IBM Watson enables your business to get started with text-analytics
By Angel Montesdeoca | 3 minute read | December 19, 2019
What are text analytics?
Text analytics can help organizations discover patterns in large unstructured data sets. Unstructured data, such as videos, photos and audio accounts for at least 80% of your company’s data, a true “blind spot” for most businesses. Add to this the fact that every second companies around the world add data to the pile exponentially; every second 2.5 billion emails are sent; Facebook alone generates more than 22 trillion messages.
Such widespread growth creates an opportunity for your enterprise to make use of this data and create smart, optimized experiences. Text analytics, powered by natural language processing (NLP), provide your employees with the tools they need to pull rich insights from their massive trove of data. Also referred to as data mining, or content mining, text analytics enable businesses to discover patterns in large unstructured data sets that translate into improved business decisions and smarter experiences.
On December 4, IBM announced that Content Mining is officially available as a text-analytics and data-mining capability in Watson Discovery for Cloud Pak for Data.? This text-analytics feature was announced alongside other new NLP features, including enhancements to Smart Document Understanding, and the addition of Content Intelligence.
How is Watson Discovery leveraging text analytics?
It is difficult to find insights when the user lacks an understanding of what they are seeking. Unlike traditional enterprise search, where users know exactly what type of answer they are looking for, Content Mining focuses on proactively finding hidden insights and helps users quickly surface information using a guided navigation experience.
In real-time, Content Mining allows you to search across documents and explore text analytics results, relationships, anomalies, and how different elements of your content change over time. For example, car manufacturers can monitor trends within customer reviews on items such as brake systems of a specific car model. Watson Discovery understands the feedback, and connects it to a specific time and event – such as a big snowfall in February.
Honda is one of the world’s most innovative companies and its engineers constantly strive to design and build the smartest, most technologically advanced products on the market. To this end, it invests billions of dollars per year in its research and development organization, Honda R&D. The R&D team, located in Honda’s test-facilities, realized that vehicle diagnostics and telematics, smartphones, biometric sensors and large bodies of unstructured text such as customer surveys are new sources of big data. These sources hold great value potential, but their engineering team did not know how to unlock the insights hidden within these huge data-sets. Today,? Honda’s engineers can see beyond their test-facilities, and use IBM Watson Discovery’s text-analytics capability, Content Mining, to gain a better understanding of how cars and drivers behave in the real world. They are able to pull insights for quality assurance purposes, which include assistance in diagnosing and repairing vehicles and detecting vehicle defects.
Content Mining also plays a key role in the digital transformation of Korean Air. Korean Air has years worth of historical maintenance records for the hundreds of aircraft in its fleet. But until recently, this vast amount of critical data was virtually unsearchable. That meant that maintenance technicians had to diagnose and fix issues without being able to tap into or interpret implications from valuable past learnings and courses of action. Using Content Mining, Watson Discovery delivered actionable insights on the root causes and solutions of issues, which enabled Korean Air to shorten its maintenance defect history analysis lead times by 90%. The maintenance employee can now see patterns of defect and failure on equipment to make preventive maintenance allowing them to spend more time getting people places on time—and working to keep their 25 million passengers happy.