Tutor SQL

Find answers to commonly asked SQL interview questions.

[Tutor SQL @TutorSql]

How can you find the 3rd highest salary in Oracle using an analytic function?
#DenseRank #SQL #TutorSQL #Oracle #Analytics #Database #DataAnalyst #DataScientist

[Tutor SQL @TutorSql]

@swapnakpanda I'm encountering an error when attempting to load the SQL page.

[Tutor SQL @TutorSql]

Q9: Write an SQL query using CASE to calculate the grade for each student:
If the avg of math and science scores is greater than or equal to 90, assign A grade.
If the avg is between 80 & 89, assign B grade
If the avg is between 70 & 79, assign C grade
Otherwise, assign 'D'.

[Connor on SQL and Database @connor_mc_d]

The database optimizer never ceases to blow my mind. TIL that we can refactor some DECODEs into simpler expressions. #database #sql 🔥

[Tutor SQL @TutorSql]

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[Tutor SQL @TutorSql]

Q8: Write an SQL query to calculate the month-over-month percentage growth for each product's sales. You should retrieve the product_id, sale_date, and percentage growth from the previous month's sales using the LEAD and LAG functions.

[Tutor SQL @TutorSql]

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[Tutor SQL @TutorSql]

Protip: 😎 Do you know that using the LEAD and LAG functions effectively and considering both the PARTITION BY and ORDER BY clauses, you can perform robust time-based and comparative analysis on your data in Oracle SQL. 🚀

[Tutor SQL @TutorSql]

If you find these interview questions helpful and insightful, consider following us on Twitter for more engaging content and valuable insights into SQL and database-related topics! 📚🔍 #SQLInterviewQuestions
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[Tutor SQL @TutorSql]

Q7: In Oracle SQL, the LIMIT function is unavailable, but there's an equivalent approach using the ROWNUM technique. Consider a table named "products" as per the screenshot.
Write an SQL query to retrieve the top 3 cheapest products using the ROWNUM technique (equi. to LIMIT).

[Tutor SQL @TutorSql]

The expected output values are for illustrative purposes and may vary based on the provided data.)
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[Sanyam Bhutani @bhutanisanyam1]

A master class in creating Synthetic datasets with LLMs! 🐐

ToolLLM paper has been popular for creating the strongest API following models.

I think there’s an incredibly underrated side to it, here’s my summary:

- The paper aims to improve API following capabilities of open source models

- The first step is to collect a large set of API call examples along with its documentation

- Low quality ones that don’t work are filtered out

- ChatGPT is used to annotate and provide reasoning for examples

- Depth First Search, a new prompting strategy is the key to making the above step work

- The open source models are fine tuned on these

- Finally a retrieval model is trained to fetch the correct APIs to call during inference

The paper has many other interesting angles as well. For me the pipeline above was a master class on how to create synthetic datasets with Large Language Models:

https://t.co/Fokn3h4AwA

[Tutor SQL @TutorSql]

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[Tutor SQL @TutorSql]

Question #6: Imagine you have a table named "events" with the attached structure and data:

Write an SQL query to extract the hours, minutes, and seconds from the "event_date" column and display them in separate columns in the result set.

Hint: Use the TO_CHAR function.

[Tutor SQL @TutorSql]

The result displays the "event_id," "event_date," and the extracted hours, minutes, and seconds from the "event_date" column in the specified format with leading zeros as required.
#tutorsql #to_char