SQL NoSQL Big Data and Hadoop
Category: IT & SoftwareCategory: Personal DevelopmentCategory: Teaching & Education
Course Info
Overview
Develop a SQL NoSQL Big Data and Hadoop arsenal of skills including critical strategic, managerial, and leadership abilities with our expertly developed SQL NoSQL Big Data and Hadoop.
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Description
This SQL NoSQL Big Data and Hadoop course will teach you how to think critically and strategically about SQL NoSQL Big Data and Hadoop, as well as how to build and implement strategy. You’ll also discover fundamental SQL NoSQL Big Data and Hadoop ideas that will help you build the foundation you need to flourish in the workplace.This Learning Paths online SQL NoSQL Big Data and Hadoop course is for working people who want to improve their abilities and advance in their careers. The SQL NoSQL Big Data and Hadoop course is provided in an interactive virtual learning environment where you can study at your own comfort and convenience.
Who is this course for?
This certificate SQL NoSQL Big Data and Hadoop course is curated for individuals who want to improve their hard and soft skills. The interactive, guided approach to learning and the potential to build their worldwide network online will help you thrive. Moreover, working professionals in managerial and leadership roles in a variety of industries will benefit from the emphasis on the dynamics of leadership, influence, and strategy, as well as SQL NoSQL Big Data and Hadoop abilities. Those pursuing career advancement in the future will benefit from the skill to apply SQL NoSQL Big Data and Hadoop-derived abilities to current and future employment.
Requirements
This Learning Paths SQL NoSQL Big Data and Hadoop course will prepare you to make data-driven decisions that will give you a competitive edge. There are no formal requirements for this course. However smart gadgets and stable internet connection is required for a smooth learning journey.
Career Path
Earn a certificate of competence from the Learning Paths platform by learning all about SQL NoSQL Big Data and Hadoop. This SQL NoSQL Big Data and Hadoop course curriculum will benefit you at all stages of your career.
Certification
After successfully completing the SQL NoSQL Big Data and Hadoop course, you will get your PDF certificate for FREE! The hardcopy certificate will cost only £11.99 with free shipping inside the UK. For delivery outside the UK an additional shipping charge will be applied.
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 | ||
| Assignment | |||
| Assignment -SQL NoSQL Big Data and Hadoop | 00:00:00 | ||
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