The Benefits of NLP (Natural Language Processing) In Business Analytics
A blog about how NLP can be used to make your analytics faster, easier, and smarter.
In this blog post, I’ll share with you just how natural language processing in business analytics can be used to make your data analysis more efficient. By integrating NLP into your business analytics it allows you to analyze the data faster, more efficiently, and much smarter. But let’s start from the beginning.
What is NLP?
Natural language processing (NLP), as the name implies, is all about processing natural languages. Whether it be human language or data in the form of plain text or speech, NLP can process and analyze them both. In short, it’s a tool used for extracting meaning from words. When it comes to business analytics, it can help save time, money and effort.
Tasks performed by NLP are already carried out by humans in some way or another. Some examples include:
- Intelligent search for documents on the internet
- Intelligent question answering systems
- Automatic summarization of documents
- Speech recognition and synthesis which includes automatic call routing systems
- Automatic translation
The release of GPT-3 — the most advanced and largest NLP model ever created — by OpenAI is a big step in language processing. It consists of around 175 billion ‘parameters’ — data points and variables that machines use for language processing. Now, OpenAI is developing GPT-4, a more powerful successor of GPT-3. Speculations reveal that GPT-4 may contain roughly 100 trillion parameters, making it 500 times larger than GPT-3.
Why data analysis is so important in business
Data analysis is important to the business world because it helps companies make smarter decisions. It is also a way to operate more efficiently, since you can get more done in less time with access to data and analytics.
Data analysis is a crucial part of the business. If you are running a business, you are probably gathering data on your customers and other important aspects of your company. Data analysis helps to determine what areas need improvement in order to make your business more profitable.
How NLP is applied in business analytics
Natural language processing (NLP) is the ability of computers to understand human languages through computational methods. It is a branch of artificial intelligence (AI), which is responsible for enabling computers to communicate in human languages.
Till now, we were writing our queries or statements in SQL or some analytical tool. AI2sql is a unique tool that helps you generate SQL queries powered by OpenAI. With AI2sql, you can efficiently generate high-quality SQL queries about tables/columns just by describing the data you need.
Natural language processing helps us by translating our natural language questions into SQL that computers can understand easily. This results in an increased efficiency for us and less time spent writing our own queries to get the data we need.
Natural language processing has many positive effects on business analytics:
- Analysis can be performed quicker.
- Natural language technology is more accurate at understanding meaning
- Natural language technology is user friendly, allowing non-technical users to perform natural language related tasks whenever they need too.
- There are many applications for natural language processing. Its uses are broad and diverse.
There are a number of factors why business analytics are more and more important for a company. Moreover, it can be crucial factor in the success or failure of particular business. As people use natural language to communicate, the potential for extracting insights from data has increased as well. With the help of natural language processing, you can make sure your insights will reflect the real world.
In addition to this, natural language processing makes it easier for your business analytics to be adopted by different departments in your company.
