CS614-Midterm
1 / 50
When performing objective assessments, companies follow a set of principles to develop metrics specific to their needs, there is hard to have “one size fits all” approach. Which of the following statement represents the pervasive functional forms?
2 / 50
Data mining is a/an ______ approach , where browsing through data using mining techniques may reveal something that might be of interest to the user as information that was unknown previously.
3 / 50
De-Normalization normally speeds up
4 / 50
The goal of ______is to look at as few block as possible to find the matching records.
5 / 50
The need to synchronize data upon update is called
6 / 50
Pre-computed _______ can solve performance problems
7 / 50
Data mining uses _________ algorithms to discover patterns and regularities in data.
8 / 50
_____ contributes to an under-utilization of valuable and expensive historical data, and inevitably results in a limitedcapability to provide decision support and analysis.
9 / 50
Grain is the ________ level of data stored in the warehouse.
10 / 50
Data mining evolve as mechanism to cater the limitations of _____ systems to deal massive data sets with high dimensionality, new data types, multiple heterogeneous data resources etc...
11 / 50
A ________ dimension is a collection of random transactional codes, flags and/text attributes that are unrelated to any particular dimension. The ______ dimension is simply a structure that provides a convenient place to store the ______ attributes.
12 / 50
The key idea behind ___________ is to take a big task and break it into subtasks that can be processed concurrently on a stream of data inputs in multiple, overlapping stages of execution.
13 / 50
DTS allows us to connect through any data source or destination that is supported by ____________
14 / 50
In _________ system, the contents change with time. :
15 / 50
B-Tree is used as an index to provide access to records
16 / 50
Which statement is true for De-Normalization?
17 / 50
5 million bales.
18 / 50
For a relation to be in 4NF it must be:-
19 / 50
30.Data Warehouse is about taking / colleting data from different ________ sources:
20 / 50
It is observed that every year the amount of data recorded in an organization :
21 / 50
People that design and build the data warehouse must be capable of working across the organization at all levels
22 / 50
Data mining evolve as a mechanism to cater the limitations of ________ systems to deal massive data sets with high dimensionality, new data types, multiple heterogeneous data resources etc.
23 / 50
The goal of ideal parallel execution is to completely parallelize those parts of a computation that are not constrained by data dependencies. The smaller the portion of the program that must be executed __________, the greater the scalability of the computation.
24 / 50
For good decision making, data should be integrated across the organization to cross the LoB (Line of Business). This is to give the total view of organization from:
25 / 50
in agriculture extension is that pest population beyond which the benefit of spraying outweighs levels
26 / 50
Focusing on data warehouse delivery only often end up _________.
27 / 50
Transactional fact tables do not have records for events that do not occur. These are called
28 / 50
To measure or quantify the similarity or dissimilarity, different techniques are available. Which of the following option represent the name of available techniques?
29 / 50
The purpose of the House of Quality technique is to reduce ______ types of risk.
30 / 50
The goal of ideal parallel execution is to completely parallelize those parts of a computation that are not constrained by data dependencies. The __________ the portion of the program that must be executed sequentially, the greater the scalability of computation.
31 / 50
The goal of star schema design is to simplify ________
32 / 50
_______________, if too big and does not fit into memory, will be expensive when used to find a record by given key.
33 / 50
The input to the data warehouse can come from OLTP or transactional system but not from other third party database.
34 / 50
There are many variants of the traditional nested-loop join, if there is an index is exploited, then it is called……
35 / 50
Normalization effects performance
36 / 50
Multidimensional databases typically use proprietary __________ format to store pre-summarized cube structures.
37 / 50
In a traditional MIS system, there is an almost linear sequence of queries.
38 / 50
____________ in agriculture extension is that pest population beyond which the benefit of spraying outweighs its cost.
39 / 50
A single database, couldn‟t serve both operational high performance transaction processing and DSS, analytical processing, all at the same time.
40 / 50
________ gives total view of an organization
41 / 50
Relational databases allow you to navigate the data in ____________ that is appropriate using the primary, foreign key structure within the data model.
42 / 50
Pakistan is one of the five major ________ countries in the world.
43 / 50
If „M‟ rows from table-A match the conditions in the query then table-B is accessed „M‟ times. Suppose table-B has an index on the join column. If „a‟ I/Os are required to read the data block for each scan and „b‟ I/Os for each data block then the total cost of accessing table-B is _____________ logical I/Os approximately.
44 / 50
Execution can be completed successfully or it may be stopped due to some error. In case of successful completion of execution all the transactions will be ___________
45 / 50
Multi-dimensional databases (MDDs) typically use ___________ formats to store pre-summarized cube structures.
46 / 50
47 / 50
As apposed to the out come of classification, estimation deal with ____________ valued outcome.
48 / 50
Cube is a __________ entity containing values of a certain fact at a certain aggregation level at an intersection of a combination of dimensions.
49 / 50
: An optimized structure which is built primarily for retrieval, with update being only a secondary consideration is
50 / 50
_________ breaks a table into multiple tables based upon common column values.
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