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Register on the SQL NoSQL Big Data and Hadoop today and build the experience, skills and knowledge you need to enhance your professional development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career. The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials. Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get a digital certificate as a proof of your course completion. The SQL NoSQL Big Data and Hadoop is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablet, and smartphones. The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly! What You Get With The SQL NoSQL Big Data and Hadoop Receive a e-certificate upon successful completion of the course Get taught by experienced, professional instructors Study at a time and pace that suits your learning style Get instant feedback on assessments 24/7 help and advice via email or live chat Get full tutor support on weekdays (Monday to Friday) Course Design The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace. You are taught through a combination of Video lessons Online study materials Certification Upon successful completion of the course, you will be able to obtain your course completion e-certificate free of cost. Print copy by post is also available at an additional cost of £9.99 and PDF Certificate at £4.99. Who Is This Course For: The course is ideal for those who already work in this sector or are an aspiring professional. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge. Requirements: The online training is open to all students and has no formal entry requirements. To study the SQL NoSQL Big Data and Hadoop, all your need is a passion for learning, a good understanding of English, numeracy, and IT skills. You must also be over the age of 16. Course Content 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 Resources Resources - SQL NoSQL Big Data And Hadoop 00:00:00

Get to grips with Docker, containers versus images, and more by learning through a hands-on approach

This course will teach you everything from scratch right from simple setups to complex solutions. If you want to master SSL and HTTPS in-depth, this course is for you! No prior knowledge of computer networks, encryption, or configuring web servers is required.

This course is for you if you have no prior coding experience. It is designed to take you through the core Java concepts with the help of practical examples and coding exercises. A course ideal for testing professionals transitioning to DevOps or Automation.

Course Overview The High Availability for the LAMP Stack Level 2 course is an in-depth training course, designed to provide learners with the practical skills and knowledge to build and deploy a highly available LAMP stack. Through step-by-step guidance, you will learn how to eliminate single points of failure and increase uptime for their Linux, Apache, MySQL, & PHP-based web sites and apps. This practical training course is ideal for those who already have some experience working at the Linux command line. You will learn everything you need to know to handle unexpected surges of traffic, scale without downtime, and survive unexpected points of failure. The concepts and techniques introduced in this course can be applied in a variety of situations, equipping you with in-demand industry knowledge.  Enrol today and learn to ensure service availability for Linux, Apache, and more. This best selling High Availability for the LAMP Stack Level 2 has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth High Availability for the LAMP Stack Level 2 is suitable for anyone who wants to build their professional skill set and improve their expert knowledge. The High Availability for the LAMP Stack Level 2 is CPD-accredited, so you can be confident you're completing a quality training course will boost your CV and enhance your career potential. The High Availability for the LAMP Stack Level 2 is made up of several information-packed modules which break down each topic into bite-sized chunks to ensure you understand and retain everything you learn. After successfully completing the High Availability for the LAMP Stack Level 2, you will be awarded a certificate of completion as proof of your new skills. If you are looking to pursue a new career and want to build your professional skills to excel in your chosen field, the certificate of completion from the High Availability for the LAMP Stack Level 2 will help you stand out from the crowd. You can also validate your certification on our website. We know that you are busy and that time is precious, so we have designed the High Availability for the LAMP Stack Level 2 to be completed at your own pace, whether that's part-time or full-time. Get full course access upon registration and access the course materials from anywhere in the world, at any time, from any internet-enabled device.  Our experienced tutors are here to support you through the entire learning process and answer any queries you may have via email.

Do you want to learn about Linux, but don't know where to start? Then you are in the right place. Take your first steps with this course. In this course, you will learn Linux installation, configuration, the Linux command line, administration, shell scripting, and much more. It is specially designed for absolute beginners with no prior experience in Linux.

Do you want to learn basic Linux system administration using real-world applied learning? Do you want to learn how to install and configure a Linux server? Do you prefer learning using hands-on as opposed to just a lecture and quiz? If you have answered yes to these questions, then you have chosen the right course.

Overview This comprehensive course on Building Big Data Pipelines with PySpark MongoDB and Bokeh will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Building Big Data Pipelines with PySpark MongoDB and Bokeh 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? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this Building Big Data Pipelines with PySpark MongoDB and Bokeh. It is available to all students, of all academic backgrounds. Requirements Our Building Big Data Pipelines with PySpark MongoDB and Bokeh 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 7 sections • 25 lectures • 05:04:00 total length •Introduction: 00:10:00 •Python Installation: 00:03:00 •Installing Third Party Libraries: 00:03:00 •Installing Apache Spark: 00:12:00 •Installing Java (Optional): 00:05:00 •Testing Apache Spark Installation: 00:06:00 •Installing MongoDB: 00:04:00 •Installing NoSQL Booster for MongoDB: 00:07:00 •Integrating PySpark with Jupyter Notebook: 00:05:00 •Data Extraction: 00:19:00 •Data Transformation: 00:15:00 •Loading Data into MongoDB: 00:13:00 •Data Pre-processing: 00:19:00 •Building the Predictive Model: 00:12:00 •Creating the Prediction Dataset: 00:08:00 •Loading the Data Sources from MongoDB: 00:17:00 •Creating a Map Plot: 00:33:00 •Creating a Bar Chart: 00:09:00 •Creating a Magnitude Plot: 00:15:00 •Creating a Grid Plot: 00:09:00 •Installing Visual Studio Code: 00:05:00 •Creating the PySpark ETL Script: 00:24:00 •Creating the Machine Learning Script: 00:30:00 •Creating the Dashboard Server: 00:21:00 •Source Code and Notebook: 00:00:00

This course takes you from a beginner to an expert level in Ansible and also prepares you for the Red Hat Certification exam. You'll become well-versed with Ubuntu, CentOS, and a little aware of Raspberry PI to manage Linux's multiple distributions using Ansible.