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SQL NoSQL Big Data and Hadoop
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Overview
Grasp the science of SQL NoSQL Big Data and Hadoop and how it relates to launching a lucrative career. Prepare for future SQL NoSQL Big Data and Hadoop needs by looking beyond the ongoing SQL NoSQL Big Data and Hadoop impact with Discover Training’s up-to-date SQL NoSQL Big Data and Hadoop course .
Discover Training’s SQL NoSQL Big Data and Hadoop course gives you a solid foundation in SQL NoSQL Big Data and Hadoop in many settings of human development. With industry expert interviews, you’ll gain a greater understanding of SQL NoSQL Big Data and Hadoop‘s applications and limitations, as well as how it’s already been efficiently used in the field. Discover Training’s SQL NoSQL Big Data and Hadoop course will help you obtain facts and knowledge to strengthen your abilities on both standard SQL NoSQL Big Data and Hadoop techniques.
As you progress through the interactive modules of this online program, you will have a strong grasp of SQL NoSQL Big Data and Hadoop to identify new opportunities for innovation and drive digital growth within your organization. Enrol in the SQL NoSQL Big Data and Hadoop course today and leverage your knowledge tomorrow.
What Will Make You Stand Out?
On Completion of this SQL NoSQL Big Data and Hadoop online course, you’ll acquire:
- CPD QS Accredited Course.
- Upon Course Completion, Earn a Complimentary PDF and a hard copy Certificate to Showcase Your Enhanced Skills.
- Lifetime access.
- 24x7 Tutor Support.
- Complete the course at your own pace.
Description
Industry professionals developed the content of this online SQL NoSQL Big Data and Hadoop course, combining their expertise and in-depth knowledge. The curriculum was developed by Discover Training to assist you in growing in your current role by providing you with the necessary information and concepts. As you progress through the modules of this course, you’ll learn the fundamentals of SQL NoSQL Big Data and Hadoop and explore the essential concepts.
Who is this course for?
This SQL NoSQL Big Data and Hadoop course is inclusive and accessible to individuals from diverse backgrounds. It specifically caters to those with a keen interest in the relevant sectors. Join us to expand your knowledge and excel in your chosen field.
Requirements
No formal requirements are needed! Enrol effortlessly in this SQL NoSQL Big Data and Hadoop course today. All you need is a device with internet access, and you’re all set to embark on your learning journey. Enjoy the flexibility of completing the course at your own pace.
Certification
Upon successful completion of the SQL NoSQL Big Data and Hadoop course, learners can obtain both a PDF certificate and a Hard copy certificate for completely FREE. The Hard copy certificate is available for a nominal fee of £3.99, which covers the delivery charge within the United Kingdom. Additional delivery charges may apply for orders outside the United Kingdom.
Career Path
Unlock the Potential of SQL NoSQL Big Data and Hadoop and gain valuable insights into the evolving SQL NoSQL Big Data and Hadoop industry. Acquire in-demand skills that can be immediately applied to lucrative job opportunities.
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 | ||
Frequently Asked Questions
Yes, Discover Training provides accredited and CPD-certified courses, ensuring learners receive recognised qualifications that support career progression and professional compliance.
Anyone can enrol, including students, professionals, job seekers, career changers, and organisations. Most courses do not require previous experience, making them accessible to learners at all levels.
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You will have 14 days to revoke your Course purchase from your purchase date. Regrettably, refunds are not allowed after your purchase have been approved, and materials have been posted to the student’s dashboard or accessed.
Yes, learners receive a downloadable digital certificate upon successful completion, suitable for CPD records, CVs, and professional portfolios.
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Number of Units:
129 -
Access:
1 Year -
Duration:
22 hours, 33 minutes -
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