NCI Courses

Data, Databases, File based systems, DBMS environment, Data Redundancy, Data Anomalies, Database System Environment, Functions of DBMS, Database Professional Career and Concept of views.

Data modelling, Relational Models, Object-relational Model and Object Models, Importance of Relational databases and comparison of database models.

Concepts and terminology in Entity–Relationship (ER) modelling, Diagrammatic technique using Unified Modelling Language (UML), Challenges associated with ER models, Build ER model based on requirements specifications.

The purpose of normalization, Designing a relational database, Potential problems associated with redundant data, Concept and Characteristics of functional dependency, Process of normalization, First Normal Form (1NF), Second Normal Form (2NF), and Third Normal Form (3NF).

Data types supported by SQL, Define integrity constraints, Integrity enhancement feature in the CREATE and ALTER TABLE statements, Create and delete views using SQL, Operations on views, Advantages and disadvantages of views, GRANT and REVOKE statements as a level of security, Transactions (COMMIT and ROLLBACK) in SQL.

Importance of SQL, Writing of SQL commands, Retrieve data using the SELECT statement, Build SQL statements, use the WHERE clause to retrieve rows that satisfy various conditions, sort query results using ORDER BY, use the aggregate functions of SQL and group data using GROUP BY.

Writing of SQL commands for complex queries, Retrieve data using the SELECT statement from multiple tables, Build SQL statements (Continuation from previous week), use subqueries, join tables together, perform set operations (UNION, INTERSECT, EXCEPT) and Perform database updates using INSERT, UPDATE, and DELETE.

Introduction to Indexing, Types of indexing, Ordered Indices, Static Hashing, Dynamic Hashing, Comparison of Ordered Indexing and Hashing, Index Definition in SQL and Tree Structures.

Concepts and benefits of data warehousing, Online transaction processing (OLTP), Architecture and main components, Tools and technologies, Concept of a data mart and the main reasons for implementing a data mart, Benefits of Data warehousing.

Designing Data Warehouses, Two main methodologies: Inmon’s Corporate Information Factory (CIF) and Kimball’s Business Dimensional Lifecycle, Principles and stages associated with Kimball’s Business Dimensional Lifecycle, Dimensional Modelling stage of Kimball’s Business Dimensional Lifecycle, Issues associated with the development of a data warehouse.

NoSQL databases, Capabilities of NoSQL Technologies, E-commerce/ Social media Applications, Motivations for NoSQL Databases, The CAP Theorem, Consequences of The CAP Theorem, Data Management with Distributed Databases, ACID and BASE Characteristics, NoSQL Classifications, Benefits of NoSQL Databases.

Introduction to Data Lakes, Data Lakes for enterprises and works, Differentiate between Data Lake and Data Warehouse, Lambda Architecture for Data Lakes, Batch layer, Speed layer, Data Storage layer, Serving layer, Data Acquisition of Batch, Data Processing and Data Store using Apache Hadoop