New forms of business intelligence incorporate both structured and unstructured data into your analysis. Where does this apply today? Customer service, intelligence analysis in government, fraud analysis in financial services, healthcare, consumer packaged goods, retail and other markets can benefit from this approach. The open web provides organizations with limitless data containing valuable information on sentiment, people, events, employers, relationships and more. The ability to extract meaning from unstructured sources combined with structured data yields new insights that can be used to improve decisions.
Let's take a look at healthcare, for example.
In an article by Dennis Amorosano entitled "Unstructured data a common hurdle to achieving guidelines", Mr. Amorosano writes "... of the 1.2 billion clinical documents produced in the United States each year, approximately 60 percent contain valuable information trapped in unstructured documents that are unavailable for clinical use, quality measurement and data mining. These paper documents have until now been the natural byproduct of most hospital workflows, as healthcare is one of the most document-intensive industries."
Forbes published an article last year entitled "The Next Revolution in Healthcare" (http://www.forbes.com/sites/singularity/2012/10/01/the-next-revolution-in-healthcare/) in which the author points out that the best healthcare institutions in the world still rely heavily on calculating risk to patients using clinical data. At the same time "the real tragedy is that the information needed to properly assess the patient’s risk and determine treatment is available in the clinician’s notes, but without the proper tools the knowledge remains unavailable and hence, unused."
The good news is that new analytic solutions are available that leverage both forms of data. BI connectivity brings the power of familiar Business tools to your applications that include unstructured data. Some of the benefits to this approach include:
- Combining BI and NoSQL provides capabilities not available using relational stores and EDWs - real-time analysis and extended query features.
- BI tools layer on top of NoSQL databases that use sophisticated security models to protect sensitive data. Users see only the information for which they have permissions.
- Analysts can learn faster using data discovery tools that allow for rapid investigation of both unstructured and structured data within the same application. A more complete view of your analysis offers tremendous advantages in patient diagnosis, claims analysis and personalized care.
To learn more about how analytics technology is working with Enterprise NoSQL Databases ideally suited to ingest, store, search and analyze all types of data, you can visit this page: