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CUSTOMER_CODE
SMUDE
DIVISION_CODE
SMUDE
EVENT_CODE
APR2016
ASSESSMENT_CODE MC0088_APR2016
QUESTION_TYPE
DESCRIPTIVE_QUESTION
QUESTION_ID
5227
QUESTION_TEXT
Distinguish the features between OLTP and OLAP
SCHEME OF
EVALUATION
Users and sytem orientatioin: An OLTP system is customer oriented and
is used for transaction and query used for transacrion and
query processing by clerks,clients and information technology
professionals. An OLAP system is market oriented and is usd for data
analysis by knowledge workers, including managers, executives and
analysts. (2 marks)
Data contents: An OLTP system managers current data that typically are
too detailed to be easily used for decision making. An OLTP system
managers large amounts of historiacl data, provides facilities for
summarization and aggregation and stores and managers information at
different levels of granularity. These features make the data easier to use
in informed decision making. (2 marks)
Database design:An OLTP system usually adopts an entity relationship
data model and an application oriented database design. An OLAP
system typically adopts either a star or snowflake model and subject –
oriented database design. (2 marks)
View:An OLTP system focuses mainly on the current data within an
enterprise or department without referring to historical data or data
in different organizations. In contrast OLAP system often spans multiple
versions of a database schema, due to the evolutionary process of an
organization. OLAP systems also deal with information that originates
from different organizations, integrating information from many data
stores. Because of their huge volume, OLAP data are stored on multiple
storage media. (2 marks)
Access patterns: The access patterns of an OLTP system consists manily
of short, atomic transactions. Such a system requires
concurrency concurrency control and recovery mechanisms. However
access to OLAP systems are mostly read only operations although many
could be complex queries. (2 marks)
(Total 10 marks)
QUESTION_TYPE
DESCRIPTIVE_QUESTION
QUESTION_ID
72559
Discuss data smoothing technologies.
QUESTION_TEXT
a.
b.
SCHEME OF EVALUATION c.
d.
Binning
Clustering
Combined computer and human inspection
Regression
(2.5 marks each with explanation)
QUESTION_TYPE
DESCRIPTIVE_QUESTION
QUESTION_ID
117785
QUESTION_TEXT
Explain the various OLAP data cube operations.
The various data cube operations are:
●
SCHEME OF EVALUATION ●
Roll-up
Drill-down
●
Slice and dice
●
Pivot (Rotate)
QUESTION_TYPE
DESCRIPTIVE_QUESTION
QUESTION_ID
117789
QUESTION_TEXT
What is data cleaning? Explain missing values method for data
cleaning.
Data cleaning routines attempt to fill in missing values, smooth out
noise while identifying outlines, and correct inconsistencies in the
data. (2 marks)
Missing value Methods are:
SCHEME OF
EVALUATION
1.
Ignore the tuple
2.
Fill in the missing value immediately
3.
Use a global constant to fill in the missing value (4 marks)
4.
Use the attribute value to fill in the missing value
5.
Use the attribute mean for all samples belonging to the same
class as the given tuple
6.
Use the most probable value to fill in the missing value (4 marks)
QUESTION_TYPE
DESCRIPTIVE_QUESTION
QUESTION_ID
117790
QUESTION_TEXT
Define FP-Tree. Explain FP-tree construction Algorithm
A frequent pattern tree( or fp-tree) is a tree structure consisting of an
item –prefix –tree and a frequent – item-header table. (3 marks)
Item – prefix- tree:
*
*
It consists of a root node labelled null
*
Each on-root node consists of three fields
SCHEME OF
EVALUATION
*
Item name
*
Support count,
*
Node link
Frequent – item – header – table: it consists of two fields:
*
*
*
the FP-tree
Item name
Head of node link which points to the first node in
(7 marks)
FP-Tree construction algorithm is given in page no: 113
QUESTION_TYPE
DESCRIPTIVE_QUESTION
QUESTION_ID
117793
QUESTION_TEXT
List and explain the various criteria used to compare the
classification methods.
SCHEME OF
EVALUATION

Predictive accuracy

Speed

Robustness

Scalability

Interpretability
5×2=10 marks