From Zero to Database Designer – Learn the Basics Fast

Explore the fundamentals of data, databases, and database management systems, and discover how SQL helps organizations collect, organize, and store information.

Explore why we store data in a database management system and how sql enables access across apps and dashboards. This course teaches database design, not sql syntax.

Explore core database types—relational, key-value, document, column-based, and graph—and contrast SQL versus non-SQL databases, highlighting OLTP real-time processing and OLAP batch analytics.

Compare excel-based data management with a relational database, learn to organize data into related tables, reduce duplication, enforce validation, and use sql for integration, security, and scalability.

Explore the structure of a database by installing a database management system, creating databases and tables, organizing them with schemas, and defining columns and rows to store customer data.

Explore how data types define what each table column stores, using examples like integer, character, numerical, and date data in customer and product tables.

Use primary keys to assign unique values for each record and foreign keys to link related tables, validating data across customers, products, and orders.

Explore how primary keys enforce unique records and how foreign keys ensure referential integrity across customers, products, and orders by validating IDs.

Explore how primary keys, foreign keys, and constraints including unique, check, and default enforce data quality and integrity by validating values and applying defaults in table design.

Explore the six-phase database development lifecycle—from planning and analysis to maintenance—and learn design modeling (conceptual, logical, physical), dbms implementation, testing, deployment, backups and recovery for a scalable, secure database.

Identify the database goal and business requirements during the planning and analysis phase, define scope, and set boundaries to prevent complexity and boost performance.

Analyze the existing system to understand data flows, identify manual versus automated processes, and uncover drawbacks. Plan migration by assessing data quality and deciding what to migrate or archive.

Design a database from scratch by defining clear business goals, scope, and boundaries; collaborate with stakeholders to determine retrieval needs, analytics, and security requirements.

Master data modeling and database design from conceptual to physical models, then map to DBMS schemas, scripts, and constraints, and implement secure, indexed databases with triggers and stored procedures.

Discover how data modeling translates business requirements into a database design by turning nouns into entities, adjectives into attributes, and verbs into relationships, then linking tables with foreign keys.

Explore cardinality and how many instances of one entity relate to another, covering 1-to-1, 1-to-many, and many-to-many relationships with examples and junction table concepts.

Define participation and distinguish total and partial participation in entity-relationship diagrams, showing mandatory versus optional relationships (single vs double lines) with examples like orders, customers, loans, and bank accounts.

Explore database design as a blueprint for organizing data, defining tables, columns, relationships, constraints, and normalization. Learn how a SQL data definition script enables efficient implementation and future maintenance.

Design databases by separating data into related tables, such as customers and orders, to simplify maintenance and updates, reduce redundancy, and boost performance through normalization and indexing.

Translate data modeling outputs into a working database by implementing the database design, executing sql scripts, configuring the dbms, and creating tables, indexes, and constraints with proper security and backups.

Normalization organizes relational data by splitting it into related tables and creating links to remove redundancy. This step-by-step process improves data quality as more normal forms are applied.

Navigate normalization levels from unnormalized format to first, second, third, and fourth normal forms and finally bcnf normal form, testing data with pedestrian, cycle, car, and heavy vehicle checks.

Learn how normalization eliminates data redundancy, avoids update, delete, and insert anomalies, and improves data integrity, quality, and query performance.

Learn the first normal form, the first step of normalization, ensuring atomic data values, no repeating groups, and unique rows with consistent data types per column.

Explore second normal form, which requires first normal form and no partial dependency; see how non-key attributes fully depend on the entire primary key in a composite key scenario.

Explore second normal form by splitting data into student details, course details, and enrollment tables, removing partial dependencies and ensuring non-key columns fully depend on their keys.

Learn why to use a surrogate key instead of a business key like username for primary keys, preserving referential integrity and foreign keys while reducing storage.

Design your table names without spaces to simplify sql and migrations. Use underscores or single words, and prefer camel or pascal case; avoid reserved words like order or from.

Design a database with less redundant data by deriving age from date of birth and calculating order totals from price and quantity at runtime, reducing storage and preventing anomalies.

Learn to enforce referential integrity across related tables by using primary keys and foreign keys to prevent orphan records and keep data consistent.

Split data into multiple columns so each field stores a single value, improving updates, searches, and sorting for addresses, names, and product details.

Avoid storing similar optional data in multiple columns by normalizing your database, splitting phone numbers into a separate phone details table, and using a type id for flexible design.

Design a relational database for an online store supporting user management, products, orders, reviews, offers, payments, refunds, and returns.

Design a basic database to manage user information and login activity, storing user details (name, email, phone, username, password) and unique login credentials with login times for future expansions.

Design a product database with a product table (id, name, description, price, quantity) and offer table (offer id, product id, offer price, description), linked by product id to support discounts.

Learn how to model orders in a database with an order table and an order item table to track each order’s date, status, customer, product items, quantities, and unit prices.

design a return details table to track returns by order item id, including date, reason, and status, and map returns to orders and order items for item-level refunds.

Design a review system by creating a review table linked to order items, capturing numerical ratings and optional comments when customers leave product reviews after orders.

Design a refund data model by tracking refund amount, refund date, refund reason, refund status, and payment ID linked to order item IDs, with payment ID optional to reduce linking.

Explore how entities like user, order, and product relate through one-to-many relationships, using ids to model login details, orders, items, reviews, returns, payments, and refunds.

Improve database design by upgrading schemas: add address handling and Createdat, rename offer reason to offer description with start/end dates, and link orders, returns, and reviews via IDs.

Install SQL Server and SQL Server Management Studio to set up a database engine. Download developer edition, choose basic or custom setup, configure authentication, and connect to the database.

Design and script the first database by creating a user table and ten related tables, including login details, product, order, payment, return, and review, with auditing columns.

Create a database diagram in SQL Server Management Studio by selecting tables and defining foreign key relationships. See how user relates to order and order relates to payment and refunds.

Implement constraints to ensure data quality in database design, including not null, unique, default, and check rules, plus primary and foreign keys for referential integrity.

Validate database constraints by inserting records to verify not null, unique, foreign key, and check constraints across user, login details, and product tables.

Demonstrate enforcing constraints by inserting valid and invalid records into offer and related tables, ensuring a positive offer price and non-null dates, and manually correcting IDs when needed.

Cross-check the database against business requirements by joining user, order, and payment data to show orders with customer details and payment status, validating end-to-end data integrity.