Augmented Analytics solutions enable decision makers and analysts to quickly get to the point of their analysis and automate ‘next-step’ actions using intelligent automation, which is the convergence of Artificial Intelligence (AI), Business Intelligence (BI), Machine Learning (ML) and Robotic Process Automation (RPA) technologies. 

Nearly every organization uses BI tools to develop dashboards that report what happened. Augmented Analytics enables decision makers and analysts to understand why by applying filters to dig deeper, find events meeting certain criteria of interest, and ultimately prescribing actions to take next. Through the integration of powerful BI, AI, ML and RPA technologies, Augmented Analytics takes traditional BI dashboards to the next level, improving the speed and quality of decision making, and even automating the required next steps. It shifts valuable resources from finding the what to learning the why.

Eliminating the hay to pinpoint the needle

Augmented Analytics automatically correlates relevant data to aid rapid discovery, reveal concealed areas requiring deeper analysis, and deliver those insights to decision makers faster than traditional BI. The integrated technologies can pinpoint hidden events or conditions such as fraud, customer churn, health conditions, or component failure. Using machine learning approaches to identify these events allows decision makers to act on them immediately, effectively eliminating discovery efforts to allow more time for addressing the root cause. Additionally, Augmented Analytics’ use of conversational analytics and natural language processing (NLP) make data science more accessible to a wider range of users and decision makers. 

Related Information:

  • Analytic Solutions can turn your agency’s operational data into valuable, actionable insight.
  • RPA can enable the automation of many of your organization’s vast number of manual, rules-based processes. 
  • What is Augmented Intelligence and how can RPA advance DOD IT Modernization. 

Our Capabilities:

  • Machine Learning
  • Robotic Process Automation
  • Business Intelligence
  • Prescriptive Analytics and Modeling
  • Neural Networks
  • Natural Language Processing
  • Data Engineering
  • Data Governance

Impacts:

  • Improves the speed and quality of decision making 
  • Automates required next steps and action items
  • Embeds AI, ML and RPA into BI apps to pinpoint areas of focus
  • Aids rapid discovery and reveals hidden areas requiring deeper analysis
  • Automatically correlates and delivers relevant data
  • Makes data science more accessible to a wider range of users and decision makers
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