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Manual VS Automated Web Data Extraction

In today’s scenario, anything is deemed incomplete without proper data to support it. Web data extraction isn’t just about comparative advantage now. It adds to the credibility of any report, person, or organization.

In the current data-driven world, users are faced with the choice of data extraction technique they want to use: manual or automated web data extraction techniques. This choice might differ from user to user, but one cannot help but emphasize the importance of each method before choosing.

In this article, we will explore and understand the differences between manual and automated web data extraction techniques.

What is web data extraction?

Web data extraction refers to the process of extracting data from websites and organizing that data into an understandable format. In simple words, extracting web data involves gathering a wide range of information, such as product details, news stories, social media content, and financial reports, from different online sources.

This data is then organized and stored in spreadsheets and databases for further analysis and use. The data extracted via these extraction techniques can then be processed and used for several purposes, like content monitoring, market analysis, lead generation, and other research purposes.

The Data Extraction blog will give you a quick review of benefits and challenges of Data extraction. If you need to know about various data extraction tools you can give the Top 5 data extraction techniques blog a thorough read.

Methods of web data extraction

This segment of the blog will brief you about the available methods of data extraction and a few examples to help ensure clarity on each method.

There are three main methods that you can use while extracting data from various websites.

1. Manual web data extraction

  • Manual extraction involves extracting data from various sources and storing it in databases or spreadsheets.
  • This involves manually copying and pasting chunks of data from websites and storing them for further use.
  • To ensure efficient extraction, you can keep track of websites and URLs you extract your data from. This helps maintain transparency, consistency and use them for future referencing.
  • You can also seek help from browser extensions, plugins or tools like web scrapers, copy-paste helpers and data extractors, to ensure efficient manual web extraction.

2. Automated web data extraction

  • Automated extraction refers to the process of extracting and storing large chunks of data from websites in spreadsheets and databases.
  • Unlike manual method of extracting data, tools like Extract-Transform Load (ETL) are used to extract data and store it in an understandable format.
  • Web scraping tools like Beautiful Soup, Scrapy, etc., offers a variety of features that help dealing with complex data.
  • You can use API scraping tools like Newsdata.io, ParseHub and Octoparse, to access data from various websites using APIs.
  • Another alternative is using web scrapers like Python and Import.io, to extract highly accurate and up-to-date data from a given website.

3. Hybrid web data extraction

  • Hybrid extraction refers to combining both manual and automated extraction techniques. It combines efficiency and precision, overcoming any obstacles faced in manual and automated data extraction.
  • You can apply machine learning models like Decision trees and Naive Bayes, to ensure only relevant and useful data is extracted and any irrelevant data is left out.
  • The extracted data can then be reviewed manually to ensure there is no missing information or errors in the data.

Factors of Differentiation

This segment of the blog focuses on the various points of difference that will be considered while distinguishing between manual and automated data extraction techniques.

Among the several factors that make manual and automated web data extraction techniques different from each other, given below are a few main points of difference.

1. Time & labour

Time and labour levied in using a particular data extraction technique play a crucial role, as it helps decide how much time and labour you need to invest to get the desired results. The time and labour investment vary for both manual and automated data extraction techniques, as do the results obtained.

2. Cost-Effectiveness

The next factor of difference is cost-effectiveness, i.e., how much cost you will have to incur to extract data from websites into understandable formats. This cost might vary depending on the requirements of each data extraction technique.

3. Proneness

The next factor in line is Proneness, i.e. proneness of the data extraction technique to difficulties of human errors, complex website structures, etc. A certain method can be prone to several difficulties that might hinder an efficient and effective web extraction of data.

4. Scalability

Scalability is the next factor contributing to the difference between the two methods of data extraction. It varies for both methods of data extraction as per the size of the data that is to be extracted from the websites.

5. Investment

The investment required for carrying out an extraction technique differs based on the resources and technology used in the given method of data extraction. While the investment might be in the manpower for one of the extraction techniques, it might not be the case for the other.

6. Consistency & Contextual Understanding

The last factor of difference is the consistency and contextual understanding offered by the given data extraction technique. The contextual understanding here refers to the ability to comprehend and interpret information under any given circumstance. On the other hand, consistency here refers to the ability to maintain the same pattern of data extraction and interpretation throughout the process.

Manual VS Automated Web Data Extraction Techniques

Points of Differences
Manual Web Data Extraction Techniques
Automated Web Data Extraction Techniques
Time & LabourThese techniques are done manually, thus proving to be time-consuming and labour-intensive.These techniques rely on ETL tools, making them comparatively faster and less labour-intensive.
Cost-EffectivenessThe employing of lots of labour makes these techniques a lot more than costly.These techniques have proven to be comparatively cost-effective.
PronenessThese techniques are carried out manually and are more prone to human errors like typos and oversight.This method uses techniques like web scraping and is prone to difficulty with complex or dynamic website structures.
ScalabilityThese techniques provide limited scalability, especially when dealing with large datasets.These techniques are comparatively more scaled and can handle large chunks of data without much difficulty.
InvestmentThe user needs to invest in terms of labour in this method of web data extraction.The user needs to invest in technology and expertise in this method of web data extraction.
Consistency & Contextual UnderstandingManual web data extraction techniques lack consistency but provide contextual understanding.Automated web data extraction techniques lack contextual understanding but make up for it by ensuring consistency.

Drawing Conclusion

After a thorough study of manual as well as automated web data extraction techniques, we couldn’t help but notice the presence of certain points where one of the data extraction techniques complemented the other.

For instance, manual extraction techniques lacked consistency but provided contextual understanding, whereas automated extraction techniques lacked contextual understanding but provided consistency.

In a way, instead of looking at them as substitutes, they can be perceived as complementary to each other. Thus, the third and best alternative for extracting techniques is hybrid web data extraction. In this method of data extraction, you combine the pros of both manual and automated data extraction techniques to extract large amounts of data while still having some sort of control over the quality.

Frequently Asked Questions

Q1. What is manual web data extraction?

Manual web extraction involves extracting data from various sources and storing it in databases or spreadsheets. This involves manually copying and pasting chunks of data from websites and storing them for further use.

Q2. What is automated web data extraction?

Automated web extraction refers to the process of extracting and storing large data from websites in spreadsheets and databases. Unlike manual extraction, tools like Extract-Transform Load (ETL) are used to extract data and store it in an understandable format.

Q3. Can you use manual web data extraction for complex extraction tasks of data?

For complex extraction tasks of data, it is recommended to use automated data extraction techniques. This is so because the ETL (Extract-Transform Load) tools making it faster and convenient to extract data from websites.

Q4. Which method is more cost-effective: manual or automated web data extraction techniques?

Automated web data extraction techniques are more cost-effective as compared to manual extraction techniques. This is so because they are effective and help avoid the cost of employing labour as is done for manual extraction.

Q5. Which method is the best for web data extraction?

While both methods have their advantages, several disadvantages might make you contemplate your decision. In such cases, hybrid web data extraction techniques take the lead and balance out the disadvantages of both methods.

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