Data Warehousing and Data Mining · Unit 4 · 4 hrs
Data Cube Technology
Exam-focused notes for Data Cube Technology (Data Warehousing and Data Mining, CSC420): what the TU syllabus asks and how it has actually been tested, with 7 solved past questions from this unit.
What this unit covers
- Efficient method for data cube computation
- Cube materialization (Introduction to Full cube, Iceberg cube, Closed cube, Shell cube)
- General strategies for cube computation
- Attribute oriented induction for data characterization
- Mining class comparison
- Discriminating between different classes
General strategies for cube computation
Explain the general strategies for cube computation. [5]
Data cube computation is an essential task in data warehouse implementation. The precomputation of all or part of a data cube can greatly reduce response time and enhance the performance of OLAP. However, it is challenging because it may require huge comput...
Full solved answer →Explain the optimization techniques in data cube computation. [5]
Data cube computation is an essential task in data warehouse implementation. Precomputing all or part of a data cube can greatly reduce response time and enhance OLAP performance. However, it is challenging because it may require huge computational time and...
Full solved answer →Attribute oriented induction for data characterization
Distinguish between data characterization and data discrimination. What are the challenges of multimedia mining? [5]
--- Both are descriptive data mining functions used to summarize and compare data. They are distinguished as follows: Aspect Data Characterization Data Discrimination --------- Definition Summarization of the general characteristics or features of a target ...
Full solved answer →Cube materialization
How many cuboids are possible from 5-dimensional data? Discuss the concept of full cube and iceberg cube. [5]
- Number of dimensions: $n = 5$ - (No concept hierarchies specified, so we assume one level per dimension.) --- A data cube of $n$ dimensions (without concept hierarchies) contains $2^n$ cuboids, because each dimension can either be included or excluded fro...
Full solved answer →What are the choices for data cube materialization? Explain the strategies for cube computation. [5]
Data cube computation is an essential task in data warehouse implementation. The precomputation (materialization) of all or part of a data cube can greatly reduce response time and enhance OLAP performance. However, it is challenging because it may require ...
Full solved answer →Efficient method for data cube computation
Suppose that we have 5 dimensional data. What will be total number of cuboids generated? If we consider each dimension has 5 levels, what will be the number of cuboids generated? [5]
- Number of dimensions: $n = 5$ - Number of levels per dimension (Part 2): $L = 5$ for each dimension --- For a data cube of $n$ dimensions where each dimension has no associated concept hierarchy, the total number of cuboids is: $$\text{Total Cuboids} = 2^...
Full solved answer →Describe the significances of pre-computation of data cube. [5]
Data cube computation is an essential task in data warehouse implementation. Pre-computation refers to computing all or part of a data cube in advance (offline), so that query results can be retrieved quickly during online analytical processing (OLAP) rathe...
Full solved answer →Make Unit 4 stick
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