Forget about AI and ML
Until You’ve Ensured Proper Analytic Management and Governance
AI and machine learning models are comprised of data, derived attributes and other simple analytics. Yet more than half of enterprises state their analytics yield inconsistent results 40% of the time – making it hard to leverage AI and ML without more time and effort.
This is driven by most companies taking a Data Tools Mindset – providing trusted access to data and self service capabilities. To achieve true AI and ML, enterprises need to leverage an Analytic Outcomes Mindset – focusing on outcomes and answers—managing and governing them as assets.
To help you better understand what it takes cross the chasm from a Data Tools Mindset to an Analytics Outcomes Mindset, we teamed up with WBR to take a closer look at where companies are at in their analytic maturity and what obstacles they face.