Structured vs Unstructured Data

Advantages and Limitations for Modern Businesses

Data is everywhere, and it's constantly growing in volume and complexity. To make sense of it all, we need to organize and structure it in a way that allows us to extract insights and knowledge. Structured and unstructured data are two types of data that have different characteristics and applications.

Structured Data
Structured data is organized in a predefined format that follows a specific schema or model. It is typically stored in databases and consists of rows and columns of data that can be easily queried and analyzed. Examples of structured data include customer records, inventory and financial data and more.

Benefits of Structured Data
The main benefit of structured data is its ability to be easily analyzed and queried using tools like SQL. Because structured data follows a predefined schema, it's possible to generate reports and perform complex analytical tasks with ease. This makes it ideal for businesses that need to track and analyze large amounts of data quickly.

Structured data is also more easily integrated with other systems and applications. Because it follows a standard format, it's easier to share and exchange data between different applications, reducing the need for manual data entry and improving efficiency.

Restrictions of Structured Data
However, structured data has its limitations. It can only capture a limited amount of information, and it doesn't allow for flexibility in data modelling. Structured data is also not well-suited for capturing unstructured or semi-structured data, such as social media posts or customer feedback.

Unstructured Data
Unstructured data, on the other hand, is data that doesn't follow a predefined schema or model. It can come in various forms, such as text, images, audio, and video, and is often found in emails, documents, social media posts, and other unstructured sources.

Benefits of Unstructured Data
The main benefit of unstructured data is its ability to capture a wide range of information. This includes insights and perspectives that may not be captured by structured data alone, such as customer sentiment, brand perception, and employee engagement.
Unstructured data is also more flexible in terms of data modeling. Because it doesn't follow a predefined schema, it allows for more creative and diverse ways of analyzing and interpreting data.

Restrictions of Unstructured Data
However, unstructured data is more difficult to analyze and query compared to structured data. It requires advanced tools and techniques, such as natural language processing and machine learning, to extract insights from unstructured data effectively.
Moreover, unstructured data may require more storage space and processing power, which can increase costs and complexity.

Taming Unstructured Data
There are ways to tame some unstructured data, allowing you to analyze and get meaning without the need for expensive tools.

For example, Kim Document allows you to take your existing MS Word documents and activate them.  By this we mean you can tag the variable data required in your existing documents, upload the document into Kim and then create a web form using the no-code wizard.  Once published, the web form allows you to capture that data, generate the document or other documents and/or use the data to populate your other systems. In the example of HR, when you onboard a new member of staff, they could complete a New Starter form, and that data would then be used to generate the welcome letter and staff handbook. It can then update the information in Workday and Jira, automatically triggering the request for a new laptop for example.  All this data is captured in a central location which you can then download and interrogate.  

Choosing the right data
What we realize is that both structured and unstructured data have their pros and cons, and organizations should choose the type of data that best fits their needs. Structured data is ideal for applications that require quick and easy analysis of large amounts of data. In contrast, unstructured data is better suited for applications that require capturing a wide range of information and insights. 

By understanding the differences between structured and unstructured data, businesses can make better decisions when it comes to data collection, management, and analysis.