Visual and Geospatial Analytics in the Energy Sector

The energy industry challenge is to reduce the time needed to collect data and report out. Digital enablement allows more time for data interrogation and transformational teamwork. Data is available through externally hosted cloud connections and on-premises databases. Machine learning blends data sources into curated, analytics-ready tables. These are easy to find via a self-service business directory using data virtualization. Agile development of organically grown user interfaces are being driven by customer need and high user satisfaction. Highly customizable visualizations, geospatial analytics, and mods allow users to trigger Python scripts. Human-guided augmented intelligence has led to actionable insights – performance, forecasting, company competitor activity, and price discounts.