A database is an organized collection of data, generally stored and accessed electronically from a computer system. Where databases are more complex, they are often developed using formal design and modeling techniques. A data structure is a data organization, management, and storage format that enables efficient access and modification. More precisely, a data structure is a collection of data values, the relationships among them, and the functions or operations that can be applied to the data.

The data structure is of 3 different types. For the analysis of data, it is important to understand the three common types of data structures. They are,

• Structured Data
• Semi-structured Data
• Unstructured Data

Structured Data: 

Structured data is comprised of clearly defined data types whose pattern makes them easily searchable. Structured data is the data that conforms to a data model, has a well-defined structure, follows a consistent order, and can be easily accessed and used by a person or a computer program.

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.

Unstructured Data:

Unstructured data is information that either does not have a pre-defined data model or is not organized in a pre-defined manner. Unstructured information is typically text-heavy but may contain data such as dates, numbers, and facts as well.

Web Scraping

Web scraping, web harvesting, or web data extraction is data scraping used for extracting data from websites. The web scraping software may access the World Wide Web directly using the Hypertext Transfer Protocol or through a web browser.

How does Web Scraping work?

Web scraping, in general, is down in 2 ways. Manual scraping and automatic scraping. Copying and pasting of information and data manually is known as Manual scraping. This process is highly intense and needs lots of effort and time-consuming. For any large data set, a manual process is not viable. An algorithm or software is used in Automatic scraping to search and extract data through multiple websites. Automatic scraping can be performed in multiple ways such as Parsers, Bots, and Text. There are so many possible ways to perform web scraping. JavaScript and Python are the two most used languages for web scraping.

Top 5 Web Scraping Practise to Building Structured Database are,

• Content Market Planning
• Brand Identity
• Price Monitoring
• Research & Development
• Competitor Analysis

Content Market Planning:

• For any business irrespective of their size and nature, to find their ideal leads and clients – content plays a key role. Yes – is the answer when asked “if Web Scraping can make your content marketing strategy better?”.
• Data for content marketing is not readily available. The flow of data is very critical for content marketing. Data can be extracted from multiple data sources using web scraping. Using web scraping, we can easily create content that syncs with the customer’s needs. Web scraping can also extract data from whitepapers, reports, audits, and online reviews.
• By extracting information with the help of web scraping from news articles, social media websites such as Facebook – one can write better articles on industry trends, about the new product launch, service offerings, etc.

Brand Identity:

• Web scraping can make a huge difference in brand identity, marketing, and monitoring. Web scraping for branding is a cost-effective and efficient process since this can be customized on the need basis of a company.
• Web crawling tools are preconfigured to collect and store only relevant data. The process can be largely automated. By doing so, one can automatically monitor and collect data from multiple web sources. This helps companies to get a more intimate and holistic view of customers, their opinions, tastes, and preferences.
• The advantages of branding through web scraping are effective brand management, in-depth insight about customers, competitor analysis, tracking and monitoring, real-time response, enhance customer satisfaction, and increase sales.

Monitor Pricing:

• For the business to grow, one of the key strategies is pricing. Be it any leading brand or a new one to the market, pricing strategy is very crucial. If the pricing is higher than the competitors (or) lower than the competitors, then the business is understood to be in a bad shape.
• Web scraping helps you to scrape the price chart. Price charts can be scraped from multiple sources and brands. Once can scrape the entire website (or) a product to determine a pricing strategy. Data inputs can be controlled while using the tool to scrape.
• With the help of web scraping, historical price data of competitors can be used to analyze, understand, and learn the patterns in pricing behavior. By doing so, it is easy to foresee competitors’ short-term and long-term strategies and develop counterstrategies. To obtain high profitability and enhance efficiency, data-driven pricing strategy is the key.

R&D:

• By using traditional methods, only basic information shall be obtained. However, web crawling usage helps to extract information that is more specific and can dig deeper. Web scraping is the common process used by researchers these days. They use web scraping and carry out research on web forums, and social media platforms.
• Web scraping is the best bet for producing critical data to aid in the R&D process. Using web scraping key insights can be obtained about the competition of the existing products. This information shall help to improve the quality of existing products. For any organization, R&D is the most important unit/team for introducing new products and services successfully.
• The features and benefits of a newly launched product by the competitor can be analyzed using web scraping. This information can be utilized in developing new products with improved quality and competitive pricing.

Competitor Analysis:

• Web scraping plays a key role in competitor research and analysis. With web scraping, competitor’s vital information such as pricing strategy, content form, leads reviews, and SEO/SMM strategy can be extracted.
• Once the data is extracted using web scraping, the data can be used to improve the current solution and define it in a way to create interest and attention among the target audience to draw more closely to what you have to offer.
• Competitors SEO strategy, PPC spend, product pricing, product line auditing, reviews and comments for their products/services, and information about funding – All the mentioned information can be collected and analyzed using web scraping.

Web scraping plays an important role in competitor research and analysis. Manually collecting a huge amount of information from the web is next to impossible. Hence, web scraping is used to gather all the data. If you need a partner to work with you on web scraping, talk to our expert team and get their professional views and suggestions.