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SQL aggregation and join queries for data analysis.
Use GROUP BY clause for aggregation
Use aggregate functions like SUM, AVG, COUNT, etc.
Use JOIN clause to combine data from multiple tables
Types of joins in SQL include inner join, left join, right join, and full outer join.
Inner join: Returns rows when there is a match in both tables.
Left join: Returns all rows from the left table and the matched rows from the right table.
Right join: Returns all rows from the right table and the matched rows from the left table.
Full outer join: Returns all rows when there is a match in either table.
You can import data in Power BI using API by connecting to the API endpoint and specifying the required parameters.
Use the 'Get Data' option in Power BI to connect to the API endpoint
Specify the required authentication method (e.g. API key, OAuth)
Select the data you want to import and transform it as needed
Refresh the data periodically to keep it up to date
Extract numbers from strings in SQL
Use the SQL function REGEXP_REPLACE to remove non-numeric characters
Use the SQL function REGEXP_SUBSTR to extract numbers from strings
Consider using regular expressions to handle different number formats
Window functions in SQL are used to perform calculations across a set of table rows related to the current row.
Window functions operate on a set of rows related to the current row
They can be used to calculate running totals, ranks, and averages
Common window functions include ROW_NUMBER(), RANK(), DENSE_RANK(), and NTILE()
They are typically used with the OVER() clause to define the window frame
Joins are used to combine rows from two or more tables based on a related column between them.
Inner Join: Returns rows when there is a match in both tables.
Left Join: Returns all rows from the left table and the matched rows from the right table.
Right Join: Returns all rows from the right table and the matched rows from the left table.
Full Outer Join: Returns rows when there is a match in either table.
Cross Join: Retur
Order of execution in SQL refers to the sequence in which different clauses are processed in a SQL query.
1. FROM clause is processed first to retrieve data from the specified tables.
2. WHERE clause is processed next to filter the rows based on specified conditions.
3. GROUP BY clause is processed to group the rows based on specified columns.
4. HAVING clause is processed to filter the grouped rows based on specified cond...
Use indexes, limit columns in SELECT, avoid using SELECT *, optimize joins
Use indexes on columns frequently used in WHERE clauses
Limit columns in SELECT to only those needed
Avoid using SELECT * to retrieve all columns
Optimize joins by using INNER JOIN instead of OUTER JOIN when possible
I applied via IIM Jobs and was interviewed before Sep 2021. There were 3 interview rounds.
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posted on 5 May 2017
I was interviewed in Aug 2016.
I have the necessary skills, experience, and passion to contribute to the company's growth and success.
I have a proven track record of achieving targets and delivering results.
I possess excellent communication and interpersonal skills, which enable me to work effectively with colleagues and clients.
I am a quick learner and can adapt to new technologies and processes easily.
I am passionate about my work and always striv...
I have the necessary skills, experience, and passion to contribute to the company's growth and success.
I have relevant experience in the industry
I possess the required skills and knowledge for the job
I am a quick learner and can adapt to new situations easily
I am passionate about the company's mission and values
I am a team player and can work collaboratively with others
Go for general aptitude questions.
I applied via Naukri.com and was interviewed in Dec 2019. There were 4 interview rounds.
posted on 10 Dec 2021
I applied via Referral and was interviewed before Dec 2020. There were 3 interview rounds.
posted on 3 Jun 2021
I applied via Referral and was interviewed in May 2021. There were 3 interview rounds.
Append and Merge are two methods used to combine data from multiple sources into a single dataset.
Append adds new rows to an existing dataset.
Merge combines two or more datasets based on a common column or key.
Append is useful when adding new data to an existing dataset, while Merge is useful for combining datasets with related information.
Example: Appending new sales data to an existing sales dataset.
Example: Merging ...
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