CS614 Midterm Current Papers VU Fall 2011 (www.vusolutions.com)
It is sometimes more efficient for an application to draw directly in a window without relying on the WM_PAINT message. How this task can be accomplished (i.e. how can we draw in a window directly without using WM_PAINT message)? (5)
Write down a C/C++ program that has 2 functions. One takes four integer variables as parameters and returns their sum and the other also takes 4 integers as argument and returns their multiplication. Also write 2 macros that perform the same tasks as these functions perform.(5)
How can I use the CopyTo method of the Windows Forms controls collection to copy controls into an array? (3)
How Windows keep track of the files?(3)
Can you write a class without specifying namespace? Which namespace does it belong to by default?(2)
"In the GDI environment there are two working spaces", Name these two. (2)
Another Paper:
MIDTERM EXAMINATION
Spring 2011
CS614- Data Warehousing (Session - 6)
Ref No: 1368137
Time: 60 min
Marks: 40
Question No: 1 ( Marks: 1 ) - Please choose one
The need to synchronize data upon update is called
Data Manipulation
Data Replication
Data Coherency
Data Imitation
Question No: 2 ( Marks: 1 ) - Please choose one
Taken jointly, the extract programs or naturally evolving systems formed a spider web,
also known as
Distributed Systems Architecture
Legacy Systems Architecture
Online Systems Architecture
Intranet Systems Architecture
Question No: 3 ( Marks: 1 ) - Please choose one
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:
Owner's Perspective
Customer's Perspective
Decision Maker's Perspective
Employee's Perspective
Question No: 4 ( Marks: 1 ) - Please choose one
Node of a B-Tree is stored in memory block and traversing a B-Tree involves ______
page faults.
O (n)
O (n2)
O (n lg n)
O (lg n)
Question No: 5 ( Marks: 1 ) - Please choose one
Which statement is true for De-Normalization?
Redundant data is a performance liability at query time, but is a performance
benefit at update time.
Redundant data is a performance benefit at both query time and update time.
Redundant data is a performance liability at both query time and update time.
Redundant data is a performance benefit at query time, but is a performance
liability at update time.
Question No: 6 ( Marks: 1 ) - Please choose one
Pre-join technique is used to avoid
Run time join
Compile time join
Load time join
Question No: 7 ( Marks: 1 ) - Please choose one
Cube is a __________ entity containing values of a certain fact at a certain aggregation
level at an intersection of a combination of dimensions.
Logical
Physical
Analytical
None of these
Question No: 8 ( Marks: 1 ) - Please choose one
The goal of star schema design is to simplify ________
Logical data model
Physical data model
Conceptual data model
None of these
Question No: 9 ( Marks: 1 ) - Please choose one
Grain is the ________ level of data stored in the warehouse
Atomic
Summarized
Aggregated
Cube
Question No: 10 ( Marks: 1 ) - Please choose one
Transactional fact tables do not have records for events that do not occur. These are
called
Not Recording Facts
Fact-less Facts
Null Facts
None of these
Question No: 11 ( Marks: 1 ) - Please choose one
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.
Junk
Time
Parallel
None of these
Question No: 12 ( Marks: 1 ) - Please choose one
During ETL process of an organization, suppose you have data which can be
transformed using any of the transformation method. Which of the following strategy will
be your choice for least complexity?
One-to-One Scalar Transformation ( but not sure )
One-to-Many Element Transformation
Many-to-Many Element Transformation
Many-to-One Element Transformation
Question No: 13 ( Marks: 1 ) - Please choose one
Change Data Capture is one of the challenging technical issues in _____________
Data Extraction
Data Loading
Data Transformation
Data Cleansing
Question No: 14 ( Marks: 1 ) - Please choose one
Rearranging the grouping of source data, delivering it to the destination database, and
ensuring the quality of data are crucial to the process of loading the data warehouse. Data
____________ is vitally important to the overall health of a warehouse project.
1. Cleansing
2. Cleaning
3. Scrubbing
Which of the following options is true?
Option 1 only
Option 2 only
Option 1 & 2 only
Option 1, 2 & 3
Question No: 15 ( Marks: 1 ) - Please choose one
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?
Simple Ratio, Min or Max Operation, Weighted Average
Only Complex Ratio, Min Operation, Max Operation
Only Simple Ratio, Min or Max Operation
Only Min or Max Operation, Weighted Average
Question No: 16 ( Marks: 1 ) - Please choose one
The input to the data warehouse can come from OLTP or transactional system but not
from other third party database.
True
False
Question No: 17 ( Marks: 1 ) - Please choose one
Normalization effects performance
True ( but not sure )
False
Question No: 18 ( Marks: 1 ) - Please choose one
Collapsing tables can be done on the ___________ relationships
One-to-One
Many-to-Many
Both One-to-One and Many-to-Many
None of these
Question No: 19 ( Marks: 1 ) - Please choose one
_________ breaks a table into multiple tables based upon common column values.
Horizontal splitting
Vertical splitting
Question No: 20 ( Marks: 1 ) - Please choose one
If w is the window size and n is the size of data set, then the complexity of merging
phase in BSN method is___________
O (n)
O (w)
O (w n)
O (w log n)
Question No: 21 ( Marks: 2 )
Briefly describe snowflake schema.
Ans:
Snowflake Schema: snowflaking is a method of normalizing the dimension tables in
star schema. When we completely normalize all the dimension tables, then the
resultent structure resemble a snowflakewith the fact table in the middle.
\
Snowflake Schema: Sometimes a pure star schema might suffer performance problems.
This can occur when a de-normalized dimension table becomes very large and penalizes
the star join operation. Conversely, sometimes a small outer-level dimension table does
not incur a significant join cost because it can be permanently stored in a memory buffer.
Furthermore, because a star structure exists at the center of a snowflake, an efficient star
join can be used to satisfy part of a query. Finally, some queries will not access data from
outer-level dimension tables. These queries effectively execute against a star schema that
contains smaller dimension tables. Therefore, under some circumstances, a snowflake
schema is more efficient than a star schema.
Question No: 22 ( Marks: 2 )
Why both aggregation and summarization are required?
Although summarization and aggregation are
sometimes used interchangeably
Summarization and aggregationare typically used for the following reasons:
They are required when the lowest level of detail stored in the data warehouse is
at a higher level than the detail arriving from the source. This situation occurs
when data warehouse queries do not require the lowest level of detail or
sometimes when sufficient disk space is not available to store all the data for the
time frame required by the data warehouse.
• They can be used to populate data marts from the data warehouse where the data
mart does not require the same level of detail as is stored in the warehouse.
• They can be used to roll up detail values when the detail is removed from the
warehouse because it is
Question No: 23 ( Marks: 3 )
Under what condition smart tools work properly to construct a less detailed aggregate
from more detailed aggregate?
Ans:
Smart tools will allow less detailed aggregates to be constructed from more detailed
aggregates (full aggregate awareness) at run-time so that we do not go all the way down
to the detail for every aggregation. However, for this to work, the metrics must be
additive (e.g., no ratios, averages, etc.). More detailed pre-aggregates are larger, but can
also be used to build less detailed aggregates on-the-go.
Question No: 24 ( Marks: 3 )
What is web scrapping? Give some of its uses.
Web scrapping is a process of applying screen scrapping techniques to the web. There
are several web scrapping products in the market and target business users who want to
creatively use the data, not write complex scripts. Some of the uses of scrapping are:
Building contact lists
Extracting product catalogs
Aggregating real-estate info
Automating search Ad listings
Clipping news articles etc.
Question No: 25 ( Marks: 5 )
Af
types of data loading strategies are and when each type of strategy is adopted? Explain.
Significance of Data Loading Strategies
Need to look at:
Data freshness
System performance
Data volatility
Data Freshness
Very fresh low update efficiency
Historical data, high update efficiency
Always trade-offs in the light of goals
System performance
Availability of staging table space
Impact on query workload
Data Volatility
Ratio of new to historical data
High percentages of data change (batch update)
Question No: 26 ( Marks: 5 )
What are the drawbacks of MOLAP? Also explain the curse of Dimensionality?
Drawbacks of MOLAP:
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