A database is an organized collection of data, generally stored and accessed electronically from a computer system. Where databases are more complex they are often developed using formal design and modeling techniques. The database management system (DBMS) is the software that interacts with end users, applications, and the database itself to capture and analyze the data. The DBMS software additionally encompasses the core facilities provided to administer the database. The sum total of the database, the DBMS and the associated applications can be referred to as a "database system". Often the term "database" is also used to loosely refer to any of the DBMS, the database system or an application associated with the database. Computer scientists may classify database-management systems according to the database models that they support. Relational databases became dominant in the 1980s. These model data as rows and columns in a series of tables, and the vast majority use SQL for writing and querying data. In the 2000s, non-relational databases became popular, referred to as NoSQL because they use different query languages.

A database should act as a kind of medium to collect and store the incoming data in an organized way. For example, in case of a relational database such as Oracle, the main purpose of this database is to store the input data and organize them in terms of attributes (columns) and tuples (rows) grouped into relations (tables). A database, in addition to storing the input data, should allow for an efficient retrieval of stored data as per user’s requirements. A database should be implemented with various security features such that it ensures high level of integrity, i.e., developing a trust for the users about their data stored in the database. A database should be highly scalable as the amount of data increases over time. In this context, it should also be highly adaptable to changes with respect to business needs. A database should be highly consistent despite the amount of concurrent transactions operating on the data stored in it. Further, it should also be highly durable so that it prevents loss of data despite the loss of power.

Fundamental Database Concepts
The Entity Relationship (= ER) Model
(the most common approach to conceptual database design)
The Relational Data Model
– Relations
– Integrity Constraints (keys, foreign keys, etc.)
Logical Database Design
(ER to relational schemas)
Relational Algebra
(an algebraic query language for the relational model)

SQL: Querying and Manipulating Data
– SQL Data Definition Language
– Single Block Queries
– Aggregation
– Joins and Outer Joins
– Nesting
– Negation
• Transaction Management and Concurrency Control
• Database Access from a Programming Language: JDBC

Data Storage and Indexing
– File Organisation and Indexes
– Tree-structured Indexing: B+-trees
– Hash-based Indexing
– Indexes in PostgreSQL
• Query Evaluation
– Sorting
– Evaluation of Relational Operators
– Query Optimisation
– Physical Database Design

English is the most popular and well-known Human Language. The English language has its own set of grammar rules, which has to be followed to write in the English language correctly. Likewise, any other Human Languages (German, Spanish, Russian, etc.) are made of several elements like nouns, adjective, adverbs, propositions, and conjunctions, etc. So, just like English, Spanish or other human languages, programming languages are also made of different elements. Just like human languages, programming languages also follow grammar called syntax. There are certain basic program code elements which are common for all the programming languages.

Most important basic elements for programming languages are:

Programming Environment
Data Types
Logical and Arithmetical Operators
If else conditions
Numbers, Characters and Arrays
Input and Output Operations


C Programming

Pre -requisite: Basic Computer Knowledge

Duration: 1.5 Month


Java Training Institute In Pune

Basic C

Environment Setup
Program Structure
Data Types, Variables, Constants
Storage Classes
Bit Fields
File I/O
Header Files
Type Casting
Error Handling
Memory Management
Command Line Arguments

Advanced C

Function arguments by reference
Dynamic allocation
Linked lists


Mongo DB for Fresher

Introduction to NoSQL
2. Introduction to MongoDB
3. Installing MongoDB on Windows
4. Data Modeling
5. Create Database
6. Drop Database
7. Create Collection
8. Drop Collection
9. Data Types
10. Insert Document
11. Query Document
12. ObjectId
13. Update Document
14. Delete Document
15. Projection
16. Limiting Records
17. Sorting Records
18. Indexing
19. Advanced Indexing
20. Indexing Limitations
21. Aggregation
22. MongoDB-Java
23. Map Reduce
24. Replication
25. Sharding
26. Create Backup
27. Deployment
28. Relationships
29. Database References
30. Covered Queries
31. Analyzing Queries
32. Atomic Operations
33. Text Search
34. Regular Expression
35. Working with MongoVUE
36. GridFS
37. Capped Collections
38. Auto-Increment Sequence


Mongo DB for Corporate

1 Module 1: NoSql Introduction & overview
What is NoSql?
Why there is a need for NoSql?
Schema less design
Brewer's CAP theorem
No Joins - Scale Out
Shared nothing architecture
Functionality vs. Scalability & performance
Comparison of NoSql with RDBMS
2 Module 2: MongoDB Introduction
MongoDB – A NoSql Database
JSON Introduction
Data Types in MongoDB
MongoDB installation on windows - Demo
MongoDB installation on Linux - Demo
Mongo shell
CRUD (Creating, Reading, Updating and Deleting data)
Demos and Assignments
3 Module 3: MongoDB Architecture
Replication sets
Types of replica set nodes
Config servers
Mongos - Routing servers
BSON Representation- Internal Storage
4 Module 4: Sharding cluster setup
Replica Set setup
Setting up config servers
Mongos – Routing server setup
Sharding setup
Auto Sharding - Insert large amounts of data
Demos and Assignments
5 Module 5: Data Modelling
No Joins – Use PreJoin/Embedding
No Foreign keys – Denormalize
Schema design - No declared schema
Shard key selection
How to embed data - Various scenarios
Benefits of embedding
Introduction to indexes
Types of indexes
Demos and Assignments
6 Module 6: MongoDB Integration with Java
MongoDB drivers
MongoDB Java driver introduction
MongoDB java API
CRUD with Java API
Demos and Assignments
7 Module 7: Mongo DB Aggregation Framework and Map Reduce
Aggregation framework introduction
Aggregation filters
Aggregation Pipelines
Aggregation framework vs. SQL – A comparison
Aggregation framework limitations
Map Reduce introduction
Map Reduce features and limitations
Demos and Assignments
8 Module 8: MongoDB Administration
Performance tuning
Demos and Assignments