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Previous year question hub

Data Transformation and Warehousing - Database Management and Warehousing - Data Science & Artificial Intelligence Previous Year Questions

Practice Data Transformation and Warehousing - Database Management and Warehousing - Data Science & Artificial Intelligence previous year questions organised from real papers, with year-wise coverage and clear topic navigation.

2Papers
2Years
3Questions
1Topics

Data Transformation and Warehousing question pattern

Every graph below is calculated only from this selection.

Questions by year

Year-wise coverage for Data Transformation and Warehousing. Each bar uses a separate theme-derived color.

Difficulty distribution

How the classified questions are distributed by difficulty.

Medium 2 66.7%
Easy 1 33.3%

Question type distribution

MCQ, numerical, multiple-select and other formats found in these papers.

MCQ 3 100%

Subject weightage

Top subjects by unique question coverage.

Data Science & Artificial Intelligence
3 Qs

Most asked topics

Top topics across the included previous year papers.

Database Management and Warehousing
3 Qs

Subtopic coverage

Top subtopics inside this exact selection.

Data Transformation and Warehousing
3 Qs

Paper coverage

Question coverage for the most populated papers. Every active PYP paper remains listed below.

Data Science and Artificial Intelligence (DA) 2026
2 Qs
Data Science & Artificial Intelligence (DA) 2025
1 Qs

Included previous year papers

Newest papers appear first. Sort by year, question coverage or name.

PaperYear / sessionQuestions in this viewOpen
Data Science and Artificial Intelligence (DA) 202620262View paper
Data Science & Artificial Intelligence (DA) 202520251View paper

All Data Transformation and Warehousing previous year questions

Practice every matching question in batches of 20, with every available option.

1
2025 · Data Science & Artificial Intelligence · Database Management and Warehousing · Data Transformation and Warehousing
Data Science & Artificial Intelligence (DA) 2025
Consider a fact table in an OLAP application: Facts(D1, D2, val), where D1 and D2 are its dimension attributes and val is a dependent attribute. Suppose attribute D1 takes 3 values and D2 takes 2 values, and all combinations of these values are present in the table Facts. How many tuples are there in the result of the following query?

SELECT D1, D2, sum(val)
FROM Facts
GROUP BY CUBE (D1, D2);
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2
2026 · Data Science & Artificial Intelligence · Database Management and Warehousing · Data Transformation and Warehousing
Data Science and Artificial Intelligence (DA) 2026
Consider that the visualization of a 3-dimensional data cube is showing Sales Quantity for each combination of the attributes Product Type, Month and Country.

From this, if we want to further visualize the Sales Quantity for each combination of Product Type, Month and State, which of the following OLAP operations should be performed?
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3
2026 · Data Science & Artificial Intelligence · Database Management and Warehousing · Data Transformation and Warehousing
Data Science and Artificial Intelligence (DA) 2026
Consider the concept hierarchies as shown in the figure.
Which of the following options denotes the total number of possible data cuboids from these concept hierarchies?

Question diagram

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