Mastering Data Modeling and Database Design

Explore how relational databases organize data into tables with rows and columns, relate data with keys, and use SQL queries to join and summarize business performance. Also cover ACID properties.

Identify candidate keys as minimal attribute sets that uniquely identify a row, whether single or composite, and distinguish their roles as super keys, primary keys, alternate keys, and foreign keys.

Explore data modeling as a blueprint for databases using ERD to map entities, attributes, and relationships, covering strong and weak entities and single- and multi-valued attributes, with Visual Paradigm.

Explore relationships and cardinality in data modeling, covering 1-to-1, 1-to-many, and many-to-many associations with optionality and crow's foot notation, plus practical examples.

Lead the three-stage data modeling process—conceptual, logical, and physical—with clear requirements. Translate requirements into an ERD and forward-engineered database design for implementation by DBAs.

Explore the first normal form in relational databases, ensuring every table cell contains a single atomic value and outlining how normalization builds from this form.

Explain how to achieve the second normal form by removing partial dependencies in composite-key tables, splitting employee and project data into related tables with foreign keys.

The fourth normal form eliminates multivalued dependency when a has multiple values of b and c, so you split into two tables, employee skill and employee project.

Explore the fifth normal form by analyzing joint dependencies, decomposing book, author, and publisher data without information loss, and evaluating supplier, product, and customer examples.

Learn to build entity relationship diagrams in Visual Paradigm practical 1, creating entities with primary and foreign keys, one-to-many and many-to-many relations, and converting conceptual to logical and physical models.

Master visual paradigm's data modeling workflow by exporting projects and diagrams, generating data specifications, and documenting entities, attributes, keys, constraints, and indices for enterprise metadata.

Learn to draw and build enterprise-grade diagrams with visual paradigm, collaborate via repositories, manage versions, and explore ERD design and end-to-end architecture using the tool and its documentation.

Install Oracle database on a machine by downloading, extracting, and setting up; configure Oracle home and base, set sys and system passwords, and prepare connections via sqlplus or sql developer.

Install SQL Developer, a graphical user interface to access the Oracle database, and connect it to your local database to run queries in a worksheet window.

Connect Visual Paradigm to the Oracle database by configuring the JDBC driver, connect to localhost/1521, and fix the error by using a slash instead of a colon.

Reverse engineering a live Oracle database into an entity relationship diagram using Visual Paradigm, translating tables, views, and schemas from DDL scripts into a coherent data model.

Master dimensional modeling for data warehousing by designing facts and dimensions to optimize read performance and enable fast reporting, using star, snowflake, and constellation schemas with conformed dimensions.

Explore the four main types of fact tables in dimensional modeling: transactional, periodic snapshot, accumulating snapshot, and factless, with examples from sales, orders, and enrollment.

Explore static and slowly changing dimensions in data modeling, detailing SCD types 1, 2, 3, and 6, and how to store current versus historical values.