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What Does Structured and Unstructured Data Mean in Automation?

Posted by OmPrompt on 16 August 2017

Data is at the core of all organisations; customer data, product data or business data. Customer information that comes through on an email might be ‘digital’ but it isn’t digitised. This means that businesses cannot make use of valuable data if it isn’t the right format.

What does Structured Data mean in Automation?

Structured data in automation is text in the form of an unambiguous sequence of letters or symbols that are in conventional layout or format. It is linked information in a format where programs can easily scan to gather accurate information. Some examples of structured data can be found in an Excel spreadsheet where information is placed in an orderly manner. Another example is in Structured Query Language (SQL) that similarly sets data in an orderly fashion. Structured data is essential for automation as it is more accessible for RPA programs to read and gather the necessary information to improve the organisations that use them. When an organisation receives documents such as sales invoices, purchase orders, and surveys to name a few, RPA's are easily able to gather accurate information and update an organisation's database. This produces more efficiency in the supply chain management system of any consumer-oriented business and is one of the largest reasons why strategic automation projects are currently being implemented into many business systems across multiple industries. Some examples of structured data are:

  • Machine-Generated Data
  • Human-Inputted Data
  • Financial Data
  • Web-Captured Data

What does Unstructured Data mean in Automation?

Unstructured data, on the other hand, can be explained as text in the form of a sequence of symbols sometimes embedded within documents that are created in various formats. These materials, regardless how random and arbitrary they are to computers, are still understood by human beings with intelligence and a tolerance for ambiguity. Unstructured data analysis in Robotic Process Automation is extremely crucial as it allows technologies with the capacity to gather an essential information from documents, emails, articles, and many other text platforms. As many businesses incorporate automation as a means to collect and analyse information across multiple text platforms, it is crucial that the technologies are equipped with the right tools to read and analyse unstructured data, which can be classified into the following formats

  • PDF Files
  • Emails
  • Spreadsheets
  • Social media Posts
  • Pictures
  • Audio/Video files

Combining Structured and Unstructured Data in Automation

As data is the official language of automation, technology should have the ability to read and interpret this language in its entirety. Automation is gradually evolving into technology with higher learning capabilities. Combining structured and unstructured data in automation speaks about the ability to read and understand texts completely without error. This ability offers a lot of advantages for organisations such as:

  • Supply Chain Systems will Improve Dramatically. There are numerous areas of supply chain management where Automation is utilised today. Some areas include purchasing, inventory management, warehousing, and distribution. These processes often come with purchase orders, checklists, schedule details, and spreadsheets that are categorised as unstructured data. Shortly when robots can process these various text formats, managing a supply chain will be more efficient than ever as errors will be obliterated and the entire chain will function seamlessly.
  • Customer Service Support will Improve Ten-Fold. Currently, Virtual Agents are being utilised to help organisations provide customer service to their consumers. Virtual agents come in the form of chatbots, which are pop-up chat boxes that are designed to gather and analyse written texts based on the keywords inputted. After recognising specific keywords, chatbots compose customised messages to aid online visitors in browsing through a web page. One major issue with many of these chatbots is they are unable to understand various texts. Because of this, their replies are often of no help to online visitors. With chatbots being able to read and understand structured and unstructured data, they will be able to successfully respond to all queries and provide online visitors with a good customer experience. Not to mention putting automation into back-office processes to free up resource and improve order entry accuracy.

It is only a matter of time before Process Automation can fully comprehend structured and unstructured data in its entirety. Once this can be achieved, customer service, product development, and most supply chain system areas will be optimised to near perfection.


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