Web data extraction and data scraping: Big Data – Hadoop way

A few years back, it was all manual data mining and it took long long days for almost all small and medium players in the market for web data mining. Today, technology is evolving a lot and we are in an era of Big data and manual data mining is no more a right method and it is mostly about automation tools, custom scripts, or Hadoop framework.

Now, let us discuss something about web data extraction. It is a process of collecting data from World Wide Web using some web scrapper, crawler, manual mining, etc. A web scrapper or crawler is a cutting tool for harvesting information available on internet. In other word web data extraction is a process of crawling websites and extract data from that page using a tool or programming. Web extraction is related to web indexing which refers to various methods of indexing the contents of web page using a bot or web crawler. A web crawler is an automated program, script or tool using that we can ‘crawl’ webpages to collect multiple information from websites.

In the world of big data, data comes from multiple sources and in huge amount. In which one source is web itself. Web data extraction is one of the medium of collecting data from this source i.e. web. Companies which are leveraging big data technology are using crawlers or programming to collect data. These data comes in bulk i.e. billions of records, or as a data dump. So, it needs to treat as big data and bring into Hadoop Eco system to get quick insight from it.

There are multiples areas where companies can explore web data extraction. Some areas are:

• In ecommerce, companies use web data extraction to monitor their competitor price and improve their product attributes. They also fetch data from different web sources to collect customer review and using Hadoop framework they do analysis – including sentiment analysis.
• Media companies use web scraping to collect recent and popular topics of interest from different social media and popular websites.
• Business directories use web scraping to collect information about the business profile, address, phone, location, zip code, etc.
• In healthcare sector, health physician scrap data from multiple websites to collect information on diseases, medicine, components, etc.

When companies decide to go for web data extraction today, then they move ahead thinking about big data because they know that data will come in bulk i.e. in millions of records will be there and it will be mostly in semi or unstructured format. So, we will need to treat it as big data and use Hadoop framework and tools for converting it for any decision making.

In this whole process, first step is web data extraction, that can be done using different scraping tools available in market (there are free and paid tools are available) or create custom script using programming language with the help of expert in scripting language like Python, ruby, etc.

Second step is to find insight from the data. For this, first we need to process the data using the right tool based on the size of the data and availability of the expert resources. Hadoop framework is the most popular and highly used tool for big data processing. Also, for sentimental analysis of those data, if needed, we need MapReduce which is one of the components of big data (Hadoop).

To summarize, for web data extraction, we can choose different tools for automation or develop scripts using programming language. Developing a script is often minimize effort as it is reusable with minimal modification. Moreover, as the volume of web data is huge-what we extract, it is always advisable to go for Hadoop framework for quick processing.