course-img

SQL NoSQL Big Data and Hadoop

£279 £39
Take This Course

Overview:

Welcome to "SQL, NoSQL, Big Data, and Hadoop!" This comprehensive course is designed to provide you with a thorough understanding of various data storage and processing technologies, including SQL, NoSQL, Big Data, and Hadoop. In today's data-driven world, it's essential to be familiar with a range of data technologies to handle diverse data types and volumes effectively. In this course, you'll learn how to work with relational and non-relational databases, manage big data, and utilize Hadoop for distributed data processing.
  • Interactive video lectures by industry experts
  • Instant e-certificate and hard copy dispatch by next working day
  • Fully online, interactive course with Professional voice-over
  • Developed by qualified first aid professionals
  • Self paced learning and laptop, tablet, smartphone friendly
  • 24/7 Learning Assistance
  • Discounts on bulk purchases

Main Course Features:

  • Comprehensive coverage of SQL fundamentals for relational database management
  • Exploration of NoSQL databases such as MongoDB and Cassandra for handling unstructured data
  • Introduction to Big Data concepts and technologies, including Hadoop and MapReduce
  • Hands-on projects and exercises for practical application of SQL, NoSQL, and Big Data concepts
  • Implementation of data processing workflows using Hadoop ecosystem tools like Hive and Pig
  • Real-world case studies and examples demonstrating the application of SQL, NoSQL, and Hadoop
  • Access to datasets and resources for practicing SQL and Big Data processing
  • Supportive online community for collaboration and assistance throughout the course

Who Should Take This Course:

  • Data engineers and analysts seeking to expand their knowledge of data storage and processing technologies
  • Software developers interested in understanding how different data technologies work together in modern applications
  • Business intelligence professionals aiming to leverage Big Data and Hadoop for data analysis and insights
  • Students and professionals looking to enhance their skills in SQL, NoSQL, and Big Data technologies

Learning Outcomes:

  • Master SQL fundamentals for relational database management and querying
  • Understand the principles and use cases of NoSQL databases for handling diverse data types
  • Gain insights into Big Data concepts and technologies, including Hadoop and MapReduce
  • Learn how to manage and process large-scale data using Hadoop ecosystem tools
  • Develop practical skills through hands-on projects and exercises in SQL, NoSQL, and Hadoop
  • Build a portfolio of projects showcasing proficiency in SQL, NoSQL, and Big Data processing
  • Apply data storage and processing techniques to real-world scenarios effectively
  • Stay updated with the latest advancements and best practices in SQL, NoSQL, Big Data, and Hadoop technologies.

Certification

Once you’ve successfully completed your course, you will immediately be sent a digital certificate. All of our courses are fully accredited, providing you with up-to-date skills and knowledge and helping you to become more competent and effective in your chosen field. Our certifications have no expiry dates, although we do recommend that you renew them every 12 months.

Assessment

At the end of the Course, there will be an online assessment, which you will need to pass to complete the course. Answers are marked instantly and automatically, allowing you to know straight away whether you have passed. If you haven’t, there’s no limit on the number of times you can take the final exam. All this is included in the one-time fee you paid for the course itself.

We guarantee that all our online courses will meet or exceed your expectations. If you are not fully satisfied with a course - for any reason at all - simply request a full refund. We guarantee no hassles. That's our promise to you.

Go ahead and order with confidence!

money_back

Easy to Access
Let's Navigate Together

Course Curriculum

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