DADS404 DATA SCRAPPING JULY-AUGUST 2025

Description

SESSION	JULY-AUGUST 2025
PROGRAM	MASTER OF BUSINESS ADMINISTRATION (MBA)
SEMESTER	IV
COURSE CODE & NAME	DADS404  DATA SCRAPPING

 

 

Assignment Set – 1

 

 

Q1. Discuss the legality of scrapping data from any web site. Write about the advantages and disadvantages of manual data scrapping. 5+5

Ans 1.

Data Scraping

Data scraping is the process of collecting information from websites for analysis, research, or business purposes. With the rapid growth of online platforms, scraping has become an important technique in data analytics and decision-making. However, the practice of extracting data from websites raises several legal and ethical concerns that must be carefully evaluated before implementation.

Legality of Data Scraping from Websites

The legality of data scraping depends largely on the type of data being collected, the purpose of collection, and the rules defined by the website owner. Scraping publicly available data is

 

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Q2. What are different kinds of reviews available on e-commerce platform Amazon? What steps could be followed to extract store these reviews for further analysis?        4+6

Ans 2.

Amazon Reviews

Amazon is one of the largest e-commerce platforms and hosts millions of customer reviews. These reviews significantly influence purchasing decisions and provide valuable insights into customer satisfaction, product quality, and seller performance. For businesses and researchers, Amazon reviews are an important source of unstructured data.

Different Kinds of Reviews Available on Amazon

Product reviews are the most common type of reviews on Amazon. Customers rate products

 

Q3. Write steps to scrap the data from Wikipedia pages. How are python libraries helpful in this?    5+5     

Ans 3.

Data Scraping from Wikipedia

Wikipedia is a widely used open-source knowledge platform that contains structured and semi-structured information on a wide range of topics. Due to its consistent page structure and publicly available content, Wikipedia is often used for academic research, data analysis, and learning data scraping techniques. Data scraping from Wikipedia involves extracting relevant information from web pages in a systematic and ethical manner.

Steps to Scrap Data from Wikipedia Pages

1. Identifying the Target Page And Data Requirements

The first step in scraping data from Wikipedia is identifying the target page and data

 

 

Assignment Set – 2

 

Q4. What kind of data operations come under data wrangling? Discuss the importance of data wrangling for data analysis. 5+5     

Ans 4.

Data Wrangling

Data wrangling refers to the process of cleaning, transforming, and organizing raw data into a usable format for analysis. In real-world scenarios, data collected from multiple sources is often incomplete, inconsistent, and unstructured. Data wrangling ensures that such raw data is prepared properly before applying analytical or statistical techniques.

Data Operations Involved in Data Wrangling

• One of the key operations in data wrangling is data cleaning. This involves handling

 

 

Q5. Why do we need Feedback Scraping? How DPLYR library of R is helpful to extract feedback data?  5+5           

Ans 5.

Need for Feedback Scraping and Role of the DPLYR Library in R

Feedback scraping refers to the process of collecting user opinions, comments, ratings, and reviews from digital platforms such as e-commerce websites, social media platforms, forums, and service portals. In the digital economy, customer feedback is continuously generated in large volumes and reflects real user experiences. Extracting this feedback systematically allows organizations and researchers to analyze customer sentiment, preferences, and

 

 

Q6. What is vendor data? Discuss the steps to scrap the tabular data available on products or services listing platform. 3+7

Ans 6.

Vendor Data

Vendor data refers to structured information related to suppliers or sellers who provide products or services to customers or businesses. This data typically includes vendor names, product listings, prices, specifications, availability, ratings, and service terms. Vendor data is widely used in supply chain management, procurement analysis, price comparison, and market research.

In online platforms, vendor data is usually presented in tabular or semi-tabular formats,