Unstructured Data Mining: The Tools You Need to Dig the Deep Web

In a world where infinite data is available at our fingertips, it’s imperative that businesses are taking full advantage of all that the informational age has to offer. Do you feel confident that your business is well-informed with regards to what is going on both with your consumer base and within your organization itself?

Many business professionals find themselves overwhelmed by the sheer volume of information available, and don’t know where to begin in making sense of it.

Because of this, we wanted to take the time to help you understand what unstructured data is and how it can be used to bring your organization - or even your industry - to the next level.

What is unstructured data?

Unstructured data makes reference to any information set that either lacks a pre-defined data model or is not compatible with relational tables.

Typically, unstructured data is made up of documents and information that are text-heavy, but could contain data in the form of dates, numbers, and facts.

The end result is an irregular and somewhat ambiguous set of data, making it difficult to analyze, organize, and understand using traditional computer programs.

Why do I want to mine unstructured data?

In 1998, Merrill Lynch stated that an estimated 80% of all potentially usable business data has its origin in unstructured form. Since that time, the amount of unstructured information has grown at a rate of 10-50 times faster than structured data, meaning that an overwhelming majority of business-relevant data must be harvested from its unstructured form.

A combination of innovation, mobile technologies, and an overall decrease in the costs of data storage and transmission has resulted in an increased and immediate need for the unstructured data mining of virtual information.

What kind of virtual information? Social networking conversations, blog posts, web articles, video files, audio clips, VoIP telephony transmissions, and other mediums that fill the deep web.

But what can be achieved through unstructured data mining, exactly? For starters, businesses can expect more accurate and more honest consumer opinions. In the past, customer surveys were the only means by which companies could strive to understand consumer perceptions of their products and services.

Unfortunately, any survey sample population runs the risk of incorrectly representing the whole, and surveys are unable to capture the true customer service experience.

Unstructured data, however, in the form of Facebook status updates, Tweets, blogs, etc. give consumers the opportunity to share their true feelings regarding goods and services in real time. Businesses who are able to harvest these types of unstructured data, therefore, can use it to improve brand perception, boost customer experiences, and meet consumer demands.

Imagine what could happen if a governmental agency could tap into this data. In fact, they do! Healthcare organizations, the intelligence community and even the financial sector are looking to the deep web to track patterns and make valuable educated predictions for human behavior.

Unstructured data mining can also be used internally.By analyzing your sales team’s correspondence with customers, you can get a better idea of why some of your sales employees are more successful or relatable than others.

For example, a company could use unstructured data mining to glean important information that could be valuable in the event of litigation.

How can I start digging?

Although unstructured data is infinite and complex, it is not impossible to work with. In addition to choosing an all-inclusive software that encompasses both structured and unstructured data mining, there are steps that any business can take to simplify the process of working with unstructured data.

Here are two suggestions which will help your organization to get the most out of unstructured data mining, and will assist your data mining software in organizing useful information.

1. Establish smaller representative data sets - Because unstructured data is so vast (and growing every minute), it is important to realize that sorting through all of it is a fruitless effort. It’s wise, therefore, to democratize the results through establishing smaller structured data sets which will help to achieve specific business objectives. These data sets will then allow for a simplified search query. It’s also a smart idea to make use of the benefits of sampling. The majority of analyses can be conducted with a reasonable level of accuracy, a faster turnaround, and lower cost when a randomized sample is used. If analyses performed on smaller data sets yields valuable insights, a business may make the decision to dive deeper into the complete data set.
2. Enforce policies to regularly review and purge data - The more data you’re working with, the more difficult it is to organize and analyze. Because of this, the purging of data is just as important as the acquisition of information. Policies should be created and enforced that require the continuous review and disposal of irrelevant data (within compliance of the law). This will increase the speed and efficiency in which the unstructured data mining process can occur.

Now that you’ve got a better picture of what unstructured data mining is and how it works, how can your organization use it?

Did you know?

IKANOW offers an open analytics platform that helps organizations turn unstructured data into actionable intelligence.

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(Image: “Coal Miner Teach Slone”, n.d. Earl Palmer Appalachian Photograph and Artifact Collection (1880-1889) MS 89-025 Special Collections, Digital Library and Archives, University Libraries, Virginia Polytechnic Institute and State University.)