Structured data is often referred to as the easiest one to manage because it is methodically organised in columns and lines. A classic example of structured data would be an excel file for instance, in which your data is stored in a way that makes it easy to process. This quantitative data is frequently used by businesses and used to be the one that prevailed, precisely due to the fact that it is fairly simple to analyse and store.
The elements present within structured data are divided into predefined categories, hence it is not that flexible, as the graph below attests.
While structured data does not require much space, it is more difficult to collect than the other types that will be mentioned in the following sections. This can be explained by its quantitative nature.
Every single structured data has to serve a purpose, you cannot use it for anything else.
So, what kind of data do companies seek to collect? Usually, it will look for basic information such as your name, email address, postal address or even location. Now that structured data has been defined, let us take a look at unstructured data and its characteristics.
Unstructured data is pretty much the opposite of structured data as the graph above shows. Unlike structured data, unstructured data does not have a predefined structure, thus it makes its search more challenging. As Forbes stated, this issue has been solved thanks to “the recent proliferation of artificial intelligence and machine learning algorithms [which] made it easier to process.”
What characterises unstructured data is its qualitative nature and the fact that it is not held or controlled within a mere excel sheet or a column/line database.
Examples of unstructured data include PDFs, audio and video files, social media content, etc.
The last category that can be mentioned when talking about Big Data is semi-structured data. This is essentially structured and unstructured data combined.
What makes semi-structured data interesting is that it has enough properties to make its analysis fairly manageable. As mentioned by the company HubSpot, “semi-structured data is information that does not reside in a relational database or any other data table.” Semi-structured data examples include emails or even HTMLs.
2OS: a no-code platform which uses Big Data
2OS is a no-code platform which is a mixture of various technologies, including Artificial Intelligence (AI), Big Data, analytical tools, integration, etc. This whole process is behind 2OS’ success. Want to know more about no-code? This article is here to help you.
Thanks to the 2OS no-code platform, you merely need a few hours to create an AI application without any line of code. The interactive guide enables you to immediately use our platform without any instructions or training.
The 2OS platform uses various technologies including AI, Big Data and analysis tools, automation of robotic processes, integration and interoperability in the cloud. All of them are managed exclusively in the no-code universe.
Regardless of the topic (Financial AI, Business Process Automation, Risk Management, Compliance, Automatic, Document Analysis, KYC…) or the industry in which you are specialised (Finance, Banking, Insurance, Healthcare, Law, Accounting…), 2OS will solve your problems with unprecedented efficiency.
The 2OS platform also provides you algorithms with which you can analyse your documents and data so as to extract useful information with strong value-added (DocReader). You can also measure the market yields of your brands and products (Sentiment Analysis), and learn how to better communicate with your customers (Know Your Customer/Name Screening), etc.
With 2OS you can create an intelligent application while respecting the integrity of your data & the highest IT security standards. 2OS has successfully invested in different R&D activities such as text-data mining, big data analysis, and automatic generation of algorithms. The outcome is concrete results delivered to our customers, streamlined processes and significantly improved business operations.