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What Is Unstructured Data Used For?

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You may not have heard of it, but data is a big deal. And there is a challenge with all this new information coming at us daily. More than 90% of it is unstructured. But what does that mean and why should you care about this?

With the recent flood of unstructured data, it has become easier than ever for businesses to make use of this new source. The goal of analyzing all types or formats is to discover actionable value.

What Is Unstructured Data?

Unstructured data are data contents that cannot be neatly fitted into a spreadsheet or accessed as easily as a database. It is difficult to store and manage, but creative minds have been finding new ways all the time.

The challenge with unstructured data is that it is not easily stored in a traditional column-row database or spreadsheet like Microsoft Excel. It can be difficult both to analyze and to search, which has made this type of information less useful for organizations. Less useful until recently now that we have tools powered by Artificial Intelligence (AI). These new AI programs were specifically created to access insights from these types of unstructured data sets.

Unstructured Data Importance

As more and more data gets generated, it is important that organizations find ways to manage this information so they can act on the insights. This helps businesses prosper in competitive environments where having Big Data access always translates into success for an organization no matter what their industry might be.

Since most unstructured data contents do not follow any grid-like pattern whatsoever, it takes some serious digging through databases or spending hours wading through countless pages online. Such efforts are needed if you

want something meaningful enough to report back with good results. Thankfully, Machine Learning (ML) has come alongside human intelligence.

Unstructured Data Examples

Unstructured data is any kind of information that does not fit into a spreadsheet or database structure. The most common examples are email or document texts, social media posts, or chat messages. These all lack grid order and can be difficult to analyze because there is not always an obvious way you would categorize them.

Here are some common types of unstructured data:

· Text files

· Photos

· Video files

· Audio files

· Web pages and blog posts

· Social media sites

· Presentations

· Call center transcripts

· Open-ended survey responses

Conclusion

For data-driven organizations, data is the lifeblood of any company and knowing what information to collect can be difficult. Business Intelligence (BI) and analytics tools such as Natural Language Processing (NLP) are being developed that have been specifically created with this goal in mind –analyzing all types or formats so you can discover actionable insights on demand.

The Content Analytics Platform (CAP), developed by Scion Analytics, can help with data discovery. The CAP can quickly analyze any textual data, in any format, and turn it into structured data that is discoverable for value.

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