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How to Analyze and Evaluate Unstructured Data

In an ideal world, all of the data that an organization collects is sorted and stored neatly into boxes, categories, columns, and labels. They are synchronized and easily accessible to all relevant personnel. However, the world is anything but ideal. A considerable percentage of data is usually unstructured, including the information found on web searches, images, social media posts, emails, presentations, and audio and video content. Even data generated internally can be considered unstructured because its intelligence may not fit into the database.

So the question is, how can you make heads or tails out of unstructured data? It’s neither as challenging nor as complicated as it sounds. One way is having a data management platform like the one you will find if you click here. You also need to keep a few things in mind with the analysis and integration of the data with its more structured counterpart. Listed below are some of them.

Determine your goal

Understanding your objective is the first step to analyzing unstructured data. If you don’t know what you’re looking for, then there’s a good chance you won’t find it. After all, not all the information will be helpful or yield the desired outcome. For example, brands and companies that wish to determine sentiment in social media will need to check if the comments or tweets are either positive or negative. If the objective is examining reactions to a product or service, considering specific hashtags or words related to them is a critical focal point because analyzing all information in the social media channel from an arbitrary range of time is inefficient.

Identify the source of the data

Another thing to consider when analyzing data that’s unstructured is the information’s source. Obviously, you must opt for sources that are relevant to the data you’re after — nothing that’s tangentially related to it — including but not necessarily limited to consumer feedback, online reviews, and any other information from the devices. If you don’t, there’s a good chance that the quality of the results may be compromised. For this reason, you must always determine the information’s origin when assessing unstructured data.

Choose a method of analysis

Once the goals and data sources have been determined, you can start deciding how you want to structure your unstructured data and turn it into identifiable information. Specific phrases and words are given bad or good values for the sentiment on social media. The latter may be a +1 while the former a -1, with neutral being 0. The sentiment score is then determined by the sum of the score of the phrases or words. Therefore, the score’s analysis, be it checking whether the majority of posts are positive or negative, is on the numeric structured text summaries instead of the text.

Conclusion

When all’s said and done, the analysis and evaluation of unstructured data are important for any business across all industries. With these tips, you’ll be able to understand the information better, deliver digital transformation, and make much more intelligent business decisions.

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