Unstructured data 101:
Due to the breadth of unstructured data solutions, whether text or search based, organizations are hard pressed to identify which solutions can offer them the right functionality to help them address their business information pains. However, with a general understanding of the options available, organizations can develop solutions tied to ROI and can increase their strategic initiatives within the organization.
The first several parts of this series discussed unstructured data, text mining, how they are used within the organization, and the business and technological factors management should consider when looking to implement an unstructured data solution. The next step for organizations is to identify what options are available and how these options best meet business requirements.
Three options for organizations
Unstructured data use within business intelligence applications will continue to expand until it becomes a regular feature within BI. Although this seems to be one of the key discussions within the business intelligence world, the use of unstructured data is actually broader. Aside from BI search, BI solutions can now leverage existing text mining or text analytics features or embed best of breed solution functionality into their front end data visualization tools. The questions organizations should be asking are: Which solution will best meet the needs of the organization? What issue is the organization trying to address? And what currently exists (i.e. technical architecture, scorecards, etc.)? An organization with a strong BI infrastructure might want end users to have more access to the right information, or may want to broaden access of published reports to the entire organization. Another organization may seek to develop predictors for customer behavior. Once management has identified the driving factors behind the initiative they can begin building a solution that includes one of the options identified.
The following three areas provide a general breakdown of the types of solutions businesses should consider as well as general benefits and challenges associated with these options. Although in-depth technical challenges will not be discussed, the items listed will give organizations a general overview to identify what key issues they should explore further when considering these solutions. Additionally, the use of unstructured data within BI based analytics, although available, is quite young in its phase of adoption. This means that organizations can explore these options but the diversity of use within BI provides a limited amount of benchmarking opportunities for organizations that wish to reference current uses.
BI search tools allow organizations to embed search into their current BI applications. In many cases, BI is relegated to super users, with in-depth knowledge of where key information resides left in the hands of IT professionals. The problem with this approach is that the wealth of information that could be given to decision makers throughout the organization very rarely finds its way beyond the defined end user community. With BI search, Google type searches allow end users to access the information they are looking for in a way that matches their comfort and ease of use due to familiarity, based on the way they currently use the Internet.
Currently, many BI vendors have embedded search within their applications by partnering with search vendors such as FAST or Google. This offers organizations an easy way to use search within current business intelligence or performance management applications. However, search has been a key component to other solutions, such as enterprise content management for many years. If organizations want to bridge the gap between BI and other solutions, an expansion of current systems to include BI or BPM based information might be a better approach to enable end users access to a wider range of data that may not be accessible otherwise.