
Explore how database management systems and databases power apps. They handle vast data—from banking and telecom to social media—covering traditional textual and numeric data, multimedia, gis, and big data systems.
Explore how a database management system—developed since the 1960s—solves traditional file processing problems by organizing data with catalogs and metadata to reduce duplication and inconsistency.
Trace the evolution from flat files to networked, relational, and object-relational databases, then NoSQL and big data, and grasp data models, schemas, and instances across conceptual, representational, and physical levels.
Explore data abstraction and data independence, including program independence and operation independence, at the physical, logical, and view levels, with a data dictionary and language roles.
Define database schemas and instances, highlighting how a database state changes with every update. Explore schema evolution and the three-level architecture: internal, conceptual, and external.
Define a transaction as a program that performs reading or updating records. Ensure it completes or fails completely, preserving consistency, isolation, and durability under concurrent execution.
Explain data independence by distinguishing logical independence and physical independence. Enable changes to the conceptual and internal schema without altering external views or applications.
Explore centralized and client-server database architectures, noting centralized remote processing versus distributed client work. Understand the three-tier web architecture with presentation, business logic, and database services layers.
Learn data mining to extract, cleanse, transform, and visualize data using clustering, regression, and classification, and explore information retrieval ranking of structured, semi-structured (JSON, XML), and unstructured text.
Explore the five phases of database design, from requirements collection and analysis to logical and physical design, and see how functional requirements, entity relationships, and constraints shape the conceptual schema.
Explore core terms in database design, including entities, attributes, relationships, and constraints, and distinguish simple, composite, single valued, multi valued, derived, null, and complex attributes within the entity relationship model.
Identify entity types and entity sets, keys and value sets, with employee examples and composite keys. Discover how relationships convert attributes into relationship types and distinguish binary and ternary relationships.
Explains cardinality ratio and participation constraints in binary relationships, including total and partial participation, existence dependency, and structural constraints; distinguishes strong and weak entity types, owner entities, and relationship attributes.
Identify department, project, employee, and dependent entities and define their attributes, keys, and relationships to support manager duration and employees’ hours per week on projects in a conceptual design.
Refine the database design by converting attributes into relationship types, determine the cardinality ratio and participation constraints, and remove redundant attributes to strengthen the conceptual schema.
Explore the additional features of the ER model, including superclass and subclass relationships, specialization and generalization, inheritance, and enhanced ER diagrams with employee subtypes and disjoint constraints.
Explore specialization and generalization constraints in dbms, including disjointness and completeness (total vs partial), predicate defined and attribute defined subclasses, with examples like job type defining engineer, secretary, and technician.
Explore specialization hierarchies and lattices in database design, contrasting strict trees with multi-parent lattices. Apply top-down refinement and bottom-up synthesis to model entity types and constraints like disjoint or overlapping.
Information is not useful if not organized. In database, data is organized in a way that people find it meaningful and useful. Database Management System (DBMS) is used to input, sort, organize and store data.
Database Management System (DBMS) is a Software for data storage & retrieval, for creating user interface (forms), reports, and for administering a DB system (security, access, etc.). An implementation of a DBMS product to support various information needs in a company includes one or more databases, logic (business rules), backend code and user interface.
An information system that is built from “applying” a DBMS or a database to a specific domain, supports specific information needs.