The data discovery process aids in revealing insights that have been dormant inside a company by creating value out of unstructured data and making it convenient for business users to use when applicable.  

Enterprises should note that any content that is challenging to find can cause users to lose trust in the content’s relevance and functionality, negating the content’s goal in the first place. As a result, this makes data discovery a high-stakes activity that needs to prioritize making content easily accessible to its consumers at all times. This can contribute to the development of actionable intelligence or information that can be used to support decision-making. 

There are three aspects to consider when managing data discovery. First, enterprises should have an internal approach to provide their unique domain knowledge to customers, partners, and/or consumers so these stakeholders can leverage information toward their end goal. Overall, this helps bolster a competitive edge. Next, paying close attention to audience engagement is what keeps customers repeatedly wanting to use a company’s content over and over again. Audiences need access to accurate information they need as readily as possible. Finally, easily and efficiently accessing information is a key to differentiating in a digital environment. No matter how big or small an organization is, providing immediate and seamless access to its domain-specific information can create a competitive advantage. 

Obstacles within data discovery happen when enterprises struggle to drive insights due to the absence of data structure. Content must be divided into distinct categories in a logical, organized matter, or it will become burdensome to navigate through discovery or other search methods.

Furthermore, data that has yet to be normalized or standardized and documents that originate from different sources and in several languages add to the difficulty of finding specific content when needed. Content isolated between individual data sources and dispersed across an enterprise can negatively affect an enterprise-wide strategy. This can also result in inefficient information access, causing data discovery procedures to fail and produce erroneous results that do not satisfy the demands or preferences of organizations.  

Now that we have seen how data discovery can harness unstructured data to generate actionable intelligence that can help businesses make better decisions and act on them faster, the next step is using taxonomies to resolve these data discovery challenges.  Read On: