Deal of The Day! Hurry Up, Grab the Special Discount - Save 25% - Ends In 00:00:00 Coupon code: SAVE25
Welcome to Pass4Success

- Free Preparation Discussions
Mail Us support@pass4success.com
Location US
Mob_nav_barsMENU

Microsoft DP-600 Exam - Topic 1 Question 43 Discussion

Actual exam question for Microsoft's DP-600 exam
Question #: 43
Topic #: 1
[All DP-600 Questions]

What should you recommend using to ingest the customer data into the data store in the AnatyticsPOC workspace?

Show Suggested Answer Hide Answer
Suggested Answer: D

For ingesting customer data into the data store in the AnalyticsPOC workspace, a dataflow (D) should be recommended. Dataflows are designed within the Power BI service to ingest, cleanse, transform, and load data into the Power BI environment. They allow for the low-code ingestion and transformation of data as needed by Litware's technical requirements. Reference = You can learn more about dataflows and their use in Power BI environments in Microsoft's Power BI documentation.


by Artie at Nov 20, 2025, 10:50 AM

Limited Time Offer

25%

Off

Get Premium DP-600 Questions as Interactive Web-Based Practice Test or PDF

Contribute your Thoughts:

0/2000 characters
Submit Cancel
Frank
2 days ago
Wait, can Spark notebooks even handle this?
upvoted 0 times
...
Levi
7 days ago
Dataflows are super efficient for ingestion!
upvoted 0 times
...
Edna
25 days ago
Stored procedures are outdated for this.
upvoted 0 times
...
Johnna
1 month ago
D) a dataflow, because who doesn't love a good old-fashioned data flow?
upvoted 0 times
...
Herman
1 month ago
A) a stored procedure? Really? That's so 2000s.
upvoted 0 times
...
Chery
1 month ago
C) a Spark notebook would be overkill for this use case.
upvoted 0 times
...
Mohammad
2 months ago
D) a dataflow seems like the most straightforward option here.
upvoted 0 times
...
Brandee
2 months ago
B) a pipeline that contains a KQL activity is the way to go for ingesting customer data.
upvoted 0 times
...
Terrilyn
2 months ago
I have a vague memory of Spark notebooks being used for data ingestion, but I don't know if that's the right choice here.
upvoted 0 times
...
Vesta
2 months ago
I feel like stored procedures could work, but they might not be the most efficient for this scenario.
upvoted 0 times
...
Val
2 months ago
I remember practicing a question about using pipelines, but I can't recall if KQL activities were specifically mentioned.
upvoted 0 times
...
Adell
2 months ago
I feel pretty confident about this one. I think the dataflow is the way to go - it's designed specifically for data ingestion and transformation.
upvoted 0 times
...
Sina
3 months ago
A stored procedure could work, but I'm not sure if that's the best approach for this type of data ingestion task. I'll have to consider the trade-offs.
upvoted 0 times
...
Justine
3 months ago
I'm leaning towards the pipeline with a KQL activity. That seems like the most straightforward way to ingest the data, but I'll double-check the details.
upvoted 0 times
...
Jesse
3 months ago
I think option B is the best choice. KQL is powerful for querying.
upvoted 0 times
...
Veronika
3 months ago
I think a dataflow might be the best option since it can handle transformations easily, but I'm not entirely sure.
upvoted 0 times
...
Linsey
3 months ago
I think a pipeline with KQL is the way to go.
upvoted 0 times
...
Tuyet
4 months ago
Hmm, I'd go with B) - can't beat that good old Kusto Query Language!
upvoted 0 times
...
Nickolas
4 months ago
Not sure about that recommendation, seems risky.
upvoted 0 times
...
Carisa
4 months ago
I'm a bit confused on the differences between a pipeline, dataflow, and Spark notebook. I'll need to review those concepts again.
upvoted 0 times
...
Meghan
4 months ago
Hmm, this seems like a tricky one. I'll need to think through the pros and cons of each option carefully.
upvoted 0 times
...

Save Cancel