Upwork DATA WAREHOUSING TEST 2018

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1. Which of the following are the modes of OLAP?

Answers:

1. MOLAP
2. ROLAP
3. KOLAP

2. OLAP queries can be characterised as on-line transactions that do not:

Answers:

1. Access small amounts of data
2. Analyse the relationships between many types of business elements e.g. sales, products, regions, and channels
3. Compare aggregated data over hierarchical time periods e.g. monthly, quarterly, yearly
4. Present data in different perspectives e.g. sales by region vs. sales by channels by product within each region
5. Respond quickly to user requests, so that users can pursue an analytical thought process without being stymied by the system

3. Normalisation is:

Answers:

1. The process of organising data in accordance with the rules of a relational database
2. The process of cleansing the data
3. The process of integrating the data into the datawarehouse from legacy systems
4. The process of compressing the data
5. The process of eliminating invalid data before it is introduced into the data warehouse

4. Which of the following would not be considered as a variable affecting the design of an OLAP system?

Answers:

1. Query demand
2. Source of data
3. Number of dimensions
4. Atomic data volume
5. Data volatility

5. A slice is:

Answers:

1. A subset of a multi-dimensional array corresponding to a single value for one or more members of the dimensions not in the subset
2. A subset of a multi-dimensional array corresponding to multiple values for one or more members of the dimensions not in the subset
3. A subset of a multi-dimensional array corresponding to a single value for one or more members of the dimensions in the subset
4. A subset of a multi-dimensional array corresponding to multiple values for one or more members of the dimensions in the subset
5. A subset of a multi-dimensional array not corresponding to a single value for one member of the dimensions not in the subset

6. Which of the following techniques can be used to improve query performance?

Answers:

1. Denormalization
2. Partitioning
3. Summarization
4. Denormalization and Partitioning
5. Denormalization, Partitioning and Summarization

7. The term OLAP was coined by:

Answers:

1. Date
2. Codd
3. IBM
4. Oracle
5. Microsoft

8. The main objects used by OLAP programs are:

Answers:

1. Multidimensional cubes
2. Metadata
3. RDBMS tables
4. Fact tables
5. Pivot tables

9. Granularity refers to the:

Answers:

1. Validity of the data stored in a data warehouse
2. The level of detail of the facts stored in a data warehouse
3. The timeliness of the data stored in a data warehouse
4. The redundancy of the data stored in a data warehouse
5. Compactness of the data stored in a data warehouse

10. Which of the following queries would be correlated with a Data warehouse?

Answers:

1. What is the current account balance of this customer?
2. How many customers have not paid their balances on time?
3. What is the total number of customers in the middle region?
4. Which product line sells best in middle region and how does this correlate to demographic data?
5. Which customer makes the maximum purchases?

11. Data Volatility describes:

Answers:

1. The degree to which data and data structures change over time
2. The redundancy of the data
3. The volume of the data
4. The compactness of the data
5. The validity of the data

12. A data warehouse is a “subject-oriented, integrated, time-variant, non-volatile collection of data in support of management’s decision-making process”. The term non-volatile means that:

Answers:

1. The data is refreshed often
2. The data is backed up often
3. The data is deleted often
4. The data is rarely changed
5. The data is of low volume

13. Which of the following is not true regarding an OLTP system?

Answers:

1. OLTP is generally regarded as unsuitable for data warehousing
2. OLTP systems can be repositories of facts and historical data for business analysis
3. The purpose of an OLTP system is to run day-to-day operations
4. The Data Model of an OLTP system is normalised
5. OLTP offers large amounts of raw data

14. A data warehouse includes data from various sources including legacy systems. Legacy systems implies:

Answers:

1. Systems that have been developed at different times by different people for a variety of purposes
2. Systems which are no longer useful
3. Systems whose data is outdated
4. Systems whose technology is outdated
5. Systems whose data is corrupt

15. A multi-dimensional data set is sparse if:

Answers:

1. The data to be analysed is less in volume
2. If a relatively high percentage of the possible combinations (intersections) of the members from the data set’s dimensions contain missing data
3. If a relatively high percentage of the possible combinations (intersections) of the members from the data set’s dimensions contain invalid data
4. If a relatively high percentage of the possible combinations (intersections) of the members from the data set’s dimensions contain valid data
5. If a relatively high percentage of the possible combinations (intersections) of the members from the data set’s dimensions contain outdated data

16. A data warehouse is a “subject-oriented, integrated, time-variant, non-volatile collection of data in support of management’s decision-making process”. The data within the warehouse is integrated in that:

Answers:

1. Users from all departments help to create the database
2. Data from various departments is collected into the warehouse
3. The final product is a fusion of various legacy system information into a cohesive set of information
4. Every user has access to the data in the warehouse
5. It contains the data of the enterprise in its entirety

17. Normalization applied to the dimension tables of a star schema is known as:

Answers:

1. Snowflaking
2. Synchronization
3. Slicing and Dicing
4. Replication
5. Data transformation

18. Replication refers to the:

Answers:

1. Physical copying of data from one database to another
2. Cleansing of the data
3. Integration of data from various sources into the data warehouse
4. Analysis of the data
5. Recovery of data

19. ROLAP stands for:

Answers:

1. Recyclic On-line Analytical Processing
2. Relational On-line Analytical Processing
3. Reduced On-line Analytical Processing
4. Rotated On-line Analytical Processing
5. Redundant On-line Analytical Processing

20. In a star schema, a table which contains data about one of the dimensions is called a:

Answers:

1. Fact table
2. Meta table
3. Data Dictionary
4. Pivot table
5. Dimension table

21. Which of the following would not be an application of Data Mining in the banking field?

Answers:

1. Detect patterns of fraudulent credit card use
2. Ascertaining the number of transactions made in a day
3. Determine credit card spending by customer groups
4. Find hidden correlation between different financial indicators
5. Predict the customers likely to change their credit card affiliation

22. A Star Schema is a database design that consists of:

Answers:

1. A fact table
2. Dimension tables
3. Pivot tables
4. A fact and pivot tables
5. A fact table and one or more dimension tables

23. HOLAP stands for:

Answers:

1. Hierarchical On-line Analytical Processing
2. Hybrid On-line Analytical Processing
3. Horizontal On-line Analytical Processing
4. Hyper On-line Analytical Processing
5. HyperCube On-line Analytical Processing

24. A structure that stores multi-dimensional information, having one cell for each possible combination of dimensions is known as:

Answers:

1. Table
2. Section
3. Partition
4. Cube
5. Repository

25. Which Data Mining function/technique is used to analyse a collection of records over a period of time?

Answers:

1. Classification
2. Associations
3. Sequential/Temporal patterns
4. Clustering
5. Segmentation

26. Which technique of Data Mining involves developing mathematical structures with the ability to learn?

Answers:

1. Clustering and Segmentation
2. Neural Networks
3. Fuzzy Logic
4. Linear Regression Analysis
5. Rule based Analysis

27. A datawarehouse should be able to implement advanced query functionality. This means :

Answers:

1. The RDBMS must provide a complete set of analytic operations including core sequential and statistical operations
2. The RDBMS must not have any architectural limitations
3. The RDBMS server must support hundreds, even thousands, of concurrent users while maintaining acceptable query performance
4. Query performance must not be dependent on the size of the database, but rather on the complexity of the query
5. The warehouse must ensure local consistency, global consistency, and referential integrity

28. The modification of data as it is moved into the data warehouse is:

Answers:

1. Data Transformation
2. Replication
3. Synchronization
4. Data migration
5. Normalization

29. Which of the following statements is incorrect regarding Data Mining?

Answers:

1. It is the process of turning data into information
2. It is a collection of many techniques
3. It is a replacement for OLAP
4. It is based on machine generated hypothesis
5. It is used in Decision Support, Prediction, Forecasting and Estimation

30. Which of the following would be the only similarity between a datawarehouse and OLTP system?

Answers:

1. Purpose
2. Structure of data
3. Type of data
4. Condition of data
5. Data model

31. Which of the following is not true regarding the process of Data Mining?

Answers:

1. Software techniques are used for finding patterns and regularities in sets of data
2. It is the computer that is responsible for finding the patterns by identifying the underlying rules and features in the data
3. Data mining analysis tends to work from the data up
4. The best techniques are those developed with an orientation towards small volumes of data
5. The analysis process starts with a set of data, uses a methodology to develop an optimal representation of the structure of the data, during which time knowledge is acquired

32. Data quality management refers to the fact that:

Answers:

1. Ad-hoc analysis must not be slowed or inhibited by the performance of the data warehouse RDBMS
2. The warehouse must ensure local consistency, global consistency, and referential integrity
3. The RDBMS server must support hundreds, even thousands, of concurrent users while maintaining acceptable query performance
4. The server must include tools that co-ordinate the movement of subsets of data between warehouses
5. The RDBMS must provide a complete set of analytic operations including core sequential and statistical operations

33. Which of the following stage is concerned with the extraction of patterns from the data?

Answers:

1. Selection
2. Pre-processing
3. Transformation
4. Data Mining
5. Interpretation and Evaluation

34. The Metadata of the data warehouse should at least contain:

Answers:

1. The structure of the data
2. The algorithm used for summarisation
3. The mapping from the operational environment to the data warehouse and the algorithm used for summarisation
4. The structure of the data and the algorithm used for summarisation
5. The structure of the data, the algorithm used for summarisation and the mapping from the operational environment to the data warehouse and the algorithm used for summarisation

35. Which of the following features are required by OLAP applications?

Answers:

1. Multidimensional views of data
2. Calculation-intensive capabilities
3. Time intelligence
4. Multidimensional views of data and Calculation-intensive capabilities
5. Calculation-intensive capabilities and Time intelligence

36. Data Mining is also known as

Answers:

1. Data Extraction
2. Data Cleansing
3. Data Archiving
4. Knowledge Discovery in Databases (KDD)
5. Data Preservation

37. Given the following steps between raw data and extracted knowledge, arrange them in the correct order:

1 Data mining

2 Transformation

3 Selection

4 Pre-processing

5 Interpretation and Evaluation

Answers:

1. 3,4,2,1,5
2. 4,3,2,1,5
3. 4,2,1,3,5
4. 4,1,2,3,5
5. 3,4,1,2,5

38. The data warehouse is typically a large database on a high performance SMP system. Here SMP stands for:

Answers:

1. Symmetric Multi-Processing
2. Superior Multi-Processing
3. Systematic Massive Processing
4. Symmetric Massive Processing
5. Systematic Multi-Processing

39. The main impetus behind data warehousing was:

Answers:

1. To discover means to reduce the data volumes
2. To make OLTP systems work faster
3. To reduce human interaction with database systems
4. To access corporate knowledge repositories based on huge databases to make sound business decisions
5. To standardise the database products used

40. SQL stands for:

Answers:

1. Structured Query Language
2. Systematic Query Language
3. Structured Query Logic
4. Structured Queuing Logic
5. Standard Query Logic

41. Changing the view of the data to a higher level of aggregation is known as:

Answers:

1. Implosion
2. Drill down
3. Drill up
4. Synchronisation
5. Summarisation

42. The movement of data from one environment to another is known as:

Answers:

1. Data Migration
2. Normalization
3. Replication
4. Data Mining
5. Data Cleansing

43. In which component of the enterprise is the data re-organised for analysis and information extracted from the data?

Answers:

1. The Data Warehouse
2. The Data Mart
3. The Data Mine
4. The operational RDBMS
5. Metadata

44. A means of extending the data accessible to the end user beyond that which is stored in the OLAP server is know as :

Answers:

1. Consolidation
2. Multi Dimensional Analysis
3. Drill Down
4. Navigation
5. Reach through

45. The logical organisation of data in a database is called:

Answers:

1. Normalisation
2. Schema
3. View
4. Fact table
5. Dimension

46. Which of the following type of data is most likely to be stored on some form of mass storage ?

Answers:

1. Metadata
2. Highly summarised data
3. Lightly summarised data
4. Current detail data
5. Older detail data

47. The requirement that the datawarehouse RDBMS server must support hundreds and thousands of concurrent users while maintaining an acceptable query performance is known as:

Answers:

1. Terabyte Scalability
2. Load Performance
3. Mass User Scalability
4. Data Quality Management
5. Query Performance

48. Metadata does not include:

Answers:

1. The actual data
2. A description of tables and fields in the warehouse, including data types and the range of acceptable values
3. A similar description of tables and fields in the source databases, with a mapping of fields from the source to the warehouse
4. A description of how the data has been transformed, including formulae, formatting, currency conversion, and time aggregation
5. Information that is needed to support and manage the operation of the data warehouse

49. The main objective of Data Mining is:

Answers:

1. The safe storage of data
2. Elimination of errors from the data
3. Deleting data that is no longer important to the organization
4. The extraction of implicit, previously unknown, and potentially useful information from data
5. To help in the generation of reports for the management

50. In the Discovery model of Data Mining, the emphasis is on which of the following?

Answers:

1. The system automatically discovering important information hidden in the data
2. The user who is responsible for formulating the hypothesis and issuing the query on the data to affirm or negate the hypothesis
3. Volume of the data being examined
4. Timeliness of the data
5. Speed with which the data is examined

51. In a star schema, the central table which contains the individual facts being stored in the database is called a:

Answers:

1. Fact table
2. Meta table
3. Data Dictionary
4. Pivot table
5. Dimension table

52. Which of the following rules would be considered the central core of OLAP?

Answers:

1. Multidimensional Conceptual View
2. Intuitive Data Manipulation
3. Accessibility
4. Batch Extraction vs Interpretative
5. Transparency

53. Changing the view of the data to a greater level of detail is known as:

Answers:

1. Explosion
2. Drill down
3. Drill up
4. Exploration
5. Aggregation

54. A multidimensional cube records a set of data derived from:

Answers:

1. Fact tables
2. Pivot tables
3. Dimensions
4. Fact tables and Dimensions
5. Fact tables and Pivot tables

55. Which Data Mining technique partitions the database so that each partition or group is similar according to some criteria or metric ?

Answers:

1. Clustering and Segmentation
2. Induction
3. Neural Networks
4. Data Visualisation
5. Linear Regression Analysis

56. Which of the following is not associated with data warehousing?

Answers:

1. Transaction processing
2. Information retrieval and analysis
3. Multi-dimensional data model
4. Query processing
5. Transformed and summarised data

57. Which of the following is an architecture for OLAP?

Answers:

1. MOLAP
2. ROLAP
3. KOLAP
4. MOLAP and ROLAP
5. MOLAP, ROLAP and KOLAP

58. Under OLAP terminology, slice and dice refers to:

Answers:

1. The user-initiated process of navigating by calling for page displays interactively, through the specification of slices via rotations and drill down/up
2. Restricting the view of database objects to a specified subset
3. A means of extending the data accessible to the end user beyond that which is stored in the OLAP server
4. Computing all of the data relationships for one or more dimensions
5. Applying calculations to input data at the time the request for that data is made

59. In the Verification model of Data Mining, the emphasis is on which of the following?

Answers:

1. The system automatically discovering important information hidden in the data
2. The user who is responsible for formulating the hypothesis and issuing the query on the data to affirm or negate the hypothesis
3. Volume of the data being examined
4. Timeliness of the data
5. Speed with which the data is examined

60. The applications of Data Mining would not include:

Answers:

1. Discovering buying-patterns for cross selling
2. Financial market prediction
3. Discovering errors made during data entry
4. Discovering which customer is most profitable
5. Credit assessment

61. A data warehouse is a “subject-oriented, integrated, time-variant, non-volatile collection of data in support of management’s decision-making process”. The data within the warehouse is integrated in such a way that:

Answers:

1. Users from all departments help to create the database
2. It contains the data of the enterprise in its entirety
3. The final product is a fusion of various legacy system information into a cohesive set of information
4. Every user has access to the data in the warehouse

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