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CS614 QUIZ 1 SOLVED
1. incorporates the concept of product quality, process control, quality assurance, and quality improvement.
a) Total Quality Management
b) Intrinsic Data Quality Management
c) Realistic Data Quality Management
d) Strong Data Quality Management
2. The extent to which data is in appropriate languages, symbols and units, and the definitions are clear is known as .
a) Interpretability
b) Uniqueness
c) Accessibility
d) Consistency
3. The degree to which values are present in the attributes that require them is known as .
a) Completeness
b) Uniqueness
c) Accessibility
d) Consistency
4. The dimension represents data correctness.
a) Free-of-error
b) Completeness
c) Consistency
d) Correctness
5. In B-tree index, the lowest level index blocks are called leaf blocks, and these blocks contain:
a) NULL value to make the leaf terminal node
b) Every indexed data value and a corresponding
c) Every indexed data value and pointer to next level block
d) Every indexed data value and pointer to root block
6. Data is the on which a Data Warehouse (DWH) runs.
a) Fuel
b) Element
c) Component
d) Entity
7. In context of data parallelism to get a speed-up of N with N partitions, it must be ensured that:
a) There are enough computing resources
b) Query-coordinator is very fast as compared to query servers
c) Work done in each partition almost same
d) All of the given options
8. Which of the following is not an activity of Data Quality Analysis Project?
a) "Define"
b) "Measure"
c) "Analyze"
d) Compression
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9. Which of the following is not a Data Quality Validation Technique?
a) Referential Integrity
b) Using Data Quality Rules
c) Data Histograming
d) Indexes
10. One of the preconditions to decide about operations to be parallelized is that
a) Operation can be implemented independently of each other
b) Output of one operation becomes the input of other
c) Operations share same memory location
d) Operations share the same namespace
11. do not (typically) keep the index values in sorted order
a) Dense index
b) Sparse index
c) B-Tree Index
d) Hash-Based index
12. Parallelism can be exploited if there is:
a) Symmetric multi-processors (SMP)
b) Sufficient I/O bandwidth
c) Underutilized or intermittently used CPUs
d) All of the given options
13. Which of the following is NOT one of the parallel hardware architectures?
a) Symmetric Multi-Processing
b) Massively Parallel Processing
c) Non-uniform Memory Access
d) Shared Memory
14. Two interesting examples of quality dimensions that can make use of the min operator are.
a) Believability and appropriate amount of data
b) Believability and Consistency
c) Believability and Redundancy
d) Reliability and appropriate amount of data
15. As the number of processors increase the speedup should also increase. Thus, we should have linear speedup. Which of the following is NOT one of the barriers to achieve this linear speed-up?
a) Amdahl Law
b) Startup
c) No Interference
d) Skew
16. In index, the ith bit is set to “1” if the ith row of the base table has the value for the indexed column
a) Inverted index
b) Bitmap index
c) Cluster index
d) Join index
17. lists each term in the collection only once and then shows a list of all the documents that contain the given term.
a) Inverted index
b) Bitmap index
c) Cluster index
d) Join index
18. The exact formula for Speed-up is:
a) (Time on Serial Processor) / (Time on parallel processors)
b) (Time on Serial Processor) * (Time on parallel processors)
c) (Time on Serial Processor) + (Time on parallel processors)
d) (Time on Serial Processor) - (Time on parallel processors)
19. is the degree to which data accurately reflects the real-world object that the data represents?
a) Intrinsic data quality
b) Realistic data quality
c) Strong data quality
d) Weak data quality
20. Assume a company with a multi-million row customer table i.e., n rows. Checking for Referential Integrity (RI), using a smart technique with some kind of a tree data structure would require time.
a) O(log n)
b) O(n)
c) O(1)
d) None of the given
21. Which of the following is NOT one of the variants of Nested-loop join?
a) Naive nested-loop join
b) Indexed nested-loop join
c) Temporary index nested-loop join
d) Binary index nested-loop join
22. “More resources mean proportionally less time for given amount of data” that statement refers to
a) Scale-Up
b) Speed-Up
c) Size-Up
d) Over-Utilized system
23. The optimizer uses a hash join to join two tables if they are joined using an equijoin and
a) outer table has less number of rows
b) inner table has less number of rows
c) cardinality of table is equal
d) large amount of data needs to be joined
24. “If resources increase in proposition to increase in data size, time is constant”. The statement refers to
a) Scale-up
b) Speed-up
c) Size-up
d) Over-utilized system
25. If a product meets formally defined “requirement specifications”, yet fails to be a quality product form the customer’s perspective, this means the requirements were .
a) Defective
b) Unclear
c) Unrefined
d) Undefined
26. is the extent to which data is regarded as true and credible?
a) Believability
b) Completeness
c) Accessibility
d) consistency
27. Which is not a/an data quality validation technique?
a) Consistency integrity
b) Referential integrity
c) Attribute domain
d) Using data quality rules
28. Which of the following is not an “Orr’s law of data quality”?
a) Data that Is not used is cannot be correct
b) Data quality is a function of its use not its collection
c) Data will be no better than its most stringent use
d) Data duplication can be harmful for the organization
29. is known as state of being only one of its kind or being without an equal or parallel.
a) Completeness
b) Uniqueness
c) Accessibility
d) Consistency
30. Which is not a/an characteristics of data quality?
a) Reliability
b) Uniqueness
c) Accessibility
d) Consistency
31. If every key in the data file is represented in the index file then it is called
a) Dense Index
b) Sparse Index
c) Inverted Index
d) A Multi-level Sparse Index
32. One of the main reasons for the failure of DWH deployment is
a) Data quality
b) Data integrity
c) Data duplication
d) Data anomaly
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