SQL Advanced
About Course
Senior SQL Developers are in high demand and demand 100k+ salary in the IT industry.
If we have to advance in our career and earn a good salary, we need these Advanced Structured Query Language skills. So let’s take the next step of learning these advanced concepts of Oracle SQL.
Learning these advanced Structured Query Language concepts would position you better in your working environment.
What will we learn?
Students will learn the art of breaking a big SQL statement into small pieces and rebuild it again.
Create Materialized views to replicate data across servers and improve performance by using simple Structured Query Language syntax.
Partition the tables for better management and performance optimization using Structured Query Language Partitioning.
Students will learn to use the Analytic Structured Query Language to aggregate, analyze and report, and model data using the Structured Query Language Analytic capabilities.
Students will learn to interpret the concept of a hierarchical query, create a tree-structured report, format hierarchical data, and exclude branches from the tree structure using SQL Hierarchical features.
Students will also learn to use regular expressions and subexpressions to search for, match, and replace strings using Structured Query Language built-in functions.
Group and aggregate data using the built-in Structured Query Language functions like ROLLUP and CUBE operators.
See you inside,
Course Content
SQL Querying: Advanced
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Welcome to the course
00:00 -
Installing Oracle
00:00 -
Installing Java SDK
00:00 -
Installing SQL Developer
00:00 -
Running scripts necessary for the course
00:00 -
Default values for columns
00:00 -
Virtual Columns
00:00 -
Arithmetic calculations on NULL Values
00:00 -
Multi table Inserts
00:00 -
Merge the data
00:00 -
Analytical Functions Introduction
00:00 -
Why Analytical Functions Example 1
00:00 -
Why Analytical Functions Example 2
00:00 -
Getting the cummulative Sum of Sales
00:00 -
Displaying Sales as a percentage of Total sales
00:00 -
Ranking your data
00:00 -
Performing Top N Analysis
00:00 -
Dividing your data into Bands
00:00 -
LAG and LEAD function Examples
00:00 -
Analyzing Sales growth across time
00:00 -
Row level data to Column level using CASE statement
00:00 -
Row level data to Column level using PIVOT
00:00 -
Row level data to Column level using LISTAGG
00:00 -
Column level data to Row level using UNION
00:00 -
Column level data to Row level using UNPIVOT
00:00 -
Hierarchical Queries Introduction
00:00 -
Connect By clause
00:00 -
Creating the Hierarchy Tree
00:00 -
Sorting the Hierarchy Tree
00:00 -
CONNECT BY ROOT unary operator
00:00 -
Get me the Sales under Manager Raj
00:00 -
SYS CONNECT BY PATH function
00:00 -
CONNECT BY for number generation
00:00 -
Extensions to Group BY
00:00 -
Sub Totals using ROLLUP function
00:00 -
Sub Totals using CUBE function
00:00 -
GROUPING function
00:00 -
GROUPING ID function
00:00 -
Limiting number of sub totals using GROUPING SETS function
00:00 -
Composite Columns
00:00 -
Table Partitioning Introduction
00:00 -
Range Partition based on range of values
00:00 -
List Partition based on list of values
00:00 -
Hash Partition based on the hash key
00:00 -
Composite Partitioning by mixing things up
00:00 -
Interval Partition for automatic partition creation
00:00 -
Materialized Views Introduction
00:00 -
Materialized Views creation Options
00:00 -
Materialized Views with ON COMMIT option
00:00 -
Materialized Views with ON DEMAND option
00:00 -
Materialized Views with REFRESH FAST option
00:00 -
Timing the refresh
00:00 -
Query Rewrite functionality
00:00 -
Regular Expressions Introduction
00:00 -
Meta Characters and
00:00 -
Meta Characters and
00:00 -
Interval Operator to match the number of occurances
00:00 -
Matching the characters in a List
00:00 -
Lets combine multiple expressions using
00:00 -
Check for an expression in the beginning or end of a string
00:00 -
POSIX Character class operators
00:00 -
Search for meta characters by placing a escape character
00:00 -
Flashback operations Introduction
00:00 -
Tracking changes in Data
00:00