Description
In the past, Organizations relied heavily on process reviews and sample reviews to drive their conclusion. Today, nearly 85% of the data they review is unstructured. Traditional IT function automates 15% but leaves the 85% to an army of humans. Digitization is seeking decision-making in real-time. Regulators are seeking review of 100% transactions. Samples are no longer sufficient Outsourcing is involving external organizations to decision-making. Policies and procedures must be digitized. Customer engagements are aggressively looking for fast turn-around on quality decision making utilizing all available structured and non-structured data. They want support for proactive online decisions to improve customer service.. The concept of using Graph databases to map relationships digitally started seeing popular usage in business around 2015. With increased compute power, in-memory computing, multi-processing and agreed-upon standards moved the concept from academics to real-world uses in business and enterprise computing. After completing this course, youu will be able to * Describe what is Knowledge Graph* Understand and articulate the use case for knowledge graph solution* Define benefit case of knowledge graph solution* Define relative complexity and benefits of knowledge graph solution andFinally, You will learn how to strategize a Graph analytics experience
