Retail sales data mart
Model raw orders into a star schema with fact and dimension tables, then answer 25 business questions with SQL.
From your first SELECT to stored procedures, data models and fast queries.
WITH monthly AS ( SELECT customer_id, DATETRUNC(month, order_date) AS month, SUM(amount) AS revenue FROM sales.orders GROUP BY customer_id, DATETRUNC(month, order_date))SELECT *, LAG(revenue) OVER (PARTITION BY customer_id ORDER BY month) AS prev_monthFROM monthly;
SQL is the language every data job is built on. In this course you write SQL from day one on real business data, then move into window functions, data modelling, stored procedures and performance tuning. By the end you can answer the SQL questions interviewers actually ask, and you have a data mart project to show for it.
You learn by doing: every week has hands-on exercises on Google Classroom, and every module ends with something you built yourself.
Filter, sort, aggregate and join tables to answer real business questions.
Rankings, running totals, LAG and LEAD, de-duplication and top N per group.
Normalisation, keys, star schemas, facts, dimensions and slowly changing dimensions.
Variables, transactions, error handling and MERGE for repeatable data loads.
Read execution plans, add the right indexes and write SARGable filters.
Practise the questions and live coding rounds used by data teams.
A clear plan from the first session to the last. The pace adapts to you: if you already know a topic we move faster, and if something needs more time we take it.
Real projects you can put on GitHub and explain with confidence in interviews.
Model raw orders into a star schema with fact and dimension tables, then answer 25 business questions with SQL.
Stored procedures that check new loads for duplicates, missing keys and bad dates, and write results to an audit table.
Take slow queries on a table with millions of rows and make them fast using plans, indexes and rewrites.
The same tools used by data teams in real companies.
Every session is just you and me, never a batch. No recordings, so we can talk openly about your code.
Each session is 1 hour 15 minutes, on weekdays, weekends or both. We agree the schedule before starting.
Assignments, projects, quizzes, interview questions and homework, all organised in one place.
You build projects like the ones companies run, and get feedback on your code and design.
Common questions, live coding practice and mock interviews with honest feedback.
CV, LinkedIn, applications and interviews. I stay with you until you are hired, as long as you do the work.
You pay for your time with me, not per course. All prices are in US dollars.
Senior Data Engineer at Algo · Lahore, Pakistan
I build data platforms with Snowflake, Azure Databricks, Azure Data Factory and Microsoft Fabric every day, and I have been mentoring since 2021. I teach what I use at work, and I stay with you until you land the job.
We use Microsoft SQL Server with T-SQL. The concepts carry over directly to Azure SQL, Snowflake, PostgreSQL and MySQL, and I point out the differences as we go.
Yes. SQL is the best first language for data work, and this course starts from zero. Most students write useful queries in the first week.
Python is the usual next step, then Power BI or a cloud platform like Azure Databricks or Snowflake, depending on the role you want.
200 USD per month whichever course you choose. You can also pay 100 USD every 15 days or 50 USD per week. All prices are in US dollars wherever you live.
If the training is not right for you after the first session, you get a full refund. After that, payments already used for completed sessions are not refunded, but unused prepaid time can be refunded.
Yes. As long as you attend your sessions and complete the assignments and projects, I keep helping you with CV, LinkedIn, mock interviews and job applications until you are hired.
Yes. Students join from many countries. We pick session times that work for your time zone before we start.
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View course →Tell me your goals and your time zone. We plan your schedule together, and your first session can start this week.