With more and more emphasis on the use of cognitive computing, it is but natural that its impact will be felt on today’s data analytics landscape.
For the longest time, Enterprises chose to mostly ignore unstructured data since the tools and skills required to derive meaning from it were not sophisticated nor flexible enough. No longer so.
Today, among the solutions offered for the analysis of unstructured data are Machine-Learning and Artificial Intelligence (AI).
AI is beginning to play a role in the discovery of patterns in unstructured data. One of its branches, Natural Language Processing (NLP), now allows a computer to understand the language of humans, thus making sense of customer conversations, and categorizing them. Which means, the use of NLP in online social conversations can help recognize a sentiment on a particular subject, probably in real time, thus giving the brand an opportunity to change course on a product, midway through its marketing campaign.
Some studies show that unstructured data weighs in at as much as 80% of the total data available today. It is to be found in social media networks, news, chat services, messaging services, niche magazines, government reports, white papers, to name a few sources. Online conversation between two or a set of people, too, is also defined as unstructured data.
So what information does unstructured data contain? It has pointers to customer requirements, feedback, emotional behavior, emerging sectorial trends, and a host of distinct information, all of which can prove to be of vital importance in executing business decisions.
Cognitive Computing Solutions
The expertise to convert these conversations or feedback from consumers, largely in real time, into near-accurate actionable intelligence to be used for business means has only become available of late.
This includes the techniques offered by cognitive computing technologies. As we had mentioned in an earlier post, cognitive computing is exhibiting all the signs of changing the way the world does business. It can be dubbed the “mother of all computing” (so far) – a superset of analytics, AI, Business Intelligence (BI) and machine learning. A simplistic explanation would be – it’s a computer trying to make a copycat version of the human mind.
Such is the rapidity of progress being made in the interpretation of unstructured data that the modern-day tools even allow employees with statistical skills but no formal knowledge of data analytics to look for answers to business questions, without the need of the IT personnel.
To start off, pattern discovery is the core of cognitive computing’s ability to make sense of unstructured data. Machine learning algorithms, they say, can establish precedents from current attributes and use of data to determine future ones.
Cognitive computing technologies including flexible machine learning algorithms can cleanse the data, add “structure” to such unstructured data, decide their integration, and determine the future course of business actions. All of which also makes an organization more agile.
Thus, if your company is one of those that has been ignoring unstructured data so far, it can no longer afford to do so. Going forward, firms that will continue to rely only on structured data will miss deriving benefits hidden in unstructured data. In today’s world of intense competition, it could prove to be a costly mistake.