CS614 Current Final Term Papers Spring 2014 & Past Final Term Papers at One Place from 22 August to 02 September 2014

[+M.Tariq Malik]

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[+M.Tariq Malik]

Q:1 Briefly explain any two types of precedence constraints that we can use in DTS.
Q:2 Time complexity of K-means algorithm is O(tkn) what does t,k,and n represents here?
Q:3 what are the problems you will face if low priority is given to cube construction?
Q:4 List down any two parallel software Architectures?
Q :5 what is unsupervised learning in Data mining?
Q:6 which scripting language are used to perform complex transformations in Data pakages?
Q :7 "Dense index consist of a number of bit vector" justifi it .
Q :8 It is essenstial to have a sub-matter expert as part of data modling team . what will be the implication if such expert is not present in organisation.

[+M.Tariq Malik]

cs614 paper:
objective all most virtualians file few new but easy...
Suppose there is a large enterprise which uses the same server for the development and production environments. What problems can arise if it uses single server for both purposes? 5m
Write down any two drawbacks if “Date” is stored in text format rather than using proper date format like “dd-MMM-yy” etc. 5m
In context of Web data warehousing, consider the “web page” dimension, list at least five possible attributes of this dimension. 5m
There are different data mining techniques e.g. “clustering”, “description” etc. Each of the following statement corresponds to some data mining technique. For each statement name the technique the statement corresponds to. 5m
a) Assigning customers to predefined customer segments (i.e. good vs. bad)
b) Assigning credit applicants to predefined classes (i.e. low, medium, or high risk)
c) Guessing how much customers will spend during next 6 months
d) Building a model and assigning a value from 0 to 1 to each member of the set. Then classifying the members into categories based on a threshold value.
e) Guessing how much students will score more than 65% grades in midterm.
Specify at least one implication, if you don’t provide proper documentation as part of data warehouse development.3 m
In context of nested loop join, mention two guidelines for selecting a table as inner table. 3m
We can identify the Session in Word Wide Web by using “Time-contiguous Log Entries” however there are some limitations of this technique. Briefly explain any two limitations. 3m
Identify the given statement as correct or incorrect and justify your answer in either case.
"The problem of Referential Integrity always occurs in traditional OLTP system as well as in DWH". 3m
There are two primary techniques for gathering requirements i.e. interviews or facilitated sessions. Which technique is preferred by Ralph Kimball? 2m
List down any two Parallel Software Architectures?2m
List down any four Static Attributes recorded by the scouts in Agriculture Data Warehouse Case Study. 2m
List down any four issues of Clickstream Data. 2m
Remember for me and Best of luck...

[Amna]

1. Write two unsupervised learning? page no. 270

Answer:

• one way clustering
• two way clustering

 

1. Bitmap index: run length encoding ka ek question tha input di hoi output findout kerni thi Page no.234

Answer: If we apply Run length Encoding on the input “11001100”, the output will be

• 12#02#12#02

 

1. B-tree vs. hash indexes men se ye query di hoi thi

SELECT*FROM R WHERE A= 5 page no.228

Btana tha k is men dense index sparse index B-tree index and bitmap index men se konsi technique use ho gi aur explain kerna tha ise

1. Identify kerna tha k ye statement correct he ya incorrect aur reason  btana tha

Bayesian modeling is an example of unsupervised learning” page no 270

Answer: incorrect. Bayesian modeling is an example of supervised learning

1. Page no. 278  pe

IF(ITEMS/TIME)>6

Then

                        Gender= female

Else

Gender= male esa ek question tha aur baki yad nahi but past men se the paper start wale lectures men se tha

 

Forward Proxy (2)

Answer: Ch#40 Page no: 369

The type of proxy we are referring to in this discussion is called a forward proxy. It is outside of our control because it belongs to a networking company or an ISP. When people talk about a proxy server (often simply known as a "proxy"), more often than not they are referring to a forward proxy. Let me explain what this particular server does. When one of these clients makes a connection attempt to that file transfer server on the Internet, its requests have to pass through the forward proxy first. A forward proxy is typically used in tandem with a firewall to enhance an internal network's security by controlling traffic originating from clients in the internal network that are directed at hosts on the Internet.

Drawbacks of waterfall model for DWH (3)

First and foremost, the project is likely to occur over an extended period of time, during which the users may not have had an opportunity to review what will be delivered.

Second, in today's demanding competitive environment there is a need to produce results in a much shorter timeframe.

in which scenario we can use waterfall (2)

The model is a linear sequence of activities like requirements definition, system design, detailed design, integration and testing, and finally operations and maintenance. The model is used when the system requirements and objectives are known and clearly specified.

my paper on 25 august/

how gender guide used.

If for very large number of records gender is missing, it would become impossible for us to manually check each and every individual‘s name and identify the gender. In such cases we can formulate a mechanism to correct gender. We can either use a standard gender guide or create a new table Gender_guide. Gender_guide contains only two columns name and gender. Populate Gender_guide table by a query for selecting all distinct first names from student table. Then manually placing their gender.

This table can serve us as guide by telling what can be the gender against this particular name. For example if we have hundred students in our database with first name equal to ‘Muhammad’. Then in our Gender guide table we will have just one entry ‘Muhammad’ and we will manually set the gender as ‘Male’ against ‘Muhammad’. Now to fill missing genders in exception table we will just do an inner join on Error table and Gender guide table.

 

run length encoding on these 2 ad-hoe the or output btana the .

Run length used in bitmap indexing

Output 1 may be

15#02# 18# (mean 1 come 5 time and 0 come 2 times and 1 come 1 8 times

(111110011111111))

Output 2 may be

11#01#11#

Output 3 may be

112#012#

Step of kimball approach for data life cycle.

Kimball Process. Four step approach. (Business process-->Grains-->Facts-->dimension). He defines a business process as a major operational process in the organization that is supported by some kind of legacy system (or systems). (Read "Business Development Lifecycle" see page#290)

Drawback of traditional web search. ch: 39 page 351

1.  Limited to keyword based matching.

2.  Cannot distinguish between the contexts in which a link is used.

3.  Coupling of files has to be done manually.

Two ways of session describe in world wide web.

Identifying the Session

• Web-centric data warehouse applications require every visitor session (visit) to have its own unique identity
• The basic protocol for the World Wide Web, HTTP, stateless so session identity must be established in some other way.
• There are several ways to do this
• Using Time-contiguous Log Entries
• Using Transient Cookies
• Using HTTP's secure sockets layer (SSL)
• Using session ID Ping-pong
• Using Persistent Cookies

what problem when single server is used to both purpose 2 purpose dye the..

MCQs

execution will be terminated abnormaly.... (quiz 4 file- 2 MCQs)

kimballs approach ......driven ( quiz 4 file-5 mcqs)

pipeline per increase through .....( quiz 4 file- 1 mcq)

selectivity of query in olap... (queries must be executed in a small number of seconds.)

star schema simplify ...

majority of data ...fail if (Majority of projects fail due to the complexity of the development process.)

er is  .......design   (constituted to optimize OLTP performance)   

survival of fittest is.....algorithm (Genetic Algorithms: These are based on the principle survival of the fittest. In these techniques, a model is formed to solve problems having multiple options and many values. Briefly, these techniques are used to select the optimal solution out of a number of possible solutions. However, are not much robust as can not perform well in the presence of noise.

shipy in kobol devlop .......( In 1972 the Mitsubishi Shipyards in Kobe developed a technique in which customer wants were linked to product specifications via a matrix format. Technique is known today as The House of Quality and is one of many techniques of Quality Function Deployment, which can briefly be defined as “a system for translating customer requirements into appropriate company requirements”. The purpose of the technique is to reduce two types of risk. First, the risk that the product specification does not comply with the wants of the predetermined target group of customers. Secondly, the risk that the final product does not comply with the product specification

Q:1 Briefly explain any two types of precedence constraints that we can use in DTS.

Answer: page 395

Precedence constraints sequentially link tasks in a package. In DTS, you can use three types of precedence constraints, which can be accessed either through DTS Designer or programmatically:

Unconditional: If you want Task 2 to wait until Task 1 completes, regardless of the outcome, link Task 1 to Task 2 with an unconditional precedence constraint.

On Success: If you want Task 2 to wait until Task 1 has successfully completed, link Task 1 to Task 2 with an On Success precedence constraint.

On Failure: If you want Task 2 to begin execution only if Task 1 fails to execute successfully, link Task 1 to Task 2 with an On Failure precedence constraint. If you want to run an alternative branch of the workflow when an error is encountered, use this constraint.

Q:2 Time complexity of K-means algorithm is O(tkn) what does t,k,and n represents here?

Page 281

Answer: Relatively efficient: O(tkn), where n is # objects, k is # clusters, and t is # iterations.

Normally, k, t n.

Q:3 what are the problems you will face if low priority is given to cube construction?

Answer: page 313

Low priority for OLAP Cube Construction: Make sure your OLAP cube-building or pre-calculation process is optimized and given the right priority. It is common for the data warehouse to be on the bottom of the nightly batch loads, and after the loading the DWH, usually there isn't much time left for the OLAP cube to be refreshed. As a result, it is worthwhile to experiment with the OLAP cube generation paths to ensure optimal performance.

Q:4 List down any two parallel software Architectures?

Answer: Shared Memory, Shard Disk and Shared Nothing

Q :5 what is unsupervised learning in Data mining?

Answer: page 27

Unsupervised learning where you don’t know the number of clusters and obviously no idea about their attributes too. In other words you are not guiding in any way the DM process for performing the DM, no guidance and no input. Unsupervised learning is closer to the exploratory spirit of Data Mining as stressed in the definitions given above. In unsupervised learning situations all variables are treated in the same way, there is no distinction between explanatory and dependent variables. However, in contrast to the name undirected data mining there is still some target to achieve. This target might be as general as data reduction or more specific like clustering. For unsupervised learning typically either the target variable is unknown or has only been recorded for too small a number of cases.

Q:6 which scripting language are used to perform complex transformations in Data packages?

Answer: Microsoft SQL Server provides graphical tools to build DTS packages. These tools provide good support for transformations. Complex transformations are achieved through VB Script or Java Script that is loaded in DTS package. Package can also be programmed by using DTS object model instead of using graphical tools but DTS programming is rather complicated.

Q :7 "Dense index consist of a number of bit vector" justify it .

Answer: Dense Index: Every key in the data file is represented in the index file. Bitmap index record (Value, Bit Vector): Bit Vector has one bit for every record in the file, ith bit of Bit Vector is set iff record i has Value in the given column. Bit vectors typically compressed. Converted to sets of rids during query evaluation.

Q :8 It is essential to have a sub-matter expert as part of data modeling team . What will be the implication if such expert is not present in organization?

Answer: It is essential to have a subject-matter expert as part of the data modeling team. This person can be an outside consultant or can be someone in-house with extensive industry experience. Without this person, it becomes difficult to get a definitive answer on many of the questions, and the entire project gets dragged out, as the end users may not always be available

==================================================================

Suppose there is a large enterprise which uses the same server for the development and production environments. What problems can arise if it uses single server for both purposes? 5m

To save capital, often data warehousing teams will decide to use only a single database and a single server for the different environments i.e. development and production. Environment separation is achieved by either a directory structure or setting up distinct instances of the database.

This is awkward for the following reasons:

• Sometimes it is possible that the server needs to be rebooted for the development environment. Having a separate development environment will prevent the production environment from being effected by this.

• There may be interference while having different database environments on a single server. For example, having multiple long queries running on the development server could affect the performance on the production server, as both are same.

 

Write down any two drawbacks if “Date” is stored in text format rather than using proper date format like “dd-MMM-yy” etc. 5m

In context of Web data warehousing, consider the “web page” dimension, list at least five possible attributes of this dimension. 5m

Page key

Page source

Page function

Page template

Item type

Graphic type

Animation type

Sound type

Page file name

There are different data mining techniques e.g. “clustering”, “description” etc. Each of the following statement corresponds to some data mining technique. For each statement name the technique the statement corresponds to. 5m

a) Assigning customers to predefined customer segments (i.e. good vs. bad) classification
b) Assigning credit applicants to predefined classes (i.e. low, medium, or high risk)  classification
c) Guessing how much customers will spend during next 6 months prediction
d) Building a model and assigning a value from 0 to 1 to each member of the set. Then classifying the members into categories based on a threshold value. Estimation
e) Guessing how much students will score more than 65% grades in midterm. Prediction

Specify at least one implication, if you don’t provide proper documentation as part of data warehouse development.3 m

Usually by this time most, if not all, of the developers will have left the project, so it is essential that proper documentation is left for those who are handling production maintenance. There is nothing more frustrating than staring at something another person did, yet unable to figure it out due to the lack of proper documentation.

Another pitfall is that the maintenance phase is usually boring. So, if there is another phase of the data warehouse planned, start on that as soon as possible.

 

In context of nested loop join, mention two guidelines for selecting a table as inner table. 3m

For a Nested-Loop join inner and outer tables are determined as follows:  page 242

The outer table is usually the one that has:

• The smallest number of qualifying rows, and/or

• The largest numbers of I/Os required to locate the rows.

The inner table usually has:

• The largest number of qualifying rows, and/or

The smallest number of reads required to locate rows

We can identify the Session in Word Wide Web by using “Time-contiguous Log Entries” however there are some limitations of this technique. Briefly explain any two limitations. 3m

Answer: A session can be consolidated by collecting time-contiguous log entries from the same host (Internet Protocol, or IP, address). In many cases, the individual hits comprising a session can be consolidated by collating time-contiguous log entries from the same host (Internet Protocol, or IP, address). If the log contains a number of entries with the same host ID in a short period of time (for example, one hour), one can reasonably assume that the entries are for the same session.

Limitations: • This method breaks down for visitors from large ISPs because different visitors may reuse dynamically assigned IP addresses over a brief time period.

• Different IP addresses may be used within the same session for the same visitor.

• This approach also presents problems when dealing with browsers that are behind some firewalls.

Identify the given statement as correct or incorrect and justify your answer in either case.
"The problem of Referential Integrity always occurs in traditional OLTP system as well as in DWH". 3m

Answer: While doing total quality measurement, you measure RI every week (or month) and hopefully the number of orphan records will be going down, as you will be fine tuning the processes to get rid of the RI problems. Remember, RI problem is peculiar to a DWH, this will not happen in a traditional OLTP system.

There are two primary techniques for gathering requirements i.e. interviews or facilitated sessions. Which technique is preferred by Ralph Kimball? 2m

Both  have their advantages and disadvantages. Interviews encourage lots of individual participation. They are also easier to schedule. Facilitated sessions may reduce the elapsed time to gather requirements, although they require more time commitment from each participant. Kimball prefers using a hybrid approach with interviews to gather the gory details and then facilitation to bring the group to consensus.

List down any two Parallel Software Architectures? 2m

Brief Intro to Parallel Processing:

Parallel Hardware Architectures

• Symmetric Multi-Processing (SMP)
• Distributed Memory or Massively Parallel Processing (MPP)
• Non-uniform Memory Access (NUMA)

Parallel Software Architectures

• Shared Memory
• Shard Disk
• Shared Nothing

Types of parallelism

• Data Parallelism
• Spatial Parallelism

List down any four Static Attributes recorded by the scouts in Agriculture Data Warehouse Case Study. 2m

Static attributes	Dynamic attributes
Farmer name	Date of visit
Farmer address	Pest population
Field acre age	CLCV
Variety sown	Predator population
Sowing date	Pesticide spray dates
Sowing method	Pesticides used

 

List down any four issues of Clickstream Data. 2m

Issues of Clickstream Data:  (Page#341)

Clickstream data has many issues:

 Identifying the Visitor Origin

 Identifying the Session

 Identifying the Visitor

 Proxy Servers

 Browser Caches  

===========================================================

objective was too much easy and almost from moaz file..
Subjective:
1.  What is Web Data Warehouse? (2 marks)

Answer: Page no: 350 Chapter: 39

Web Warehousing can be used to mine the huge web content for searching information of interest. It’s like searching the golden needle from the haystack. Second reason of Web warehousing is to analyze the huge web traffic. This can be of interest to Web Site owners, for e-commerce, for e-advertisement and so on. Last but not least reason of Web warehousing is to archive the huge web content because of its dynamic nature.

2.  What are the four issues of Clickstream Data? (2 marks) repeat

3.  Write first two phases of Kimball's Aproach of business dimensional lifecycle. (2 marks)

Answer= Kimball also proposes a four-step approach where he starts to choose a business process, takes the grain of the process, and chooses dimensions and facts. He defines a business process as a major operational process in the organization that is supported by some kind of legacy system (or systems).

4.  There are four categories of data quality improvement. Write any two. (2 marks)

Ans. The four categories of Data Quality Improvement

• ƒProcess

• ƒSystem

• ƒPolicy & Procedure

• ƒData Design

1. Data profiling is a process which involves gathering of information. What are the purposes that it must fulfill? (3 marks)

Answer: Data profiling is a process which involves gathering of information about column through execution of certain queries with intention to identify erroneous records. In this process we identify the following:

• • Total number of values in a column
• • Number of distinct values in a column
• • Domain of a column
• • Values out of domain of a column
• • Validation of business rules

We run different SQL queries to get the answers of above questions. During this process we can identify the erroneous records. Whenever we will come across an erroneous record, we will just copy it in error or exception table and set the dirty bit of record in the actual student table. Then we will correct the exception table. After this profiling process we will transform the records and load them into a new table

Student_Info

Ref: Handout Page No. 354

6.  What are the drawbacks of Traditional Web Searchers? (3 marks) repeat

7.  Apply Run length encoding on the given code and write output. (3 marks)

Case-I:    1111111110000111

            Answer: 19#04#13

Case-II:    00001111000000

            Answer: 04#14#06

8.  Identify the given statement as correct or incorrect and justify your answer in either case. (3 marks)

"One-way clustering is used to get local view and Two-way clustering is used to get global view."

Answer: Incorrect

One-way clustering gives global view and bi-clustering gives local view

9.  A pilot project strategy is highly recommended in data warehouse. What are the reasons for its recommendation? (5 marks)

Answer: A pilot project strategy is highly recommended in data warehouse construction, as a full blown data warehouse construction requires significant capital investment, effort and resources. Therefore, the same must be attempted only after a thorough analysis, and a valid proof of concept. A small scale project in this regard serves many purposes such as (i) Show users the value of DSS information, (ii) establish blue print processes for later full-blown project, (iii) identify problem areas and, (iv) reveal true data demographics. Hence doing a pilot project on a small scale seemed to be the best strategy.

10.   Data acquisition and cleansing. (5 marks)

• The pest scouting sheets are larger than A4 size (8.5” x 11”), hence the right end was cropped when scanned on a flat-bed A4 size scanner.

• The right part of the scouting sheet is also the most troublesome, because of pesticide names for a single record typed on multiple lines i.e. for multiple farmers.

• As a first step, OCR (Optical Character Reader) based image to text transformation of the pest scouting sheets was attempted. But it did not work even for relatively clean sheets with very high scanning resolutions.

• Subsequently DEO’s (Data Entry Operators) were employed to digitize the scouting sheets by typing.

Data cleansing and standardization is probably the largest part in an ETL exercise. For Agri-DWH major issues of data cleansing had arisen due to data processing and handling  at four levels by different groups of people i.e.

(i)                 Hand recordings by the scouts at the field level

(ii)               typing hand recordings into data sheets at the DPWQCP office

(iii)             photocopying of the scouting sheets by DPWQCPpersonnel and finally

(iv)             data entry or digitization by hired data entry operators.

11.  A table was given and asked to use bitmap indexes technique and make index tables for "TicketType" and "FlightNo". (5 marks)

12.  1 table dia hua tha us mein Name, item, time aur gender dia hua tha aur sath ye statement di hui thi. (5 marks)

IF

           Items/Time >= 6
Then
           Gender= ‘F’
else
           Gender = ‘M’

a)  Find the accuracy % of given data.

b)  If Name: Ali, Items: 2, time: 14, then find the gender of Ali.

Answer: page 278

The model in our case is a rule that if the per item minutes for any customer is greater or equal than 6 than the customer is female else a male i.e.
The above rule is based on the common notion that females spend more time during shopping than male customers. Exceptions can be there and are treated as outliers.

 

Since for the first record the ration is greater than 6 meaning that our model will assign it to the female class, but that may be an exception or noise. The second and the third records are as per rule. Thus, the accuracy of our model is 2/3 i.e. .66%. In other words we can say the confidence level of our classification model is 66%. The accuracy may change as we add more data. Now unseen data is brought into the picture. Suppose there is a record with name Firdous, time spent 15 minutes and 1 item purchased. We predict the gender by using our classification model and as per our model the customer is assigned ‘F’ (15/1=15 which is greater than 6).

[Amna]

Best file to prepare current subjectives

[Amna]

best files to prepare MCQS other thn moaaz files.

[Amna]

My todays paper of CS614 with solution

1. It is called a _____________ violation, if we have null values for attributes where NOT NULL  constraint exists

• Load
• Transform
• Constraint page 161
• Extraction

1. UAT stands for

• User acceptance testing page 193

1. Implementing a DWH requires ____________ integrated activities.

• Tightly page 289
• Loosely
• Slackly
• Lethargically

1. The application development quality assurance activities  cannot be completed until the data is _____________

• Stabilized page 308
• Identified
• Finalized
• Computerized

1. Normalization is a process of efficiently organizing data in a data base by _________ a relational table into smaller table by projection.

• Composing
• Decomposing page 41
• Joining/merging
• Combining

1. “Dirty data” class of anomalies include
   1. Lexical errors
   2. Integrity constraints violation
   3. Business rule contradiction
   4. Irregularities
   5. Duplication

• i and iii and iv
• i and ii and v
• i and ii

Syntactically Dirty data: lexical errors, irregularities

Semantically dirty data:  integrity constraint violation, business rule contradiction, duplication

Coverage anomalies: missing attributes, missing records

1. Quality sold is stored as fact.

• Additive
• Non-additive
• Association
• Non-association

1. Product selection phase fall in Kimball

• Lifecycle Technology Track page 290
• Lifecycle Data Track
• Lifecycle Analytic Applications Track
• None of the given

1. Give least time to ____  can prove suicidal attempt of DWH project

• OLAP
• De-normalization
• ETL page 313
• None of the given

1. Multan division is the cotton hub

1. Which is not an issue of “Click stream data”.

• Identifying the Visitor Origin
• Identifying the Session
• Identifying the Visitor
• Another option was given which is not issue of click stream.

 

1. HTTP true statement

• Is stateless page 364
• Non world wide web protocol
• Used to maintain session
• Message routing protocol

1. SMP stand for Symmetric Multi-Processing

 

1. K-clustering is equal to sequence of n

• K much greater than n
• K much smaller than n
• K is equal to square of n
• None of the given

1. The ith bit is set to 1, if ith row of the base table has the value for the indexed column. The statement refer to

• Inverted
• Bitmap page 233
• Dense
• Sparse index

1. __________ is a systematic sampling process that provides field specific information on pest pressure and crop injury.

• Pest scouting page 333
• Soil survey
• Seed survey
• Water survey

1. In context of web data ware house. Which is NOT one of way to identify session

• Using asynchronous session tracking protocol
• Using Time-contiguous Log Entries
• Using Transient Cookies
• Using HTTP's secure sockets layer (SSL)
• Using session ID Ping-pong
• Using Persistent Cookies

 

Some mcqs from my midterm paper. 2 underlined MCQs are also included in my final paper

1. The telecommunication data warehouse is dominated by the sheer volume of data generated at the call level _________ area.

• Subject page 35
• Object
• Aggregate
• Details

1. 4NF has an additional requirements which is

• Data is in 3NF and no null key dependency
• Data is in 2NF and no  Multi value dependency page 48
• Data is in 3NF and no multi value dependency
• Data is in 3NF and no foreign key table

1. 3NF remove even more data redundancy than 2NF but it is at the cost of

• Simplicity and performance page 48
• Complexity
• No of table
• Relations

1. In full extraction, data extracted completely from source. No need to keep track of change to the _________

• Data source page 133
• DWH
• Data mart
• Data destination

1. Which is not the characteristics of DWH

• Ad-hoc  access
• Complete repository
• Historical data
• Volatile page 27

1. Experienced showed that for a single pass of magnetic tape that scanned 100% of the record only________ of the records.

• 5% page 12
• 30%
• 50%
• 80%

1. HOLAP provides a combination of relational database access and “cube” data structures within a single framework.  The goal is to get the best of both MOLAP and ROLAP:

• scalability and high performance page 78

1. ____________ are created out of the data warehouse to service the needs of different departments such as marketing, sales etc.

• MIS
• OLAPs
• Data mart page 31
• None of the given

 

Subjective:

 

1. 1.       Write 4 partitioning types of shared nothing in Parallel Software Architecture?

Answer:

Shared nothing RDBMS architecture requires a static partitioning of each table in the database.

How do you perform the partitioning?

• Hash partitioning
• Key range partitioning.
• List partitioning.
• Round-Robin
• Combinations (Range-Hash & Range-List

1. 2.       What is Web data ware house? (Answer in current solution file)

1. 3.       Variants of nested-loop?

Answer:

Nested-Loop Join: Variants

1. Naive nested-loop join

2. Index nested-loop join

3. Temporary index nested-loop join

1. 4.       Is there any strategy to standardize a column

Answer: page 480

There are no fixed strategies to standardize the columns.

1. 5.       Dynamic attributes of agri data ware house(answer in current solution file)

1. 6.       Write 2 limitation of persistent cookies

Answer:

Answer= Limitations

• • It's possible that the visitor will have his or her browser set to refuse cookies or may clean out his or her cookie file manually, so there is no absolute guarantee that even a persistent cookie will survive.
• • Although any given cookie can be read only by the Web site that caused it to be created, certain groups of Web sites can agree to store a common ID tag that would let these sites combine their separate notions of a visitor session into a super session

1. 7.       As the number of processes increase, the speedup should also increase. Thus theoretically there should be a linear speedup, however this is not the case in real. List atleast 2 barrier of linear speedup.

Answer:

• Amdahl’ Law
• Startup
• Interference
• Skew

1. 8.       In context of nested loop join, mention two guide lines for outer table.(answer in current solution file)

1. 9.       Before sitting down with the business community to gather information, it is suggested to set you up for a productive session. Write three activities requirement preplanning phase

Answer:

Requirements preplanning: This phase consists of activities like choosing the forum,  identifying and preparing the requirements team and finally selecting, scheduling and preparing the business representatives.

1. 10.  There are different data mining techniques e.g. “clustering”, “description” etc. Each of the following statement corresponds to some data mining technique. For each statement name the technique the statement corresponds to. 5m

Answer:

a) Assigning customers to predefined customer segments (i.e. good vs. bad) classification
b) Assigning credit applicants to predefined classes (i.e. low, medium, or high risk)  classification
c) Guessing how much customers will spend during next 6 months prediction
d) Building a model and assigning a value from 0 to 1 to each member of the set. Then classifying the members into categories based on a threshold value. Estimation
e) Guessing how much students will score more than 65% grades in midterm. Prediction

 

1. 11.  Write down any two drawbacks if “Date” is stored in text format rather than using proper date format like “dd-MMM-yy” etc. 5m

1. 12.   Data acquisition and cleansing.

Answer:

• The pest scouting sheets are larger than A4 size (8.5” x 11”), hence the right end was cropped when scanned on a flat-bed A4 size scanner.

• The right part of the scouting sheet is also the most troublesome, because of pesticide names for a single record typed on multiple lines i.e. for multiple farmers.

• As a first step, OCR (Optical Character Reader) based image to text transformation of the pest scouting sheets was attempted. But it did not work even for relatively clean sheets with very high scanning resolutions.

• Subsequently DEO’s (Data Entry Operators) were employed to digitize the scouting sheets by typing.

Data cleansing and standardization is probably the largest part in an ETL exercise. For Agri-DWH major issues of data cleansing had arisen due to data processing and handling  at four levels by different groups of people i.e.

(i)                 Hand recordings by the scouts at the field level

(ii)               typing hand recordings into data sheets at the DPWQCP office

(iii)             photocopying of the scouting sheets by DPWQCPpersonnel and finally

(iv)             data entry or digitization by hired data entry operators.

 

 

[salma]

Thanks for sharing. 

[sumaira shabbir]

thnx 4 sharing  friends 

[Faiʀy Qu££n]

1. K-clustering is equal to sequence of n

• K much greater than n
• K much smaller than n
• K is equal to square of n
• None of the given

Ans??? 

[sumaira shabbir]

i think 

• K is equal to square of n   

[Amna]

i think greater hoga... Q k aik jaga ye aya ha notes mai

Relatively efficient: O(tkn), where n is # objects, k is # clusters, and t is # iterations.

Normally, k, t >> n.

[sumaira shabbir]

hmmmm