For businesses committed to innovation, unstructured data presents a lot of opportunities. In an enterprise, data is everywhere. It comes in different shapes and sizes ready to be analyzed for business intelligence. Historically, businesses have relied on structured data for insights. The predefined format and accessibility of structured data lends itself to easy analysis. Yet 80% of enterprise data remains untapped due to its unstructured format. Enterprises did not know how to tap into unstructured data or how to leverage it for opportunity. It was mysterious and out of reach carrying within it transformational insights. As data analytics tools and technologies adapted to using unstructured data, the pros and cons of this type of data emerged.
Pros Of Unstructured Data
In the enterprise, unstructured data has advantages across architecture and business.
Unstructured data does not have a defined purpose which makes it incredibly versatile. It can be used across different formats. While structured data is trapped in Excel spreadsheets of rows and columns, unstructured data can be generated across social media posts, video, audio, and free form text. This makes unstructured data beneficial for generating a greater number of use cases and applications than structured data.
The power of unstructured data in delivering transformational insights is unparalleled. Because an enterprise has more unstructured data than structured data, there is more volume of data to work with. Even though unstructured data is more difficult to analyze, once it is processed, it can give a powerful competitive edge to any business.
Structured data is stored in data lakes which can be costly and time-consuming to access. Conversely, unstructured data is stored in data warehouses which makes it cheap to store and easy to access.
Cons Of Unstructured Data
The new adoption of unstructured data makes it prone to more unknowns and some disadvantages.
Hard To Analyze
Structured data has been used by businesses for years, it has become user-friendly. An average user with data knowledge can access and analyze it. Unstructured data is not that easy to wrangle. It needs trained data scientists and data analysts to take it from raw form and extract value from it.
Data Analytics Tools
For structured data, a user can use Excel to derive insights from it. Unstructured data cannot be managed by traditional business tools. A business looking to derive value from unstructured data needs to invest in the right data analytics tool. All data analytics tools are not created equal. Some tools have Artificial Intelligence (AI) and Natural Language Processing (NLP) technologies that help with data analysis.
Unstructured data comes in many different formats. When analyzing diverse formats across medical records, social media posts, and emails, unstructured data may become challenging to analyze and leverage.
For the enterprise looking to succeed in a competitive market, it needs to harness the chaos of unstructured data into insights. The new adoption of unstructured data comes with advantages and disadvantages for the enterprise. While unstructured data can yield powerful insights, it is harder to analyze than structured data due to a lack of predefined format and a number of different formats. Once an enterprise selects the right data analytics tools to harness unstructured data, it will step into the future of possibilities.