The data that’s generated every day is astounding, and ninety percent of it is unstructured. But what exactly does it mean, and why is it important? As its name suggests, unstructured data refers to datasets that don’t fit or aren’t stored within structured databases. Because of this, they’re generally harder to search for and analyze, which is the reason why they’ve only become useful for brands and companies in recent years, thanks to AI-powered analytics tools like those found at dataloop.ai. These have been created to store, sort, and access insights that otherwise would have been inaccessible.
Unstructured data examples
Any data that lacks recognizable structures is defined to be unstructured. Some examples of this are the following:
- Web pages
Since a considerable portion of data being produced these days are unstructured, organizations must be able to find ways of analyzing and managing it, so they’re able to act accordingly on the information to make the right decisions and prosper, especially in competitive environments. If the information remains ignored, businesses won’t maximize what’s available and might miss out on opportunities to thrive and flourish.
While most organizations have depended on the structured data they’ve collected for many years, it’s only in the past few years that the tools have been developed to analyze and assess the information contained within the unstructured data and use it to help their businesses grow. Algorithms powered by artificial intelligence are now able to extract meaning from the volumes of all the unstructured data created daily. This leads to companies mining, integrating, storing, tracking, indexing, and reporting insights from the data.
One example is consumer analytics. Whenever companies and brands can incorporate unstructured data from various sources like online reviews, chatbot conversations, mentions in social media, and the use of AI in spotting patterns, they gain intel that enables them to make quick decisions to improve their relationships with their customers. As a result, they can maintain their engagement and attract more prospects into the fold, allowing their business to generate more revenue in the long term instead of only profiting in the short time. However, this isn’t all that the utilization of analytics tools is good for — it can also aid organizations with regard to compliance.
For heavily regulated organizations, compliance concerns can be potentially costly when it comes to reputation, money, and time. However, with all the insight coming from unstructured data, businesses can uncover issues much earlier to avoid or minimize any negative impact on the company. This is primarily made possible through sentiment analysis, language processing, pattern recognition, artificial intelligence, and speech-to-text conversions via machine learning.
No one can deny the importance of unstructured data. To realize its potential fully, organizations must knock data silos down for more scalable data hubs. With the right systems in place to store, report, and analyze information from various sources, a business can uncover a considerable amount of value out of this type of data.