Culling complex data for new insights from unstructured data analytics
In recent years, unstructured data analytics has soared in popularity due to the increasing availability of complex data sources, such as web logs, multimedia content and social media data. In raw format, semi-structured data sources often output in JSON or XML format, while unstructured data has its own internal structure, but doesn’t conform neatly in a database. In both cases, semi-structured and unstructured data sources are challenging for nontechnical business users and data analysts to unbox, understand, and prepare for analytic use, which is the fundamental challenge of unstructured data analytics. How can these non-technical users truly undergo unstructured data analytics without dependence?