Knowledge Graph Benefit Case
Learn how to leverage the power of knowledge graphs for improved decision-making and customer service. This course is ideal for business analysts, architects, management consultants, MBA students, analytics students, and data scientists. Gain insights into the benefits and complexities of knowledge graph solutions and develop a strategic approach to graph analytics. Start your journey towards real-time decision-making today.
What you’ll learn
- Describe what is Knowledge Graph
- Articulate knowledge graph use cases
- Articulate benefit case for knowledge graph use cases
- Define relative complexity of knowledge graph solution
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 and
Finally, You will learn how to strategize a Graph analytics experience
Who this course is for:
- Business Analysts
- Architects
- Management Consultants
- MBA Students
- Analytics Students
- Data Scientists
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