Semi-structured is made up of partially unstructured data and partially data structure created by metadata. It is an interesting intersection between the two data types and it can yield transformational insights when analyzed. A good example of semi-structured data is an X-ray. An X-ray consists of a great many pixels. The sheer volume of pixels cannot be searched, queried, and analyzed like structured data. However, X-rays, like most files, contain metadata. This “data about data” is what enables semi-structured and unstructured data to be harnessed.
Every day data is used to shape the direction of businesses, develop new business offerings, and gain a competitive advantage. In a market where businesses pursue innovation and thrive off disruption, harnessing data is integral to success.
Data is everywhere. It comes in different shapes and sizes. There are three different types of data: structured data, unstructured data, and semi-structured data.
Structured data is what has traditionally been thought of as data. It exists in predefined formats and is easily accessible by the average user. Unstructured data is the new frontier of data. It lacks a predefined format akin to endless chaos of data full of powerful insights. The middle between structured data and unstructured data is semi-structured data.
Semi-Structured Data Examples
An X-ray is just one example of unstructured data. Upon further examination, numerous examples of unstructured data can be found in everyday business operations.
Email is a great example of semi-structured data. The popularity of the Internet and the proliferation of social media has created a deluge of new data. This data comes in flexible formats collected from a vast population sample. Digital communications such as emails are a source of semi-structured data. This is because every email has:
– “To” line
– “From” line
– Date stamp
– Time stamp
The above fields are sources of structured information. However, the text body of an email is a form of unstructured data. There is no defined format or character limit for the body of an email. Emails collected, searched, and analyzed across an enterprise can represent a powerful source of information and record-keeping. Furthermore, emails can provide data mining opportunities to:
– Analyze customer feedback
– Streamline customer support
– Target marketing initiatives
– Develop social media initiatives
– Shape strategic initiatives
The overwhelming popularity of the Internet has produced a lot of content. Another example of semi-structured data is web pages. Most web pages have an organization with tabs for:
– About Us
These tabs are easy to navigate and search thus representing structured data. However, the web pages are written in HTML containing text and data within each of these pages that have no structure. A wealth of information lies hidden in web pages across the internet. Once a business knows how to leverage digital resources, both internal and external, it will become more successful.
Unstructured Data Vs. Semi-Structured Data
The availability of semi-structured data poses the question: what is the difference between semi-structured and unstructured data? It is a grey area that leaves a lot open to interpretation. All documents, images, and other files have some form of data structure. Therefore, it is hard to distinguish where semi-structured data ends and unstructured data begins. Both semi-structured and unstructured data lack organization and rules that are present in a relational database of structured data.
As more technological advances of data analytics tools evolve, the understanding of semi-structured data and how it relates to unstructured and structured data will deepen. For now, semi-structured data remains a prolific presence on the internet capable of taking businesses forward into the future.