Data Enrichment collects, organizes, normalizes structured and unstructured data and delivers high quality data in the form that can provide information that could help in competition analysis, competitive cross-reference analysis, up selling, accessories and many others.
Embedded Analytics integrates analytic content and capabilities within applications, such as business process applications (e.g. CRM, ERP, EHR/EMR) or portals (e.g. intranets or extranets) and also IoT and machine learning data and presents it combined with data from of all enterprise applications.
Real-time Analytics displays active viewers of a page and create a sense of urgency for users looking at an item with finite inventory by displaying most popular content such as top-10 active pages with a real-time dash-boarding and heat-map reports.
Decriptive, Predictive and Prescriptive Analytics summarizes what happened in descriptive analytics using sentiment or other social network data. Then it takes different data streams and applies statistical, modelling, mining and machine learning algorithms to allow predictions into future. Finally, it uses the predictive analytics to suggest a possible action or consequence and helps application of it through use of intervention of a collaborating decision maker using actionable and feedback techniques.
Multiple combined data presentations helps combine data from multiple data sources and tell data stories in a format that makes data easily accessible using visualizations.