Customer Success Services
Use a combination of physical principles, empirical knowledge, and data science to build a solution to uncover key patterns within your data—driving significant business valueDownload brochure
Increased throughput and improved quality through data-driven root cause analysis
Solutions to predict failures and find corrective measures by understanding data patterns
Improve operations through transforming empirical knowledge into algorithms
(2 Days – 1 Week) This is a workout to help prioritize KPIs through forming a prioritized outcome map, identification of data sources, assessment of data availability, development of data dictionary, and proposal of next steps on an analytics roadmap.
(1 Week – 4 Weeks) Conduct data profiling through reviewing up to 10 data sources to assess data quality and perform preliminary tests for causality. Through RCA and understanding the interactions among variables, we will identify any quick wins.
(12 Weeks) The Data Science Accelerator supports a holistic approach to collaboration on a MVP using agile data science methodologies. We construct and implement preliminary analytic models with clickable prototypes for solution showcase.
(2 Days) Educate your teams on the basics of data science by showcasing success stories. Participants will understand how to identify use cases and prioritize them based on outcomes. This includes developing an analytic roadmap.