Overview
This comprehensive course on SQL NoSQL Big Data and Hadoop will deepen your understanding on this topic.
After successful completion of this course you can acquire the required skills in this sector. This SQL NoSQL Big Data and Hadoop comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market.
So enrol in this course today to fast track your career ladder.
How will I get my certificate?
At the end of the course there will be an online written test, which you can take either during or after the course. After successfully completing the test you will be able to order your certificate, these are included in the price.
Who is This course for?
There is no experience or previous qualifications required for enrolment on this SQL NoSQL Big Data and Hadoop. It is available to all students, of all academic backgrounds.
Requirements
Our SQL NoSQL Big Data and Hadoop is fully compatible with PC’s, Mac’s, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G.
There is no time limit for completing this course, it can be studied in your own time at your own pace.
Career Path
Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to—
- Open doors of opportunities
- Increase your adaptability
- Keep you relevant
- Boost confidence
And much more!
Course Curriculum
- 15 sections
- 131 lectures
- 22 hours, 34 minutes total length
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Introduction 00:07:00 -
Building a Data-driven Organization – Introduction 00:04:00
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Data Engineering 00:06:00
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Learning Environment & Course Material 00:04:00
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Movielens Dataset 00:03:00
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Introduction to Relational Databases 00:09:00
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SQL 00:05:00
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Movielens Relational Model 00:15:00
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Movielens Relational Model: Normalization vs Denormalization 00:16:00
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MySQL 00:05:00
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Movielens in MySQL: Database import 00:06:00
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OLTP in RDBMS: CRUD Applications 00:17:00
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Indexes 00:16:00
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Data Warehousing 00:15:00
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Analytical Processing 00:17:00
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Transaction Logs 00:06:00
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Relational Databases – Wrap Up 00:03:00
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Distributed Databases 00:07:00
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CAP Theorem 00:10:00
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BASE 00:07:00
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Other Classifications 00:07:00
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Introduction to KV Stores 00:02:00
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Redis 00:04:00
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Install Redis 00:07:00
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Time Complexity of Algorithm 00:05:00
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Data Structures in Redis : Key & String 00:20:00
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Data Structures in Redis II : Hash & List 00:18:00
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Data structures in Redis III : Set & Sorted Set 00:21:00
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Data structures in Redis IV : Geo & HyperLogLog 00:11:00
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Data structures in Redis V : Pubsub & Transaction 00:08:00
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Modelling Movielens in Redis 00:11:00
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Redis Example in Application 00:29:00
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KV Stores: Wrap Up 00:02:00
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Introduction to Document-Oriented Databases 00:05:00
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MongoDB 00:04:00
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MongoDB Installation 00:02:00
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Movielens in MongoDB 00:13:00
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Movielens in MongoDB: Normalization vs Denormalization 00:11:00
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Movielens in MongoDB: Implementation 00:10:00
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CRUD Operations in MongoDB 00:13:00
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Indexes 00:16:00
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MongoDB Aggregation Query – MapReduce function 00:09:00
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MongoDB Aggregation Query – Aggregation Framework 00:16:00
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Demo: MySQL vs MongoDB. Modeling with Spark 00:02:00
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Document Stores: Wrap Up 00:03:00
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Introduction to Search Engine Stores 00:05:00
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Elasticsearch 00:09:00
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Basic Terms Concepts and Description 00:13:00
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Movielens in Elastisearch 00:12:00
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CRUD in Elasticsearch 00:15:00
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Search Queries in Elasticsearch 00:23:00
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Aggregation Queries in Elasticsearch 00:23:00
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The Elastic Stack (ELK) 00:12:00
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Use case: UFO Sighting in ElasticSearch 00:29:00
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Search Engines: Wrap Up 00:04:00
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Introduction to Columnar databases 00:06:00
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HBase 00:07:00
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HBase Architecture 00:09:00
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HBase Installation 00:09:00
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Apache Zookeeper 00:06:00
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Movielens Data in HBase 00:17:00
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Performing CRUD in HBase 00:24:00
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SQL on HBase – Apache Phoenix 00:14:00
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SQL on HBase – Apache Phoenix – Movielens 00:10:00
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Demo : GeoLife GPS Trajectories 00:02:00
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Wide Column Store: Wrap Up 00:05:00
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Introduction to Time Series 00:09:00
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InfluxDB 00:03:00
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InfluxDB Installation 00:07:00
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InfluxDB Data Model 00:07:00
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Data manipulation in InfluxDB 00:17:00
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TICK Stack I 00:12:00
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TICK Stack II 00:23:00
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Time Series Databases: Wrap Up 00:04:00
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Introduction to Graph Databases 00:05:00
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Modelling in Graph 00:14:00
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Modelling Movielens as a Graph 00:10:00
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Neo4J 00:04:00
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Neo4J installation 00:08:00
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Cypher 00:12:00
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Cypher II 00:19:00
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Movielens in Neo4J: Data Import 00:17:00
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Movielens in Neo4J: Spring Application 00:12:00
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Data Analysis in Graph Databases 00:05:00
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Examples of Graph Algorithms in Neo4J 00:18:00
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Graph Databases: Wrap Up 00:07:00
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Introduction to Big Data With Apache Hadoop 00:06:00
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Big Data Storage in Hadoop (HDFS) 00:16:00
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Big Data Processing : YARN 00:11:00
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Installation 00:13:00
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Data Processing in Hadoop (MapReduce) 00:14:00
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Examples in MapReduce 00:25:00
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Data Processing in Hadoop (Pig) 00:12:00
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Examples in Pig 00:21:00
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Data Processing in Hadoop (Spark) 00:23:00
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Examples in Spark 00:23:00
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Data Analytics with Apache Spark 00:09:00
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Data Compression 00:06:00
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Data serialization and storage formats 00:20:00
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Hadoop: Wrap Up 00:07:00
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Introduction Big Data SQL Engines 00:03:00
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Apache Hive 00:10:00
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Apache Hive : Demonstration 00:20:00
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MPP SQL-on-Hadoop: Introduction 00:03:00
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Impala 00:06:00
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Impala : Demonstration 00:18:00
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PrestoDB 00:13:00
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PrestoDB : Demonstration 00:14:00
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SQL-on-Hadoop: Wrap Up 00:02:00
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Data Architectures 00:05:00
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Introduction to Distributed Commit Logs 00:07:00
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Apache Kafka 00:03:00
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Confluent Platform Installation 00:10:00
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Data Modeling in Kafka I 00:13:00
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Data Modeling in Kafka II 00:15:00
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Data Generation for Testing 00:09:00
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Use case: Toll fee Collection 00:04:00
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Stream processing 00:11:00
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Stream Processing II with Stream + Connect APIs 00:19:00
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Example: Kafka Streams 00:15:00
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KSQL : Streaming Processing in SQL 00:04:00
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KSQL: Example 00:14:00
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Demonstration: NYC Taxi and Fares 00:01:00
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Streaming: Wrap Up 00:02:00
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Database Polyglot 00:04:00
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Extending your knowledge 00:08:00
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Data Visualization 00:11:00
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Building a Data-driven Organization – Conclusion 00:07:00
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Conclusion 00:03:00
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Assignment -SQL NoSQL Big Data and Hadoop
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Claim Your Certificate
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This course includes:
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Duration:22 hours, 34 minutes
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Access:1 year access
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Units:131
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Level:
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CPD Points:10
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Certificate:Yes
