Analyzing unstructured data can be very difficult. Yet unstructured data comprises 80 percent of the data that organizations process on a regular basis.
Structured data provides you with linked, defined and organized data fields that you can easily move and analyze (with the right algorithms). But reviewing unstructured data, which often comes from documents, digital media, and social media sources, doesn't give you that luxury.
So what are the best ways to make unstructured data manageable and get the most out of it?
How to deal with unstructured data.
1. Work with a partner. If you feel overwhelmed by the potential in your unstructured data and don't have the technical knowledge or experience to manage it, your best option may be to work with a partner who specializes in unstructured data. Skilled in cleaning, classifying, or analyzing While not all companies will have the budget necessary to pursue this option, it is certainly the most efficient and convenient. Some specialized tools even allow you to automatically parse, sort, and parse unstructured data, although this is a relatively new area of development.
2. Assess the value of your data and clean up your records. Not all unstructured data is worth analyzing, or even keeping. It costs money to collect and store your data, and it costs even more to clean that data into a format that can be analyzed. If the data comes from a source that will not create much value for your organization, you should consider deleting it.
3. Manually parsing an entire text file of your data is nearly impossible, or at least time-consuming. Instead, it's better to take a random or stratified sample from the collection and use it to create a "dictionary" that you can use to find similar patterns in the rest of the data. There are many ways to approach this, including natural language processing or text analytics, but the end result is the same: create a framework that can be used to organize or identify the rest of your data fields.
4. Clean the entire data set. Your goal should be to take unstructured data and transform it into structured data. Using the framework you created from the random sample, you should be able to write a script that allows you to clean your entire data set. Ideally, you'll be able to categorize and segment this data so you can easily analyze it in the future.
5. Analyze it. Assuming your data is properly organized and easy to digest, you can analyze that data and start making decisions based on the insights gained. Once structured, you can view your data like any other structured data set.
A preference for structured data
While unstructured data can be valuable and practically indispensable in today's data-rich environment, structured data is much easier to analyze. Whenever possible, lean toward sources that allow you to start with a clean, organized record from the beginning. That way, you can skip the structuring process and go straight to analytics.
As big data technology becomes more sophisticated, it will become easier for companies to structure and analyze unstructured data. In the meantime, work with an expert or use your own data structuring algorithms to extract the most value from your unstructured sources.
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