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1. Data Parsing

2. What is Data Parsing?
In the easiest words, data parsing is converting data from one format to another.
For example, if a text is in HTML format, data parsing can help you convert the file
into a more readable format, such as normal text.
It is a popular data transforming process, commonly used in compilers where we
have to parse the computer code into simpler machine code. Likewise, when web
developers write code that runs on hardware, they have to use data parsers. The
exact process is also employed in SQL engines, where SQL engines first parse an
SQL query and then execute it and show the results.

3. Uses of Data Parsing
Data Parsers are used for many technologies and languages, such as:
● Java and other programming languages
● HTML and XML
● Interactive data language and object definition language
● SQL and other database languages
● Modeling languages
● Scripting languages
● HTTP and other internet protocols

4. Different types of data parsing
Grammar driven data parsing: In this technique, the data parser uses a set of
formal grammar rules and accomplishes the parsing task. In simple words,
sentences from unstructured data are first fragmented and then transformed into a
more structured and easily understood format.
Data-driven data parsing: Data-driven data parsing is based on a probabilistic
model of conversion. Unlike the deductive approach of text analysis used by
grammar-driven parsing models, it applies rule-based methods, semantic
equations, and Natural Language Processing (NLP) for structuring the resultant
sentences and their analysis.

5. Work optimization: The most significant advantage of data parsing is that it helps
you navigate through tremendous quantities of data by simplifying it and making it
more readable.
Saving time: Data parsers help businesses by providing them with the right
algorithm or the right tool to extract the data from its present form.
Modernizing Your Data: Data accumulated by businesses can be years old and
may not be available in the current format. In other words, it might be challenging
to make any use of such stored data.
Benefits of Data Parsing software

6. Business workflow optimization: Data parsers help companies structure
unstructured datasets and convert them into usable information. That’s why
businesses use data parsers to optimize their data extraction workflows.
Shipping and Logistics: Businesses that sell online products or services use data
parsing to extract billing and shipping information. Parsing is also used to manage
shipping labels and ensure the data format is correct.
Real Estate: Real estate firms use data parsing technologies to extract data from
real estate emails by property owners and builders or CRM platforms and then
process the information to forward to real estate agents.
Use Cases of Data Parsing

7. Learn More about Data Parsing
https://nanonets.com/blog/what-is-data-parsing/