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CS614 Assignment 01 Spring 2021 Solution / Discussion Due Date: 24-05-2021

Assignment No. 1(Graded)

Semester Spring 2021
Data Warehousing– CS614

Total Marks: 20

Due Date: 24-05-2021

Objective:

This assignment has been designed to develop your ability about basic data warehouse and different issues related to DWH. 

Instructions:

Please read the following instructions carefully before solving & submitting the  assignment:

1.      The assignment will not beaccepted after due date.

2.      Zero marks will be awarded to the assignment that does not open or the file is corrupt.

3.      The assignment file must be an MS Word (.doc) file format; Assignment will not be accepted in any other format.

4.      Zero marks will be awardedto the assignment if copied (from other students, internet or any source).

5.      Zero marks will be awardedto the assignment ifthe Student ID is not mentioned in the assignment file.

For any query about the assignment, contact only at CS614@vu.edu.pk

 

Please do not post queries related to assignment on MDB.

 

Note:The assignment covers lectures 1-10.

 

 

Question 1  (Marks 10)                                                  

 

Suppose that you are the data analyst on the project team building a data warehouse for an insurance company. List at least three data sources from which you will bring the data into your data warehouse?

 

Question 2  (Marks 10)

Data warehouse systems often have complexity issues due to many business requirements. Technical complexity issues arise from three areas: sourcing issuestransformation issues and target issues.

Write at least two examples of each (Not more than one line for each).

 

Note: Deadline for assignment submission is 24 May 2021.

Wish you best of Luck!

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CS614 Assignment 1 Solution Spring 2021

 

Question NO 1 Solution

Operational Database

The Operational Database is the source of Information for the data warehouse. It includes detailed information used to run the day-to-day operations of the business. The data frequently changes as updates are made and reflect the current value of the last transactions. An operational database is a database instance that creates or updates large amounts of data in real-time. This can be based on any number of database technologies that support the availability levels, speed, concurrency, data integrity and recoverability required.

 

Archive data

The archive data store is almost always represented in relational format. If the source I can be brought back into service. data is relational, the mapping between the two is straightforward. However, some source databases will not be relational and will require some work to make them relational. Data archiving is the practice of identifying data that is no longer active and moving it out of production systems into long-term storage systems. Archival data is stored so that at any time it

The archive datastore must be managed in a way that ensures its long-term viability. This is the main objective.

Benefits of Data Archiving:

  • Reduced cost:
  • Better backup and restore performance:
  • Prevention of data loss
  • Increased security
  • Regulatory compliance

 

Semi-structured data

Semi-structured data is a form of structured data that does not obey the tabular structure of data models associated with relational databases or other forms of data tables, but nonetheless contains tags or other markers to separate semantic elements and enforce hierarchies of records and fields within the data. Semi-structured data is a combination of structured and unstructured data and shares characteristics of both. It also follows certain schema, consistency, and exists to ease space, clarity. CSV, XML and JSON documents are semi-structured documents. No SQL databases are considered popular to handle semi-structured data.

 

Question No 2 Solution

 

Transformation issues:

It takes various tests, each of which takes time and is time-consuming when applied to larger data sets, making it less accurate. During the transition, a lack of experience and carelessness can cause issues. A variety of limitations exist in data warehouses, such as data authentication being fake at times. In certain instances, data authentication is not feasible.

 

Target Issue:

The final stage is Load, which is an operation that involves loading data that has not been cleaned into the target system, resulting in an error. Irrelevant loading causes an error in the target scheme.

 

Sourcing Issue:

Database path is incorrect

Creating bottlenecks due to insufficient CPU or Memory resource Saving DATA in URDU, FARSI in Database.

CS614 Assignment 1 Solution Spring 2021 || Data Warehousing || 100% Correct Solution

Download CS614 Assignment Solution File: https://bit.ly/3yroojD

#CS614 Assignment 1 Solution Spring 2021
Question NO 1
Solution
Operational DB
The Operational Database is the source of
Information for the data warehouse. It includes
detailed information used to run the day-to-day
operations of the business. The data frequently
changes as updates are made and reflect the current
value of the last transactions. An operational
database is a database instance that creates or
updates large amounts of data in real-time. This can
be based on any number of database technologies
that support the availability levels, speed,
concurrency, data integrity and recoverability
required.
Archive Data
The archive data store is almost always represented
in relational format. If the source I can be brought
back into service. data is relational, the mapping
between the two is straightforward. However, some
source databases will not be relational and will
require some work to make them relational. Data
archiving is the practice of identifying data that is no
longer active and moving it out of production
systems into long-term storage systems. Archival
data is stored so that at any time it
The archive datastore must be managed in a way that ensures its long-term viability. This is the
main objective.
Benefits of Data Archiving:
> Reducedcost:
> Better backup and restoreperformance:
> Prevention of dataloss
> Increasedsecurity
> Regulatorycompliance
Semi-structured data
Semi-structured data is a form of structured
data that does not obey the tabular structure
of data models associated with relational
databases or other forms of data tables, but
nonetheless contains tags or other markers
to separate semantic elements and enforce
hierarchies of records and fields within the
data.
Semi-structured data is a combination of
structured and unstructured data and shares
characteristics of both. It also follows certain
schema, consistency, and exists to ease
space, clarity. CSV, XML and JSON
documents are semi-structured documents.
No SQL databases are considered popular to
handle semi-structured data.
Question 2
Solution
Target Issue:
The final stage is Load, which is an operation that involves loading data that has
not been cleaned into the target system, resulting in an error. Irrelevant loading
causes an error in the target scheme.
Transformation issues:
It takes various tests, each of which takes time and is time-consuming when applied
to larger data sets, making it less accurate. During the transition, a lack of
experience and carelessnesscan cause issues. A variety of limitations exist in data
warehouses, such as data authentication being fake at times. In certain instances,
data authentication is not feasible.
Sourcing Issue:
Database path is incorrect
Creating bottlenecks due to insufficient CPU or
Memory resource Saving DATA in URDU, FARSI
in Database

CS614 Assignment 1 Solution Spring 2021

 

Question NO 1 Solution

Operational Database

The Operational Database is the source of Information for the data warehouse. It includes detailed information used to run the day-to-day operations of the business. The data frequently changes as updates are made and reflect the current value of the last transactions. An operational database is a database instance that creates or updates large amounts of data in real-time. This can be based on any number of database technologies that support the availability levels, speed, concurrency, data integrity and recoverability required.

 

Archive data

The archive data store is almost always represented in relational format. If the source I can be brought back into service. data is relational, the mapping between the two is straightforward. However, some source databases will not be relational and will require some work to make them relational. Data archiving is the practice of identifying data that is no longer active and moving it out of production systems into long-term storage systems. Archival data is stored so that at any time it

The archive datastore must be managed in a way that ensures its long-term viability. This is the main objective.

Benefits of Data Archiving:

  • Reduced cost:
  • Better backup and restore performance:
  • Prevention of data loss
  • Increased security
  • Regulatory compliance

 

Semi-structured data

Semi-structured data is a form of structured data that does not obey the tabular structure of data models associated with relational databases or other forms of data tables, but nonetheless contains tags or other markers to separate semantic elements and enforce hierarchies of records and fields within the data. Semi-structured data is a combination of structured and unstructured data and shares characteristics of both. It also follows certain schema, consistency, and exists to ease space, clarity. CSV, XML and JSON documents are semi-structured documents. No SQL databases are considered popular to handle semi-structured data.

 

Question No 2 Solution

 

Transformation issues:

It takes various tests, each of which takes time and is time-consuming when applied to larger data sets, making it less accurate. During the transition, a lack of experience and carelessness can cause issues. A variety of limitations exist in data warehouses, such as data authentication being fake at times. In certain instances, data authentication is not feasible.

 

Target Issue:

The final stage is Load, which is an operation that involves loading data that has not been cleaned into the target system, resulting in an error. Irrelevant loading causes an error in the target scheme.

 

Sourcing Issue:

Database path is incorrect

Creating bottlenecks due to insufficient CPU or Memory resource Saving DATA in URDU, FARSI in Database.

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