Text analytics takes data mining to the next level, analyzing unstructured data to help firms refine their customer view. Techniques such as text analytics and identity resolution software can help firms to maintain financial compliance, understand customer sentiment and carry out big data analysis. This growing market is driven by the expansion of digital information and the need to process and analyze it.
Analyzing unstructured data
Application, Development and Delivery professionals like solution architects, software and systems engineers, project managers and tech-leads can all use text and entity analytics to improve and expand their organizations capabilities. In areas such as financial compliance, social media monitoring and big data analysis, text analytics can provide useful insights.
The expansion of the digital world has created vast bodies of unstructured data and unstructured text. On Facebook alone, there are 1.97 billion users worldwide generating online content every month. The total amount of digital information is expected to reach 40 ZB by 2020 according the International Data Corporation (IDC). In fact, about 1.7 MB of new information is added every second for per person. Yet only about 1% of this data is analyzed.
Data mining techniques
Data mining techniques like text analytics, entity extraction, sentiment analysis and identity resolution software can use this information to produce instant results. These have a wide range of applications. They can help firms to complete their customer view and to understand customer sentiments about their business, products and services. Banks and financial institutions can use these for compliance screening customers and employees.
There are several techniques for analyzing vast collections of unstructured content, each with several applications. These analyze a variety of digital sources for information that can be used for better decision making.
- Text analytics produces data that can be used to measure customer opinion expressed in product reviews and feedback.
- Entity extraction analyzes unstructured text to identify entities like people, dates, places, events and companies.
- Sentiment Analysis produces analysis of positive or negative attitudes to events or products.
- Identity resolution software can help match identities to identify individuals and entities.
With so many applications, the text mining software market is set to grow. Its current value is estimated to be $3 billion and it is projected to double to around $6 billion by 2020. Techniques such as text analytics and identity resolution software can provide accurate insights for businesses into compliance, customer sentiment and threat detection.
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