AI Pattern, Amalgamation, Data Science, Machine Learning

Unraveling Layers of Unstructured Data

In today’s fast paced business environment often a combination of capabilities is needed to achieve tangible¬† business benefit, to build solutions that gather content from multiple¬† sources, traditional databases all the way to including web and social. With those solutions, you can store, analyze, and report on data by using a combination of analytics and data science capabilities to drive actionable insights and visualization.

Unstructured data over unstructured content usually refers to text, sound, pictures, video. The analysis of unstructured content or unstructured data starts with the notion of cognitive capture with the ability to OCR the content.

Pulling structured data out of the depths of unstructured content allows us to gain access to that content.

Amalgamation takes that derived content and looks it up in systems of record, to match it with a Master Data Management system, to match it with a customer profile, a market segment, a recommendation, a basket analysis, a collaborative filtering.



AI Pattern, Data Science, Machine Learning, Uncategorized

Entity Resolution


Different Entities may be named differently but might actually be the same Entity.


Identities are not unique. How can we tell if they are probably associated  with the same Entity,


Each entity name has a unique identifier.


Market Basket Analysis using association rule learning is a candidate algorithm  for performing account resolution analysis.


 You have probabilistic indication of convergence on entity from possible multiple entities