Discuss Databricks Databricks Certified Data Engineer Associate Exam Topic 2 Question 59

Which option best SQL keywords can be used to convert a table from a long format to a wide format?

Suggested Answer: A

The SQL keyword that can be used to convert a table from a long format to a wide format isPIVOT.The PIVOT clause is used to rotate the rows of a table into columns of a new table1.The PIVOT clause can aggregate the values of a column based on the distinct values of another column, and use those values as the column names of the new table1.The PIVOT clause can be useful for transforming data from a long format, where each row represents an observation with multiple attributes, to a wide format, where each row represents an observation with a single attribute and multiple values2.For example, the PIVOT clause can be used to convert a table that contains the sales of different products by different regions into a table that contains the sales of each product by each region as separate columns1.

The other options are not suitable for converting a table from a long format to a wide format.CONVERT is a function that can be used to change the data type of an expression3.WHERE is a clause that can be used to filter the rows of a table based on a condition4.TRANSFORM is a keyword that can be used to apply a user-defined function to a group of rows in a table5. SUM is a function that can be used to calculate the total of a numeric column.

1:PIVOT | Databricks on AWS

2:Reshaping Data - Long vs Wide Format | Databricks on AWS

3:CONVERT | Databricks on AWS

4:WHERE | Databricks on AWS

5:TRANSFORM | Databricks on AWS

: [SUM | Databricks on AWS]

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25 comments · newest first

Kenny 3 months ago

"CASE" can also be useful for conditional formatting.

Serita 3 months ago

What about "GROUP BY"? It can help too, but not as effectively.

Rosio 4 months ago

Agreed! "PIVOT" makes it easy to reshape data.

Rochell 5 months ago

I think "PIVOT" is the best choice. It’s straightforward.

Lynelle 5 months ago

Don't forget about CASE statements too!

Adelle 5 months ago

Wait, can you really convert long to wide with just SQL?

Rodney 6 months ago

I thought you could just use GROUP BY instead?

Nobuko 6 months ago

Totally agree, PIVOT is the way to go.

Lauran 6 months ago

You can use PIVOT for that!

Marshall 6 months ago

Haha, I bet the answer is "All of the above" - they just love tricking us with those!

Shonda 6 months ago

Isn't it Reshape and Widen? I'm pretty sure that's the way to go.

Yolando 6 months ago

Hmm, I think Transpose and Melt might do the trick.

Brett 7 months ago

Pivot and Unpivot, of course!

Elouise 7 months ago

I definitely remember using aggregate functions in these types of questions, but I'm confused about how they fit with the wide format conversion.

Aleisha 7 months ago

I feel like CASE statements could also play a role in converting formats, but I can't recall the exact syntax.

Shawnee 8 months ago

I remember practicing a similar question where we had to transform data, and I think GROUP BY was involved too.

Alesia 8 months ago

I think we might need to use the PIVOT function for this, but I'm not entirely sure how it works in SQL.

Johnna 8 months ago

I feel pretty confident about this. I think using a combination of GROUP BY and CASE statements could be an effective way to convert the table format.

Denna 8 months ago

This seems like a tricky one. I'm going to review my notes on data transformation techniques and see if I can come up with a solid strategy.

Jesusita 8 months ago

Okay, I've got a few ideas on how to tackle this. I'll start by considering the PIVOT and UNPIVOT keywords, and see if those might work for this type of conversion.

Yan 9 months ago

Hmm, converting from long to wide format? I'm a little unsure about the best SQL keywords to use for that. I'll need to think it through carefully.

Precious 9 months ago

I think I know how to approach this, but I want to double-check my understanding before I start writing anything.

Rebbeca 3 months ago

↳ replying to Precious

Don't forget about CASE statements too, they can help!

Lorean 3 months ago

↳ replying to Precious

Yeah, PIVOT is definitely the way to go!

Lisandra 3 months ago

↳ replying to Precious

I believe you can use the PIVOT keyword for that.

Databricks Certified Data Engineer Associate Exam - Topic 2 Question 59 Discussion