From marketing to medicine, personalized treatment is taking hold. Customers across all industries expect more these days, and they will go elsewhere if they don’t get what they want. The most advanced organizations are actively addressing this dynamic by blending traditional customer data with big data, then using analytics to fine-tune their products and services. This episode of DM Radio to featured Host Eric Kavanagh interviewing Reltio CMO, Ramon Chen together with David Corrigan of InfoTrellis, and Dan Sholler of Collibra.
One of the opening topics was how machine learning is not just about understanding the defined rules. We noted that for the first time you have the complete picture. Traditional master data management (MDM) systems present an incomplete view by just focusing on master profile data. Transactions, and interactions that are siloed in separate applications do not provide machine learning algorithms with the full context, to derive the necessary insight to make an impact.
Similarly when you run analytics and you generate a BI report from a data warehouse, the resulting actions taken in an operational system ends up being loosely coupled. This again is missing the big picture, companies are unable to close the loop to generate accurate ROI. And machine learning cannot be truly effective without access to continuous new streams of information from new data sources. Details of outcomes are needed to refine suggestions and predictions.