Explore relational databases by learning how tables, primary keys, and foreign keys create one-to-one, one-to-many, and many-to-many relations, and how normalization (1NF–BCNF) reduces redundancy to enable fast, reliable SQL queries.

Explore PostgreSQL data types including numeric, character, date-time, boolean, JSON, and user-defined types, and learn schemas as logical containers with examples creating schemas and tables.

Master database creation and management with pgadmin, connecting to the server and running SQL queries to create databases with Postgres as owner, encoding, and templates; explore schemas, tables, and objects.

Create a table using pgadmin by connecting to a Postgres server, define columns with data types, set a serial primary key, and view the table in the public schema.

Learn to alter a table by adding, dropping, and renaming columns using pg admin ui and sql, with hands-on steps on the employees table in the public schema.

Learn how to delete a table safely using pgadmin or a drop table statement, including cascade options and foreign key constraints, with deletion being permanent.

Create PostgreSQL tables using SQL create table syntax, defining serial primary keys, not null constraints, varchar and numeric types, and default current_date.

Learn to insert data into an employees table using SQL insert statements, with serial id, default hire date, and multiple records, then verify results by running a select.

Learn how to retrieve data with sql by writing select queries to fetch all or specific columns from a table, apply where filters on salary, and prepare results for dashboards.

Learn how to modify existing data with the SQL update statement, using set and where clauses to target records by id or name, and back up before updates.

Master delete operations in SQL by removing specific records with delete from table where id = 2, and understand primary key uniqueness in CRUD operations.

Master SQL basics with structured query language to retrieve, modify, and delete data in relational databases, using select, insert, update, delete, create, and drop commands.

Master the select statement with a query tool, fetch all columns using select *, filter by where id, and retrieve specific fields like salary for Alice, such as 75,000.

Discover how the select distinct keyword eliminates duplicate records without deleting data in an employees table, surfacing unique positions such as designer, manager, and developer.

Learn to use the count aggregate function in SQL to count records in the employees table, alias the total, and filter with a where clause in PostgreSQL.

Learn to retrieve data with SQL by using select and where clauses, selecting specific columns or all columns from tables, and filtering with conditions and operators.

Learn to filter data with the where clause in SQL, using a select statement on the employees table, applying salary and date filters and combining conditions with logical operators.

Sort sql query results with the order by clause, using asc by default and desc for descending, on one or multiple columns; apply to salary, name, and more.

Learn to efficiently limit results using the limit clause, apply where filtering, and sort with order by desc to fetch the top records from large data sets.

Learn to use limit and offset in SQL to skip the top rows and fetch the next set, with examples of limit two and offset two.

Learn to use the sum() aggregate function in SQL to calculate total salaries and other numeric totals. Group results by position and apply where filters for dashboard-ready insights.

Explore using the SQL avg function to calculate averages from numeric columns, such as salaries and product prices, and apply group by and where filters to view position-based results.

Apply the min function in SQL to quickly find the smallest values in numeric or date columns, such as minimum salary or earliest hire date.

Apply the max function in SQL to find the largest value in numeric, date, or string columns, such as the maximum salary from the employees table, and filter by position.

Master string_agg in Postgres SQL to concatenate employee names with a delimiter into a single cell, using group by to organize results.

Apply the SQL variance function in Postgres to measure population variance, using salaries in the employees table and group by position to compare variance across groups.

Learn to calculate standard deviation in SQL with the stdev function on numeric columns like salaries, using group by and where to analyze dispersion.

Learn to use count distinct in sql to count unique values, exclude duplicates, and filter results with where on an employee table example.

Learn to group data efficiently in SQL with the group by clause, using aggregate functions (count, sum, avg, max, min) to produce per-group totals by position and department.

Master advanced data filtering with having after aggregation, using group by and sum to analyze department wise salaries; practice dynamic SQL queries with aggregations and thresholds.

Explore how to use sql joins to combine data across tables in postgres, covering inner, left, right, full outer, and cross joins with practical examples.

Create department and employees tables with department id as a serial primary key and a foreign key in employees; perform an inner join to show each employee with department name.

Master left join in SQL by returning all rows from the left table and matching rows from the right table, with nulls for non-matches, as shown with employees and department.

Explore right joins vs left joins and inner joins, returning all records from the right table and showing nulls for nonmatching rows, and decide join type by business needs.

Learn to use full outer join to combine two tables, including matching and nonmatching rows, with left and right joins to produce a complete result set.

Learn how to perform a self-join by joining an employee table to itself, using a manager id to fetch each employee's manager name with aliases and an on clause.

Learn how cross join in sql produces the cartesian product of two tables, such as products and colors, yielding all possible combinations for reporting.

Enforcing the not null constraint ensures each column contains a value, establishing mandatory fields in a users table and preventing empty data in your PostgreSQL database.

Apply the unique constraint in SQL to enforce uniqueness across username and email columns, preventing duplicates and ensuring data integrity in user records.

Explore how primary key constraints uniquely identify each record in PostgreSQL and boost performance while enabling reliable table relationships, demonstrated with a sample student table.

Learn how to enforce referential integrity in SQL using foreign key constraints between customers and orders, with on delete cascade and on update cascade.

Learn how to enforce data validity with PostgreSQL check constraints, validating age between 18 and 65 and non-zero salaries when inserting into an employees table.

Explore PostgreSQL default constraints in inserts. Create an employees table with employee_id as a serial primary key, name, status default active, and created_at default current_timestamp, inserts show defaults and overrides.

Learn how PostgreSQL indexes speed data retrieval by indexing the name column with a B-tree index; explain analyze shows performance gains and space overhead with slower writes.

Master timestamps and date and time handling in sql by creating and querying events and shifts tables, using date types, insertions, between, extract, and current_date or current_timestamp for reports.

Explore PostgreSQL mathematical functions beyond basic arithmetic, including trigonometry, logarithms, rounding, and random number generation. Practice SQL expressions for addition, subtraction, multiplication, division, and sine and log.

Master string manipulation in PostgreSQL with concat and substring functions to join and analyze text, concatenate names across columns, and slice data for precise data extraction.

Explore how subqueries in PostgreSQL nest queries to break complex problems into smaller parts, using them in select, from, and where clauses to filter results.

Learn to use the SQL case statement for conditional logic to categorize salaries as high, medium, or low, creating a virtual column alias for dynamic reports and visualizations.

Master PostgreSQL backups with pgAdmin to ensure data integrity, export databases to custom format or SQL script, and configure dump options for data, schema, and restoration.

Learn to restore a PostgreSQL database with pgadmin 4 by creating a new database and selecting a custom or tar backup, ensuring version compatibility and required permissions for business continuity.

Tackle a database management capstone by building a database end to end, covering schema design, data integration, insert operations, and PostgreSQL optimization with practical examples.

Design a simple company management schema with departments, employees, and projects, including department id serial, unique constraints, foreign keys, and a composite key for the many-to-many relationship.

Insert sample data into departments, employees, and projects, establish a many-to-many mapping with employee_id and project_id, and prepare for validation with select queries in the next lecture.

Write SQL queries with select statements, where clauses, and joins to retrieve data from employees, departments, and projects, displaying employee id, first name, last name, department name, and project name.

Learn how to optimize databases by creating indexes on email, department ID, and project name to accelerate searches, improve query performance, and support faster report generation.

Explain analyze reveals planning and execution times for a PostgreSQL query, and shows how adding indexes on department_id dramatically reduces planning and execution time.

Optimize query performance by vacuuming and analyzing to maintain table statistics for the query planner. Review the statistical query plan and its findings for reports.

Explore partitioning large data sets by creating partitioned tables with the partition keyword, separating employees into hr, engineering, sales, marketing, and developers.

Master the database backup process by selecting the company db, initiating a custom format backup named company_db.backup, and saving to a chosen location, with restoration covered in the next lecture.

Master restoring a Postgres database from a backup in pgadmin: create the target database, select a custom .backup, run restore, and verify data across tables in a local development environment.

Learn to manage PostgreSQL users and roles through pgadmin by creating login group roles, setting passwords and expiration, configuring connection limits, and assigning superuser or read/write permissions with memberships.

Learn Power BI for data preparation, data visualization, distribution and management, using multiple data sources to create stunning visuals and actionable dashboards.

Learn to set up Power BI on Windows and Windows Server, understand operating system requirements, and start building business intelligence reports as a beginner or professional.

Master how to ask great questions for SQL and Power BI tasks from data to dashboard, using Google Drive, Stack Overflow, and error-code screenshots with instructor support.

Master Power BI visualizations with real-world exercises using Excel data sources, guided by step-by-step video lectures and practical practice for data insights.

Explore business intelligence with Power BI to analyze large data sets, create interactive dashboards and reports, and drive data-driven decisions through real-time data, AI insights, and collaborative visuals.

Power BI visualizes data insights with real-time analytics through interactive dashboards and reports, connects to diverse data sources, and enables desktop, services, mobile, and gateway for data-driven decisions and collaboration.

Explore how Power BI visualizes data to support quick, informed decisions through interactive dashboards, real-time analytics, and charts such as bar, line, pie, donut, and radar.

Explore Power BI desktop, service, and mobile apps to connect data sources, transform data, build visualizations, publish dashboards, and share real-time insights across cloud and mobile tools.

Download Power BI Desktop from the official Microsoft website, select x64 for Windows, complete the setup, then import data from Excel, SQL Server, or CSV, and publish reports.

Explore the Power BI desktop interface, connect data from Excel or SQL Server, load sample data, and build reports with visuals, modeling, DAX, and publish.

Explore essential Power BI desktop settings, including data source configuration, options, autosave, regional language, and data loading, plus building relationships and saving pbix reports.

Collect and shape data from diverse sources, including Excel files, SQL Server, and web data, using Power BI and Power Query for transformation to create report-ready, live dashboards.

Learn to import and load data from Excel and CSV into Power BI, explore get data from other sources, and build a simple table report you can export to PDF.

Transform and clean Excel data in Power BI by renaming columns, changing data types, splitting columns, and applying filters, then load into the dataset and create basic charts.

Learn how to use the Power Query Editor in Power BI to transform data from Excel, clean and shape it, rename and remove columns, and apply reusable transformation steps.

Learn to clean and shape data in power BI using power query editor, importing Excel data, handling nulls, standardizing departments, removing duplicates, and adding a custom annual bonus column.

Merge two tables in Power BI with Power Query using inner, left, right, full, and anti joins to build a salary report from employee details and employee salary.

Establish relationships across Power BI data tables by linking common keys like customer id and product id to analyze related data and build region and category sales reports.

Create Power BI data models by establishing table relationships to ensure data integrity and fast reporting. Import data, clean with Power Query, and build visuals using star or snowflake schemas.

establish relationships between product details and sales data in Power BI using Excel data, enabling one-to-many relationships and model view for accurate visualizations.

Optimize data models in Power BI by establishing many-to-one relationships among sales, customers, and products to enable fast, scalable reports and a star schema with single cross filtering.

Import excel data into Power BI, model sales, customers, products, and date tables, and create DAX measures for total sales and average price; visualize with a line chart.

Master data analysis expressions (dax) in Power BI, Excel, and SSAS to create custom calculations, aggregations, calculated columns, measures, and time intelligence for interactive dashboards.

Master calculated columns with DAX in Power BI by linking sales and products on product ID and computing total cost as quantity times price using related.

Learn to create measures with DAX formulas, building on calculated columns and relationships to compute total sales from the sales amount. Use measures in visuals with sum and average.

Learn how to use DAX measures in Power BI visuals by dragging calculated columns and measures into bar charts and other visuals, customize colors, titles, borders, and effects for dashboards.

Master DAX aggregation functions in Power BI to calculate total sales, average sales, distinct product counts, and total revenue. Import data, relate sales to products, and build measures for visuals.

Explore interactive filters and conditional calculations to create filtered reports in Power BI, selecting laptop, monitor, or smartphone data, and customize visualization elements like axes, legends, and colors.