In our comprehensive MongoDB training program, we explore MongoDB in complete detail. We start by the basics, explaining what a database is, and where and how it can be used. Later on we guide you in installing the MongoDB software on your system and give you a basic idea of the environment that you would be working on. The software works on both Windows and Ubuntu, and both the methods are covered in the curriculum. By the end of the course, you will be able to create your own database using MongoDB with extreme ease and convenience.
By the end of 2020, noSQL will constitute of a whopping $4.2 billion market worldwide , with with a compounded annual growth rate of 35.1% in the 6 years between 2014 and 2020. This is due to the increasing popularity of cloud computing in the market, considered to be the technology of the future.
The course has been planned keeping even the newcomer in mind. The concepts are explained giving suitable examples which makes understanding a lot easier. By the end of this course, you will easily be able to create a noSQL database using MongoDB, in accordance with he requirements of the corporate world.
At the end of the course, you will be given a project that would apply all the concepts that you learn. This is for better understanding and visualising things in a practical manner. Online study materials are provided for reference as well. There are regular mock tests for the students, in order to gauge their progress in a much better manner.
Concepts of Data Modelling
To become adept at creating databases using MongoDB architecture
Hadoop and MongoDB integration
This course requires no pre-requisites, and everything will be started from scratch.
MongoDB is relevant because it is getting huge recognition thanks to-
Ease of work which boosts productivity.
Presence of schema barrier, which makes the developer focus on building applications rather than databases.
Widespread support for most high level languages.
Introduction to design, architecture and the installation
MongoDB base concepts and categories of databases
NoSQL and its importance in modern day computing
RDBMS and its advantages
NoSQL database and its various types
Contrasts between noSQL and SQL
Acid and Base property
Implementation of noSQL and CAP Theory
Introduction to MongoDB
MongoDB server designing, database designing and tools to be used.
Collection, Keys, Values and Documents in MongoDB
Overview of JSON and BSON documents and their uses in MongoDB
Various methods of installing MongoDB based on the operating system i.e. Windows, MacOS and Linux.
Setting up the MongoDB environment
MongoDB package and the use of various tools available in the package Introductory Project
Crud Operations in MongoDB
CRUD operations in MongoDB, their syntax and queries and their usage in the MongoDB environment.
MongoDB Development and Production Architecture
Introduction to CRUD in MongoDB
Concepts of CRUD and various concerns in CRUD including read and write operations
Concepts of Concern Levels and Journalling
MongoDB Cursor, Optimisation of queries and behaviour of queries
Distributed Read & Write Queries
Datatypes in MongoDB and Syntax and Queries of CRUD in MongoDB platform
Schema Design and Modelling of Data using MongoDB
By the end of this module we will be familiar with the concepts of Data Modelling, and learn in depth on how to approach the various challenges that we face in Data Modelling using MongoDB. We also have a look at model structure and a lot of other things.
Data Modelling Introduction- Concepts and Types
Need of MongoDB for data modelling
Approaches to data modelling
RDBMS and amp - The Similarities
Data Model in MongoDb
Embedding and amp in MongoDB data model
Linking challenges in MongoDB for data modelling
Examples for Data Modelling and observed patterns.
Model Relationships between Documents in MongoDB environment:
Model One-to-One Relationships with Embedded Documents
Model One-to-Many Relationships with Embedded Documents
Model One-to-Many Relationships with Document References
Tree Structures in MongoDB:
Tree Structures built with array of ancestors
Materialised path tree structures
Nested Sets Tree Structures
Applications of models based on the context
Model data to carry out atomic operations
Model Data to complement search of keyword using MongoDB
References to Data Model and Data Modelling use cases.
This administration module in MongoDB makes us learn about monitoring issues related to our database and the corresponding servers. We learn more about the concepts of backup of the data and the various methods of recovery of data using MongoDB.
Concept of Administration in MongoDB environment
Checking the health of the MongoDB database
Issues faced with the Database and various ways to monitor them in MongoDB
Monitoring of issues at lower levels like Server, Database and collection level in MongoDB
Tools used to monitor issues in MongoDB database.
Profiling of database, database locks, usage of memory , connections and page faults in database handling
Various MongoDB methods for backup and recovery
MongoDB import and export of data
MongoDB run time configuration
Optimal practices in data management in MongoDB
Administration tasks using MongoDB in real time.
Ability to scale and availability
In this module, we cover advanced concepts like replica-set and master-slave replication using the previous concepts of MongoDB. We also briefly discuss the concepts of Sharding.
MongoDB replication- An Introduction
Setting up a replication clustering MongoDB
MongoDB sharding- An Introduction
Key concepts of sharding like configuration sever, query router, keys etc.
Setting up of sharding, various types and their management using MongoDB.
Indexing and Aggregation Framework using MongoDB
We learn about two new MongoDB frameworks in this module: Indexing and Aggregation
Introduction to Index
Concepts and types of index and their properties in MongoDB
Creating an index using MongoDB
Tutorial to Index using MongoDB
Indexing Reference using MongoDB
Introduction to Aggregation, various types and approaches to the concept. e.g. pipelining, single purpose etc. using basics of MongoDB
Tuning performance using MongoDB
MongoDB tools and engineering of various applications
This module gives us an insight to the various components of package and advanced concepts that are related to MongoDB. Furthermore, we also learn integration of MongoDB to Hadoop.
Package Components in MongoDB
MongoDB Configuration File Options
Limits and Threshold Values in MongoDB
MongoDB API and Drivers, Concept of MongoDB monitoring service
Rest interface and HTTP in MongoDB
Hadoop integration with MongoDB.
MongoDB based data migration with Hadoop.
Case Studies and Projects Using MongoDB
This module tells about the various security features of MongoDB and integration with various softwares like Jaspersoft, Pentaho and other GUI tools.
Introduction to security in MongoDB
Concepts of security and corresponding tutorials using MongoDB.
MongoDB integration with Jaspersoft
MongoDB integration with Pentaho
MongoDB integration with Hadoop /Hive
MongoDB integration with Java
MongoDB integration with GUI Tool Robomongo
Final project using concepts o MongoDB and Java.
En el habitual mensaje sabatino, publicado en Twitter,
A DBA i.e. a database administrator can earn an average salary of $81000 annually by the adept knowledge of MongoDB. As you continue working this can go upto $100000. A database architect who can create data models, migrate data, and can warehouse and analyse data can earn upto $107000 in the industry. Data Scientists can also use MongoDB to present data visually and make further forecasts. They are highly in demand, and it is going to further increase in the future. The average salary is high as $104000.
En el habitual mensaje sabatino, publicado en Twitter, Trump aseguró que el proyecto sanitario que “se abre paso en el Congreso” reducirá el déficit federal y será asequible y de calidad, “lo contrario de la gran mentira que era Obamacare”, la reforma sanitaria del expresidente Barack Obama.
“Si no lo sustituimos (Obamacare), la calamidad solo empeorará y quiero decir que empeorará mucho”, subrayó Trump.
How qualified are the trainers?
With more than two decades of corporate experience, the trainers are the some of the best MongoDB trainers out there. They have been in the market right from the days of its inception and have knowledge of the various changes that have taken place, and the exact requirements of the recruiters.
Is the final project important to learning the MongoDB course?
All the concepts that you have learned using that of Database creation and handling and management will be covered in the final project, which is the best way to understand the whole course. The practical exposure to the course is provided by the project, and that is what is the most important when you go for a job. For a complete learning experience the project is highly recommended to all the students.
Please bering into light the various refund policies for the course?
The refund is done only if the cancellation is done within 48 hours of the initial payment time. Any time after that will not be considered by us. The money will be refunded directly back to your bank account within a month of the date of cancellation.
Can I attend the classes anytime I want or do I have to follow the schedule?
Anytime you want to. The videos are recorded and put up on our website. They can be accused using the desktop website or the app that is available on the Android and app store. However, it is better to attend them live for instant query and doubt clearing.
How approachable are the trainers?
You can reach out to all our trainers anytime using their e-mails provided on our website. Further, you can put out your doubts and queries on our MongoDB discussion page and the trainers or your peers can answer your doubts there.