![]() ![]() Following are some of the qualities that an enterprise-grade web scraping solution should have: The latter is more inclined towards the extraction of data from the web for real-world applications and hence requires advanced solutions that are built for the same. However, if we consider the practical applications of the data, it’s obvious that there’s a clear distinction between mere web scraping and enterprise-grade web data extraction. Web scraping is only a common term for the process of saving data from a web page to a local storage or cloud. Scraping tools cannot cater to the requirements of a business as it could be well out of their capabilities. Unless you are a hobbyist looking to extract a few web pages for tinkering with a new data visualization tool, you should steer clear from web scraping tools. For starters, tools aren’t meant for large-scale extraction which is what most businesses will require. However, Google docs and other web data extraction tools come with their own limitations. You could check out our guide on using google sheets to scrape a website if you want to learn something that might come handy. ![]() You can even use Google docs to extract data from a simple HTML page if you are looking to understand the basics of web scraping. Today, there are various solutions catering to the web data extraction requirements of companies DIY tools to managed web scraping services are out there and you can choose one that suits your requirements the best.Īs we mentioned earlier, there are so many different ways to extract data from the web although not all of these would make sense from a business point of view. Since the scope of extraction was limited back then, the extraction methods mostly comprised of manual methods like copy-pasting text into a local document.Īs businesses realized the importance of web scraping as a big data acquisition channel, new technologies and tools surfaced with advanced capabilities to make web scraping easier and efficient. Hence, go through the demands of your thesis first before indulging yourself into data collection.Įver since the data on the web started multiplying in terms of quantity and quality, people have sought out ways to scrape or extract this data for a wide range of applications. But, these data collection techniques vary according to problem generated in the thesis. Thus, if researcher wants to bring up to date, reliable and factual data's they should prefer primary source of collection. Secondary data is easy to collect as they are pre-collected and are preferred when there is lack of time whereas primary data's are tough to amass. Limitation of these is that they may not be the updated one or may be manipulated as it is not collected by the researcher itself. Data's are collected from articles, bulletins, annual reports, journals, published papers, government and non-government documents and case studies. Secondary Technique - In this technique the data is collected from the pre-collected resources they are called as secondary data's. ![]() On the other, hand the advantage is in the court of most updated data as it is directly collected from the source. For example - personal in-depth interviews and questionnaires are self-analyzed data collection techniques, but its limitation lies in the fact that self-response can be sometimes biased or even confused. Self-analysis is a sub classification of primary data collection - As understood here you get self-response for a set of questions or a study. Primary Technique - Here, the data is collected by the first hand source directly are known as primary data's.So, let's have a broader look on the different data collection techniques which gives a reliable ground to your research. Whereas if the topic is like "Causes of performance appraisal", then the demanded data would be objective and in the terms of figures which shows different parameters, reasons and factors affecting performance appraisal of different number of employees. Also their collection techniques vary along with the topic in detail for example if the topic is like "Changing era of HR policies", the demanded data would be subjective and its technique thus depends on the same. ![]() These data's are collected according to the demand of research topic and its study undertaken. These facts and figures which are required to prove the fundamentals of study are known as "data's". Re-search in itself means searching on a searched content and this involves some proven fact along with some practical figures reflecting the authenticity and reliability of the study. Irrespective of the grade of the topic and the subject of research you have chosen, basic requirement and process of all remains same i.e. ![]()
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