SQl+Python for Data Analytics & Business Analytics(19 Hours)

Master creating a table in sql by defining rows and columns, choosing data types, and inserting data into an employee table.

Use the select into command to create a table without a create statement from orders, backup into order bcp and order bcp one, with tbl loss where profit < 0.

Use the drop table command to delete a table or view, demonstrated with the employee table in the Udemy database. Refresh the database to verify the table no longer exists.

Learn how to modify an existing table using the alter table statement, including adding, modifying, and dropping columns and constraints, demonstrated on an employee table in SQL Server.

Learn how to insert data into an SQL table using a graphical user interface, from creating the employee table to importing 200 rows via copy-paste from Excel and bulk insert.

Learn to use the insert into statement to add data to a table, including single and multiple row inserts in the employee table, with both string and numeric data.

Learn to bulk insert data into a sql table from a csv file using the bulk insert command. Set the path, field terminator, and row terminator for efficient import.

Import data from an Excel file into a SQL Server table using the data import wizard, mapping sheets to tables in the Udemy database and validating with select queries.

Export data from a SQL Server table to an Excel file using the export task, selecting the source table and destination, then verify the transferred data.

Learn how to safely delete data in SQL Server using conditional delete statements, compare delete vs truncate, and understand when truncation cannot be rolled back.

Learn to delete all data from a table using delete and truncate, compare dml versus ddl, note that delete allows a where clause and is slower, while truncate is faster.

Master the update statement to modify records with a where clause, avoiding mass changes, with examples updating city to Mumbai and salaries by 10%, including brackets for spaced column names.

Learn to update data with SQL Server using conditions, including changing department from HR to human resource and applying a 10 percent salary increase in total salary.

Learn how to use begin transaction with insert, update, and delete in SQL to control and rollback changes, and commit to make them permanent.

Master the select statement in SQL Server to extract data and view all columns with star, and learn to show only specific columns like name, department, and salary.

Learn how to use the distinct keyword with select to fetch unique values from columns such as region, product category, and product name in the orders table, removing duplicates.

Apply a where clause to filter the orders table by region, selecting the west region. Use and to add a second condition where profit is less than zero.

Apply the end operator to filter data with multiple conditions in SQL, using where clauses to combine region and salary, or west region with profit and technology category data.

Use the or operator to combine conditions in a where clause. Return orders that match any condition, such as west region or sales below zero.

Explore the in operator for filtering data with multiple conditions in a where clause, and compare it to the or operator, with departments such as sales and management.

Use the between operator to filter numbers, dates, and text by a start and end value in where clauses.

Explore how to use the like operator to pattern match data with where clauses, percentage wildcards, and not like for exclusion across samples as employee names and Xerox product names.

Learn how to use the top clause to return a specified number of records from large tables, including top N, 50% or 25%, and ordering for top or bottom sales.

Apply the order by clause to sort data in ascending or descending order, using multiple columns like department and total salary, or by column number to organize results.

learn to sort data in ascending order using SQL Server, including multi-column sorting, filtering by the technology product category, and ordering by profit in large data sets.

Explore SQL for data analytics and business analytics by ordering data in descending order, selecting from orders, filtering by product category technology, and sorting by profit.

Sort sql data with order by multiple columns, using ascending or descending order for department, name, and total salary; explore region, product category, and profit in employee and orders tables.

Learn how to group data by department in sql server, compute salary sums and employee counts, and sort results in ascending or descending order.

Group by aggregates data across one or more columns to summarize results and show unique values, often using an aggregate function with examples from the employee table.

Learn to use group by to aggregate data by region, calculating order counts, total profit, and region-wise average, maximum, and minimum profits. Apply aliases to name result columns clearly.

Learn how to use the having clause with group by to filter aggregated data, illustrated with region wise profit in the orders table.

Learn to use a subquery to retrieve the employee data with the maximum salary by computing the maximum salary in an inner query and filtering the outer query.

Explore subqueries by finding the product with the minimum sales from the orders table, using an inner query and a master query to retrieve the product name or full row.

Learn to compute the average salary using the avg function, then query the employees table to select records where salary exceeds that average.

Use a subquery to compare two tables and extract matching records from the master table with a select where in, based on names that appear in the second table.

Retrieve the product name for the third highest sale from an orders table using top, order by, and subqueries—an interview-style scenario.

Identify the product with the third smallest sales by querying the orders table in SQL Server, using top 3 and order by sales asc, then select the matching product name.

Learn to extract the third largest value from grouped data using subqueries, group by, and having in SQL server, with department and region examples.