The amount of data generated daily is just mind-boggling. And as much as 90 percent of that data is defined as unstructured data. But what does that mean and what do you need to know about unstructured data? We delve into the details below.
What is Unstructured Data?
Data that is defined as unstructured is growing at 55-65 percent each year.
Unstructured data can’t be easily stored in a traditional column-row database or spreadsheet like a Microsoft Excel table. It’s therefore more difficult to analyse and not easily searchable, which is why it wasn’t useful for organizations until recent years. Today, however, we have unstructured data analytics tools powered by artificial intelligence (AI) that were created specifically to access the insights available from unstructured data.
Examples of Unstructured Data
Think about any kind of data that doesn’t have a recognizable structure and you have identified an example of unstructured data. Here are some of the most common examples of unstructured data:
- Emails: Although emails include date, sender and recipient addresses and subject information, the text in the body of the mail doesn’t follow a format. Some refer to emails as semi-structured data.
- Text files
- Video files
- Audio files
- Webpages and blog posts
- Social media sites
- Call center transcripts/recordings
- Open-ended survey responses
Importance of Unstructured Data
Since the bulk of data generated today is unstructured data, it’s important that organizations find ways to manage and analyze it so that they can act on the data and make important business decisions. This helps organizations prosper in highly competitive environments. If this information is ignored, organizations aren’t using everything that’s available to them to be successful.
Unstructured Data Analytics Tools
While organizations have relied on structured data insights for years, it wasn’t until tools were developed to analyze structured data that the wealth of information unstructured data contains became accessible and usable to businesses in a meaningful way. Artificial intelligence algorithms now help extract meaning automatically from the volumes of unstructured data that is created daily. Businesses use big data tools and software such as Hadoop to process, mine, integrate, store, track, index and report business insights from raw unstructured data. Without these tools, it would be impossible for organizations to efficiently manage unstructured data.
One use case for unstructured data is customer analytics. When companies are able to integrate unstructured data from a variety of sources such as call center transcripts, online reviews of products, chatbot conversations and social media mentions, and use artificial intelligence to spot patterns in the information from these sources, they have the intel available to make swift decisions that can improve customer relationships.
Unstructured data can be a treasure trove of marketing intelligence. With the ability to quickly scan huge datasets and find patterns in customer behavior, decision-makers learn what products or services are most compelling for their target market. This has important applications for product development as well as figuring out what marketing initiatives are most worthwhile.
For organizations that are heavily regulated, compliance issues can be costly in time, money and reputation. With the insight provided by unstructured data when analyzing emails and chatbot conversations, for example, organizations could uncover regulatory issues earlier and before there is a significant negative business impact. This ability is made possible by natural language processing, sentiment analysis, pattern recognition, speech-to-text conversions through machine learning and artificial intelligence algorithms.
To fully realize the potential of unstructured data, organizations need to knock down data silos in favor of a scalable data hub. By having the systems to store, analyze and report data from a variety of sources and share it with decision-makers in a business, organizations can finally uncover the enormous business value of unstructured data.