.
05:00
Modelling in Graph
13:38
Modelling Movielens as a Graph
09:59
Neo4J
03:31
Neo4J installation
08:27
Cypher
12:20
Cypher II
19:08
Movielens in Neo4J: Data Import
17:16
Movielens in Neo4J: Spring Application
11:33
Data Analysis in Graph Databases
05:10
Examples of Graph Algorithms in Neo4J
18:19
Graph Databases: Wrap Up
06:56
+ Hadoop Platform
14 lectures 03:10:44
Introduction to Big Data With Apache Hadoop
06:22
Big Data Storage in Hadoop (HDFS)
15:46
Big Data Processing : YARN
11:01
Installation
12:40
Data Processing in Hadoop (MapReduce)
14:01
Examples in MapReduce
24:51
Data Processing in Hadoop (Pig)
11:45
Examples in Pig
21:18
Data Processing in Hadoop (Spark)
08:48
Examples in Spark
22:36
Data Analytics with Apache Spark
08:59
Data Compression
05:41
Data serialization and storage formats
19:50
Hadoop: Wrap Up
07:06
Requirements
  • No strict requirement but knowledge of relational database will be helpful.
  • A Windows, Linux or Mac Machine to set up a lab
  • Any Hadoop Vendor Sandbox like Cloudera Quickstart or HDP VM (Hadoop)
Description

A comprehensive look at the wide landscape of database systems and how to make a good choice in your next project

The first time we ask or answer any question regarding databases is when building an application. The next is either when our choice of database becomes a bottleneck or when we need to do large-scale data analytics.

This course covers almost all classes of databases or data storage platform there are and when to consider using them. It is a great journey through databases that will be great for software developers, big data engineers, data analysts as well as decision makers. It is not an in-depth look into each of the databases but promises to get you up and running with your first project for each class.

In this course, we are going to cover 

  • Relational Database Systems, their features, use cases and limitations

  • Why NoSQL?

  • CAP Theorem

  • Key-Value store and their use cases

  • Document-oriented databases and their use cases

  • Wide-columnar store and their use cases

  • Time-series databases and their use cases

  • Search Engines and their use cases

  • Graph databases and their use cases

  • Distributed Logs and real time streaming systems

  • Hadoop and its use cases

  • SQL-on-Hadoop tools and their use cases

  • How to make informed decisions in building a good data storage platform


What is the target audience?

  • Chief data officers

  • Application developer

  • Data analyst

  • Data architects

  • Data engineers

  • Students

  • Anyone who wants to understand Hadoop from a database perspective.


What this course does not cover?

This course does not access any of the databases from the administrative perspective. So we don't cover administrative tasks like security, backup, recovery, migration and the likes.
Very in-depth features in the specific databases in discussion. An example is that we will not go into the different database engines for MySQL or how to write a stored procedures. 


What are the requirements?
The lab for this course can be carried out in any machine (Microsoft Windows, Linux, Mac OX). 
However, the training on HBase or Hadoop will require you to have a hadoop environment. The suggestion for this will be to to use a pre-installed sandbox, a cloud offering or install your own custom sandbox.


What do I need to know to get the best out of this course?
This course does not assume any knowledge of NoSQL or data engineering.
However a little knowledge of RDBMS (even Microsoft Access) is enough to get you into the best position for this course.

Who this course is for:
  • Chief Data Officers
  • IT Decision Makers
  • Database Architects
  • Software Developers
  • Big data Engineers
  • Anyone who wants to understand the where each NoSQL class of database best fits.
  • Anyone who is curious about NoSQL or Big Data Systems