BIG DATA AND AUGMENTED ANALYTICS
Augmented analytics is an approach to data analytics that employs the use of machine learning and natural language processing to automate analysis processes normally done by a specialist or data scientist. Diwo uses augmented analytics to parse through big data and deliver valuable, actionable insights that are easily understood and trusted by the user.
Big data + augmented analytics = timely, actionable insight
Big data by itself is pointless, unless it is analyzed and delivered to a decision-maker with business context. Diwo’s Decision Intelligence solution breaks through the noise and gets you past the “last mile of analytics” to deliver contextual insights that lead to effective decisions.
The complexity and volume of data every business accumulated is a common challenge for those who need to make decision. Big data + augmented analytics help decision-makers get the right insights at the right time in order to make effective decisions.
How are big data and augmented analytics being used in organizations today?
For large enterprises looking to reduce the analytic load of their teams, to surfacing risk and opportunities immediately or for software developers adding capability and value beyond traditional reporting, use cases for augmented analytics are broad. This is particularly true for industries where the data and the variables being analyzed are complex enough or too vast in volume for their users to be able to comprehensively and reliably perform analysis with their current manual approach.
Diwo closes the decision gap to help you achieve immediate and measurable business value through real-time, contextual recommendations.
Diwo transforms big data into actions that drive big revenue and big results
Ultimately, the most successful organizations in the digital age will be those that are able to gain the clearest insights from all of their big data. Diwo facilitates that by prioritizing context over data and decisions over dashboards.