Unstructured Data Matters

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According to an article written in Forbes, over 80% of business-relevant information exists in an unstructured format, primarily text, and it is growing at exponential rate. Most companies have yet to derive meaningful insight from these data sets. These astonishing facts underscore two indisputable truths. First, unstructured data should matter to enterprises. Second, exploiting unstructured sources with text analytics platforms, should be an essential component of any comprehensive business-intelligence program.

It’s clear businesses have reached consensus that unstructured data analysis is positioned to create new competitive advantages. There’s no doubt that the application of analytical tools, in the context of unstructured data analytics, will lead to profound “mutations” of existing methods and lead to development of new analytical approaches. Analysis of unstructured data will strongly affect the accuracy of decisions and as well as significantly accelerate decision-making.

While there’s plenty of chatter about analyzing unstructured data, there’s little consensus on how to harness it to improve business practices. Companies are still overwhelmed by the sheer volume and exponential growth. Much of this data, and the insight that it contains, remains untapped.

 
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Commit to Analyzing it?!

Taken as a whole the task of tackling unstructured data can be daunting, but like preparing to run a big race, you can develop a plan to reach your desired objective. While approaches will vary, the fundamental necessity in achieving success will greatly hinge on your understanding the challenge and your commitment level to getting it done.

The same holds true with unstructured data analysis. Most business leaders will outwardly acknowledge the importance of leveraging insights from unstructured data but in their mind, doubts might linger.

“What exactly is unstructured data?”

“Is there any real value in analyzing it for my company?”

“Do I have the resources (time, money and expertise) to do this?”

“How do I even start this initiative?”

These doubts lead to poorly defined project goals and often hobble any attempt at meaningful analysis. To avoid this pitfall, it’s important to remember some basics:

#1 — Your company has a lot of unstructured textual data at its disposal

Textual data is being created everywhere. It can be found inside your company walls in forms such as — email, chat, surveys that you collect, comments to your website, comments from your CRM system, or text fields from any proprietary applications that you use. It can also be found outside your walls in forms such as — social media, forums that you monitor, comments from news articles that mention topics of interest to you. The point is, there’s a lot of textual data out there that can provide meaningful insight into your business.

#2 — There’s value within these data sets

How can you know what a book is about if you only read 20% of it? Sounds preposterous, but that’s exactly what’s happening in the corporate world today. Companies are spending billions of dollars analyzing structured data, while leaving unstructured data untouched. There’s a treasure trove of useful information in unstructured data and in future blog posts we will highlight specific use cases of how analyzing it has led to insights that bettered business practices at a diverse set of leading companies.

#3 –Analyzing unstructured data doesn’t require a team of rocket scientists

You don’t need to spend millions to analyze unstructured data. Analyzing data does not require a highly technical army of mathematicians, data scientists and IT folks on staff. True analysis occurs at the end user level with the brand manager in charge of a particular product segment, the marketer tasked with optimizing a campaign, or the executive looking to anticipate the wants and needs of a customer base. The end user has the ability, authority, and motivation to improve business practices. Technologies exist today to empower end users to make data driven decisions without having to rely on a huge support staff to provide them with analytics.

#4 — Don’t expect to press a magic button to lead you to insight

Proper analysis requires a combination of machine computation and human interpretation. The machine does the number crunching while end users apply their business acumen to determine best courses of action given the fact set. Do not expect to press a magic button to lead you to insight. An end user must determine which datasets are valuable, how they should be mined, and how their teachings can be applied to better your business. A company’s job is to empower end users to have as much relevant data as possible to make the best decision possible.

There is a great potential for game changing discoveries from analyzing unstructured data. The ability to mine insights has never been easier! Stratifyd works closely with a wide range of businesses to unify their structured and unstructured data, providing them insight in minutes, not months.

 
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