Unstructured Content and Big Data
For most organization’s unstructured content is abundant and overflowing but not exploited to derive the most value to improve decision-making, drive profitability, and competitive advantages. Big Data deals with structured data, semi-structured (or unstructured) data, and unstructured content. Unfortunately, unstructured content does not fit neatly into database analytics and must be solved with proven technologies that can extract concepts from content and classify to taxonomies to gain business value from content.
Ensuring that the right information is available to end users and decision makers is fundamental to trusting the accuracy of the information. Only when unstructured content is proactively managed can insights be attained to achieve additional business advantages beyond improving search, records management, and data privacy. Organizations can then find the descriptive needles in the haystack to gain competitive advantage and increase business agility. The business imperatives driving this issue:
- Unstructured content is surpassing relational data and must be proactively managed
- Only evaluating structured or semi-structured data does not provide the nuances, sentiment, or knowledge found within unstructured content
- Lack of effective decision making as all the pertinent information can’t be found or extracted
- Ability to respond more quickly to market, competitive, customer perceptions
Concept Searching’s technologies and the Smart Content Framework™ analyze and extract highly correlated concepts from very large document collections. This enables organizations to attain an ecosystem of semantics that delivers understandable results. The valuable insight gained can be used to identify competitive advantages, customer perception, regional trends, and, perhaps more importantly, identify internal knowledge capital that exists but is rarely used because it cannot be found.
For more information about this topic, please read our ‘ Big Data Solution Overview‘.