Mike Gualtieri: How to Make AI Happen Without Getting Fired

Mike Gualtieri from Forrester Research offers 8 tips on how to make AI happen without getting fired. These tips are based on his discussions with enterprise data scientists and enterprise leaders who embarked on machine learning and AI projects in their organizations. When determining and executing an AI Strategy at your company, the following eight observations, tips and advice may be very useful before getting started. Link Continue reading

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Decision Management: What It Is and Why You Need It

GartnerDMToday Roy Schulte from Gartner ran the webinar “Decision Management: What It Is and Why You Need It” describing the state of the art in decision management and offering guidance on how to get started. Here are a few slides: Continue reading

Posted in Business Analytics, Business Processes, Decision Modeling, Decision Models, DMN, Products | 1 Comment

Spreadsheets in Decision Management

On March 14 Carole-Ann Berlioz from Sparkling Logic will run the webinar  “Spreadsheets in Decision Management“: “In some cases, spreadsheets are translated into business rules, in others, they remain the format of choice for maintenance, while systems must learn how to interpret them at runtime” Link  Presentation at DecisionCAMP-2018

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Challenge March-2019 “Organ Transplant Decisioning”

The development of techniques for organ transplant means that now one person’s death may lead to a lifesaving operation for another. This challenge considers one of the many crucial decision-making processes involved in this miracle of modern medicine. Possible solutions to the challenge may be based around both stateful and stateless decision engines. Link

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Why it’s still worth it to learn Java

Python and Go may get all of the hype, but Java is still potentially the smartest language for developers seeking a new job to learn right now. Despite being more than 20 years old, Java remains an enterprise mainstay: The programming language currently tops the TIOBE Programming Community index, and Java developers saw some of the fastest-growing salaries in the US in 2018, according to Glassdoor. Link

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Is Your Insurance Business Missing a Critical Decision Window When it Comes to AI?

Yesterday Craig Bedell from IBM’s Global Insurance Industry Leadership Team wrote: “I believe most insurance companies have hit a critical point in time with regards to their investments in analytics, innovation and even AI, where business leaders are measuring more critically the “success” of programs to date by what they have contributed to the bottom line of the organization. I am seeing innovation and analytics groups struggling, not for the lack of developing new insights, but rather because their insights are not being adapted into the day-to-day decision-making processes of the company to really make the differences they promise.” Recently, Craig and James Taylor co-authored this whitepaper

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The ML Surprise

Peter Norvig points to the ML “surprise” described in Josh Cogan’s article “The Surprising Truth About What it Takes to Build a Machine Learning Product“:  “Optimizing an ML algorithm takes much less relative effort, but collecting data, building infrastructure, and integration each take much more work. The differences between expectations and reality are profound.” Link

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