Open Internet by MindsNet

Design Big Data Analytics That Automatically Discover Unknown Patterns and Insights

Current big data analytics require humans to specify what patterns or insights to look for, yet creating analytics that can automatically discover completely unknown patterns and generate novel insights remains largely theoretical. Most analytics approaches can only find patterns that humans design them to find, missing unexpected discoveries. The challenge requires developing big data analytics that can explore data autonomously to find patterns humans haven't thought to look for, generate novel hypotheses and insights without human guidance, and discover valuable patterns that aren't obvious or expected. Major obstacles include defining what constitutes interesting or valuable patterns without human input, ensuring automated discovery doesn't generate false patterns or meaningless correlations, validating discovered patterns for significance and actionability, and presenting discoveries in ways humans can understand and act upon. Without autonomous pattern discovery, big data will continue being limited by human imagination and preconceptions about what patterns exist. Success would enable big data systems that act as autonomous researchers, discovering insights and opportunities that humans would never think to investigate.

Computing & Technology, Information Technology, Big Data