How Unstructured Data Can Help You Fill the Gaps in Your Analysis
IDC estimates that unstructured data will make up 80% of all data by 2025. The reason for this high percentage is that unstructured data comes from a number of different sources, including social media comments and reviews, images, audio, medical reports, and even the emails people write to both customers and colleagues.
Characteristics of Unstructured Data
The primary difference between structured and unstructured data is that the latter does not follow any particular format or rules related to structure. This data cannot be stored in rows and columns, and no pre-defined data model can be identified just by looking at it. Due to the lack of structure, this data is inherently difficult to organize and can even contain several duplicates or inaccurate values.
The Case for Unstructured Data
Unstructured data can exist in a variety of formats and does not have any pre-defined schema or rules, which is why it can be very difficult to extract value from it. As a result, most unstructured data is never used for business intelligence or analytics.
This can be a limitation, especially when it comes to decision-making and driving innovation primarily because unstructured data can potentially contain a lot of useful information that businesses can leverage. Add to this the fact that 58% of respondents of a survey on data-driven decision-making say that less than half of the business decisions at their companies are driven by data and information, and it’s easy to understand how much more value businesses can extract by making sense of unstructured data.
Take the example of a hospital. While patient IDs and appointment dates are generally in a structured format, a lot of other relevant information such as prescriptions, medical history, and patient feedback are stored in TXT files and PDFs. All of this information, when viewed together, can help hospitals draw valuable insights and improve the quality of patient care offered.
With unstructured data extraction and management extraction and management, businesses can get a better understanding of the bigger picture thanks to the ‘unconventional’ data that they are able to use. Additionally, using tools to manage unstructured data, businesses can also use make use of data stored in multiple locations and finally export it to their destination of choice for business intelligence or any other purpose.
The infographic below shows why managing unstructured data is challenging, why you should add structure to it, and use cases to understand how it can be leveraged in various settings and industries.