Business Rules for Automating Business Policy

AAAI Conferences

Rockville, MD 20850 Colleen McClintock Infinite Intelligence, Inc. 1155 Connecticut Avenue, #500 Washington 20036 Jacqueline Sobieski Fannie Mae 3900 Wisconsin Avenue Washington 20016 Abstract Business policy can be defined as the guidelines and procedures by which an organization conducts its business. Organizations depend on their information systems to implement their business policy. It is important that any implementation of business policy allows faster application development and better quality management and also provides a balance between flexibility and centralized control. This paper views business rules as atomic units of business policy that can be used to define or constrain different aspects of the business. It then argues that business rules provide an excellent representation for business policy. KARMA was developed and deployed at Fannie Mae. 1 Introduction Business policy can be defined as the guidelines and procedures by which an organization conducts its business. Business policy is often documented in manuals and business guidelines and is reflected in an organization's information systems. Organizations depend on their information systems to implement this policy.


Tips for Data Scientists @CloudExpo #BigData #IoT #ML #AI #DataScience

#artificialintelligence

I spend a lot of time helping organizations to "think like a data scientist." My book "Big Data MBA: Driving Business Strategies with Data Science" has several chapters devoted to helping business leaders to embrace the power of data scientist thinking. My Big Data MBA class at the University of San Francisco School of Management focuses on teaching tomorrow's business executives the power of analytics and data science to optimize key business processes, uncover new monetization opportunities and create a more compelling, engaging customer and channel engagement. However in working with our data science teams, I have come to realize that we also need to address the other side of the data science equation; that we need to teach the data scientists in order for them to think like business executives. If the data science team cannot present the analytic results in a way that is relevant and meaningful to the business (so that it is clear what actions the business leaders need to take), then why bother.


Business Analytics and Intelligence Compared

@machinelearnbot

Business analytics and business intelligence are two different notions, but only few people understand the difference. Interestingly, even people who have worked in the business industry struggle with this particular topic or have various different answers when someone asks the question'What is the difference between business analytics and business intelligence?' Some people define business analytics as an umbrella term and place intelligence as one of its parts, together with data warehousing, enterprise performance management, risk, compliance and analytic applications. Meanwhile, others use the term business analytics as a level of domain knowledge related to predictive or statistical analytics. Business intelligence can be defined as the necessity to get the most out of a particular information.


Business Analytics and Intelligence Compared

@machinelearnbot

Business analytics and business intelligence are two different notions, but only few people understand the difference. Interestingly, even people who have worked in the business industry struggle with this particular topic or have various different answers when someone asks the question'What is the difference between business analytics and business intelligence?'


Tips for Data Scientists @CloudExpo #BigData #IoT #ML #AI #DataScience

#artificialintelligence

I spend a lot of time helping organizations to "think like a data scientist." My book "Big Data MBA: Driving Business Strategies with Data Science" has several chapters devoted to helping business leaders to embrace the power of data scientist thinking. My Big Data MBA class at the University of San Francisco School of Management focuses on teaching tomorrow's business executives the power of analytics and data science to optimize key business processes, uncover new monetization opportunities and create a more compelling, engaging customer and channel engagement. However in working with our data science teams, I have come to realize that we also need to address the other side of the data science equation; that we need to teach the data scientists in order for them to think like business executives. If the data science team cannot present the analytic results in a way that is relevant and meaningful to the business (so that it is clear what actions the business leaders need to take), then why bother.