Data Modeling and Relational Database Design using ERwin

Identify identifying and non identifying relationships in relational design, showing how parent and child keys migrate, optional versus mandatory foreign keys, weak entities, and association entities for many-to-many joins.

Explore recursive relationships in data modeling and relational database design with ERwin, using role names and foreign keys to model supervisor, prerequisite, and parent-child connections.

Model super types and subtypes by abstracting common attributes into a generic employee entity and defining full time and part time subtypes with their own specific attributes and rules.

Model supertypes and subtypes in ERwin using a discriminator attribute and identity relationships. Apply rollup or roll-down transformations to adjust between supertype and subtype tables.

Analyze and model a retail banking information system by identifying entities such as bank, branch, customer, account, and transaction, and design a conceptual, logical data model with relationships and constraints.

Configure Erwin diagrams to display entities, attributes, data types, and keys, choose layout types, and adjust background, alignment, and sizing for clear relationship visualization.

Create and assign domain objects to model attributes to enforce consistent data types. Explore domain inheritance, overriding, and forward engineering to reflect domains in DDL and table definitions.

Use the bulk editor in Erwin to apply definitions to multiple entities or tables, export and edit definitions in CSV, and re-import updates to the model.

Master Erwin forward engineering to generate an Oracle schema from a physical model, preview the ddl, and deploy tables, primary keys, unique indexes, and foreign keys.

Connect to an Oracle database and reverse engineer its objects to generate a data model in ERwin.

Explore naming configurations in Erwin Data Modeler, including case and length settings, and learn to apply a glossary and name mapping to derive physical names with prefixes and suffixes.

learn to use erwin's complete compare to identify differences between baseline and working models, import or export changes, and apply updates like the account type table and foreign keys.

Master erwin complete compare to compare two models (left vs right), view differences, and import or export changes, then generate alter scripts and explore versioning with Maat model repository.

Export diagram images from ERwin by generating the current diagram or multiple diagrams, choose output formats such as enhanced metafile, jpeg, or png, and copy diagrams into documents.

Create and export entity reports using report designer, choosing report type (logical, physical, or combined), selecting entities, applying filters, grouping by entity, and exporting to HTML, PDF, or CSV.

Master exporting diagrams to html and pdf reports with ERwin's report designer, including subject areas, entities, attributes, definitions, and clickable links, plus color customization options.

Explore dimensional modeling techniques optimized for analytics, organizing data into fact and dimension tables in a star schema to improve understandability and performance, and develop this model with Erwin.

Design a retail star schema with a fact_sales table and four dimensions: customer, product, store, date, defining grain, base and calculated measures, and non-identifying relationships in ERwin for Oracle.

Capture source to target mappings and ETL rules in Erwin by creating data movement sources, importing tables from models or csv, defining column mappings, and sharing them via report export.

Create detailed mapping reports in a spreadsheet and publish diagram-based HTML and PDF documents of source-to-target mappings, including ETL rules for a physical data model.

Learn how normalization minimizes redundancy and dependency to prevent insert, update, and delete anomalies, and why isolating data enables consistent relational design.

Apply first normal form by ensuring unique column names and that order of columns and rows is insignificant, a single domain value per cell, and no duplicate rows.

Explore first normal form through a customer transactions example, showing atomic values, removal of repeating groups into a separate table, and foreign key relationships.

Master second normal form by eliminating partial dependencies, ensuring non-prime attributes depend on the complete key, and decompose tables to remove partial dependencies.

Explore third normal form by eliminating transitive dependencies, ensuring non-prime attributes depend directly on the key, with sales and measurement table examples including coupon code and discount.

Learn how Boyce-Codd normal form requires every determinant to be a candidate key, strengthening third normal form by eliminating non-key dependencies.