The human brain is an astounding creation of Mother Nature. The mechanisms behind the complex set of functions that it performs so effortlessly are yet to be discovered and understood in its complete depth. One function of the brain that has intrigued scientists for several years now is that of breaking apart a long string of letters into words and then finding meaning out of them to form a sentence. The tireless efforts that went into understanding and then emulating the same, helped scientists in incorporating a similar function into computer syntax analysis. It is this capability of our computers that we call Data Parsing.
To understand the technicalities and the possibilities of data parsing, let us take a deeper look into the concept with this blog today.
Data parsing is defined as a process where a computer creates a functional and machine-usable form of the data present in a file. Data parsing is an integral step of programming that follows lexing in a series of different stages involved. Essentially, the process allows you to analyze special characters in a given data using Natural Language Processing. Further, it is combined with a process called extraction, which is concerned with structuring data into sets and then finding a meaning to it. Extraction occurs via user-defined rules.
What is A Data Parser, and How Does it Work?
A compiler component that implements the process of data parsing is called a data parser. Businesses require a data parser because it is the only way in which they can ascertain which part of an HTML string is important and needs to be extracted. Further, it will facilitate the extraction of necessary data and then convert it into a convenient format like JPEG, PDF, etc.
Reiterating the fact here that data parsers work completely on user-defined rules. This means that firstly their processing is not tied to formats. Rather it involves conversion from one format into another. Secondly, the manner in which this conversion takes place will depend on how the data parser was coded in the first place. HTML is not the only one area where parsers are considered useful. They are actively used in Java and other programming languages too. It is also used for Modeling languages, Scripting languages, and SQL.
Benefits of Data Parsing for Industries
● Operations Optimization
Businesses have loads of data in the unstructured format, which is hard to analyze, process, and interpret. A data parser automates the structuring of such data, giving support to data extraction workflows. So, in fields where data extraction is an important everyday task, data parsers play a pivotal role. These include the likes of investment analysis, business applications, social media management, etc.
● Logistics Management
Companies involved in logistics have to deal with tons of data related to billing and delivery. A data parser makes it very convenient for them to extract shipment and billing details without any manual handling. It is the job of data parsers to maintain a uniform format for all data and arrange the shipping labels for orders.
● Real Estate Dealing
Property dealers and real estate developers are actively using data parsers to extract lead data from emails. Data from several CRM platforms is also being extracted using these applications so as to guide the marketing strategies for real estate agents. Details like contact numbers, property addresses, and cashflow details are all managed effectively using data parsers.
● Finance Firms
The banking industry is leveraging the benefits of data parsers to a great extent. Probably banks and financial firms get the largest chunk of physical forms related to KYC’S, loan sanctions, etc. A data parser helps bank employees to extract and verify important and relevant information stored in these forms so as to complete these processes promptly.
Features Of A Good Data Parser
The maximum utility of a data parser can be realized only when it is custom-made for the operations that you want to perform. The advantage of a custom-made data parser is that it can be created in any programming language. A good data parser is also flexible with multiple data formats. Moreover, the litmus test for any data parser is that the user should be able to input data in any format and also get an output in a format of their choice. Usually, building a data parser that guarantees all this becomes very expensive, and hence, companies turn to external service providers for the same.
KlearStack Data Parsing API
KlearStack’s’ data extraction tools enjoy a remarkable reputation among users. Our AI-based OCR software provides the best combination of smart computing and conversion of data in unstructured files into digitally usable forms. The software is based on advanced Machine Learning models that support fast character recognition and classification. To enjoy these exclusive benefits and optimize your business operations, contact KlearStack today.