
Get an overview of what all is covered in this course.
Lecture provides details into what PostgreSQL is and what is the SQL use case for any analytics professional
Steps to setup the Postgres with PGAdmin4 in windows machine
Explore PgAdmin 4 to interact with Postgres databases, manage schemas and tables, run sql queries via the query tool, and export results to csv or excel.
load a sample data set into Postgres using pgAdmin 4 by creating a table and importing data from CSV, either via the UI or via a copy command.
Explore select and from basics in sql with pgadmin4, retrieving fields from a table, using star, aliasing tables, and applying limit and aggregate functions like count and sum.
Learn to create tables and insert data in PostgreSQL, define schemas with primary key, not null, unique, and foreign key constraints, and copy schemas with as and where 1=2.
Learn to use where keyword to filter data on the sales order table with conditions such as greater than 1000, between 1000 and 2000, not null, like, and not in.
Sort query results with order by and control rows using limit, offset, or fetch, demonstrated by sorting on gross sales and platform across the sales data.
Learn how to use group by and having in PostgreSQL to perform aggregations, such as total gross sales by platform, with filtered results.
Explore how to determine a table's granularity by examining the schema, forming hypotheses about the grain, and validating with group by and having counts using a sales order example.
Explore joins in Postgres, including inner, left, right, full outer, self, and cross joins, with practical syntax and examples using pgAdmin4.
Learn how union, union all, intersect, and except combine query results by appending rows, deduplicating outputs, finding intersections, and computing differences across data snapshots.
Understand the writing and execution sequence of SQL queries in pgAdmin4, mastering the keyword order from select to limit and how the server processes joins and filters.
Explore case when statements in Postgres to implement if-else logic within a single query. Learn syntax with when-then-else, nested cases, multiple conditions, optional else, and aggregation using group by.
Learn to use where with left, right, or full outer joins in PostgreSQL, compute 2014 first purchases, and determine the 30-day repeat rate while preserving nulls.
Explore subqueries in Postgres for data analytics, learning to nest queries, filter orders by average sales, and use exists, any, and all in where clauses and joins.
Learn a practical cross join workflow to identify sister subcategories across furniture, technology, and office supplies by computing Euclidean distances and ranking nearest matches.
Explore self join and natural join in Postgres, using inner joins on the same table and joins without an on condition, with examples from demographics by state.
A Common Table Expression (CTE) is temporary result set which can be referenced within another SQL statement.
They are temporary in the sense that they only exist during the execution of the query
Partitioning a table improves the query performance.
The data gets stored into different chunks for a partitioned table.
When we query the table by filtering over partitioned field, only a small chunk of data is read instead of all the records.
This course is intended for -
Anyone willing to get a good hands-on experience with PostgreSQL (postgres is short).
Are working, or are interested in working in the data analytics or related industry.
Those who wants to learn the SQL concepts by solving real-world business problems and not just hypothetical problems.
People who wants to gain expertise to dive into data and extract important findings.
There is no prior coding experience mandatorily required to start this course. Only the motivation to learn is enough :)
The aim to have all the concepts clarified, and at the same time, keeping the content very interactive.
The datasets considered is very practical in nature.
The assignment are designed in such a way, to give an idea of exact problems that the analytics professionals face on day-to-day basis.
Downloadable SQL files are attached with all the lessons. This will save time re-writing the codes.
The course will serve as a way to gain problem solving capabilities.
My learnings from last 7 years working in data analytics industry has been tutored in this course
After successful completion of this course -
You will be able to translate business problem statements into data driven solutions. For example, if someone asks you a use case of cross join, you can elaborate in very concise and practical way.
You will be much more confident using SQL irrespective of the database you work on.
Tools required -
PGAdmin 4,
PostgreSQL.
(There is a dedicated section in this course on setting up the environment and loading the sample dataset).
The course structure is divided into 3 sections -
Beginners,
Intermediate
Advance.
Based on the current level of experience, you can choose to start from either of these and to also jump between sections or lectures as you seem fit. There is no dependency between the lectures so you can focus on your specific learning goals.
We've included the SQL script file which is showcased in the lecture. Use these to save time re-writing the codes.
Make the most use of the available Udemy tools like Q&A, Assignment, Notes. to clarify the doubts and self evaluate.
I would also like to hear the feedback on this course to make it even better and more exhaustive with regular updates. Please provide feedbacks via ratings, reviews or direct messages.
We aim for 100% student satisfaction, you can request a 30-day refund if you are not satisfied with the course material.