5 Myths About Unstructured Data
Unstructured Data Analytics, or UDA, is one of the newest and hottest subfields of Big Data today, naturally comes with its share of misconceptions that either cause businesses to be too hesitant buying into the technology, or cause businesses to misinterpret what UDA can do for them and therefore cause them to fail to utilize it efficiently. UDA analyzes data with no clear structure or organization (such as a string of text or numbers) so let’s clear up exactly what it is and how it works. Here are some common myths about UDA and some clarification about its potential uses and benefits:
Myth 1. Unstructured Data is only textual data
Merrill Lynch estimates that over 80 percent of data found today is unstructured, but not all of that data is text. Unstructured data encompasses formats like IMS, chat, and customer reviews, but also includes photographs, videos, scientific measurements (such as seismographs), and even ordinary communication techniques such as facial expressions, body language, and tone of voice. It turns out, almost all forms of communication in the world have the potential to be transformed into data — and almost all of that data would be deemed unstructured. This is the future of data analytics, making sense of not just words, but everything that comes with them.
Myth 2. Unstructured Data Analytics is not helpful to companies without Chat or Customer Review Data
Many companies don’t rely on customer reviews or chats to understand what their clients are thinking. They may lack the service, may not have enough content to analyze, or simply aren’t in that field of business. However, any enterprise that communicates in any way stands to benefit from Unstructured Data Analytics. UDA on company emails can serve to figure out what employees need. UDA on their own website can serve to address the company image and presence. Sometimes, the most important part of repairing company-client relations is to start inside the company itself.
Myth 3. Unstructured Data Analytics only means Sentiment Analysis
A common misconception is that UDA is confined to Sentiment Analysis, or the measurement of how people feel (positively or negatively) about something. In reality, Sentiment Analysis is merely a feature of advanced UDA platforms and works with many other features to construct the big picture of the data. Other features of UDA include syntactical analysis (which uses the syntax of sentences to determine the importance of the words within), topic categorization (which arranges data into categories based on theme), and geospatial organization (which uses geography and setting to aid in the interpretation of the data).
Myth 4. Taxonomies are enough to conduct Unstructured Data Analytics
A taxonomy, or data classification center, manages the organization of much of today’s Unstructured Data into serviceable categories. What businesses should understand now, however, is that today’s technology has moved much farther than anything a simple taxonomy can offer anymore. Taxonomies can sort data into specific categories like “long” or “short”, “from Virginia” or “from last year”, but it can’t go into the actual data and pull out its meaning like contemporary UDA initiatives can. It’s the equivalent of putting different types of candy into boxes without ever tasting them.
Myth 5. Unstructured Data Analytics can’t do much more than human intuition.
Some within the business realm make the case that the humans can tap the feel and meaning of datasets better than any machine can. No machine can ever interpret the data completely, error-free because the translation of data-driven insight into action is a business decision, not a technological algorithm. However, a decision-maker needs to make sure they have the full picture of the data before going after any major, business-defining choices. UDA organizes, analyzes, and visualizes data so you can have a much faster path from data to revenue.