Two Frustrations With the Data Science Industry

Posted on May 14, 2017 by decisionmanagementcommunity

NathanBrixiusOn May 13, 2017 Nathan Brixius described his frustrations with data science industry (such as overclassification and overreliance on credentials) starting with this rant:

“I don’t give a shit if you call yourself a data scientist, an analyst, a machine learning practitioner, an operations research specialist, a data engineer, a modeler, a statistician, a code poet, or a squirrel. I don’t care if you have a PhD, if you went to MIT or a community college, if you were born on a farm or in a city, or if Andrew Ng DMs you for tips. I want to know what you can do, if you can share, if you can learn, if you can listen, and if you can stand for what is right even if it’s unpopular. If we’re good there, the rest we can figure out together.” Continue reading →

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OMG Event “BPMN IN ACTION”

Posted on May 11, 2017 by decisionmanagementcommunity

The Object Management Group (OMG) invites Business Process Modeling practitioners and interested parties to attend this free innovative and informative meet and greet “BPMN in Action“. Cocktails and light snacks will be served while leading software vendors will demonstrate live the iterative elaboration and interchange of a BPMN model using their respective tools that implement the BPMN standard. The event will take place on June 5 at Radisson Blu Hotel in Brussels. Hopefully, we will see a similar “DMN in Action” event in the nearest future.

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A Popular Overview of Natural Language Processing and related AI techniques

Posted on May 8, 2017 by decisionmanagementcommunity

 

This new article “Overview of Artificial Intelligence and Role of Natural Language Processing in Big Data” in simple terms explains major AI techniques and key differences between NLP, AI, ML, DL & NN

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Interpreting Machine Learning

Posted on May 2, 2017 by decisionmanagementcommunity

Correlation“You’ve probably heard by now that machine learning algorithms can use big data to predict whether a donor will give to a charity, whether an infant in a NICU will develop sepsis, whether a customer will respond to an ad, and on and on. Machine learning can even drive cars and predict elections. … Err, wait. Can it? I believe it can, but these recent high-profile hiccups should leave everyone who works with data (big or not) and machine learning algorithms asking themselves some very hard questions: do I understand my data? Do I understand the model and answers my machine learning algorithm is giving me? And do I trust these answers?” Patrick Hall published an article that presents several approaches beyond the usual error measures and assessment plots for visualizing data and interpreting machine learning models and results.

Posted in Artificial Intelligence, Business Analytics, Decision Modeling | Leave a comment

RapidGen is our New Sponsor

Posted on April 27, 2017 by decisionmanagementcommunity

DMCommunity.org welcomes a new premium sponsor RapidGen Software who offers a powerful DMN execution engine capable to handle complex logic at scale. RapidGen translates XML output from DMN modeling tools into highly efficient, directly executable machine code using a single-pass compiler. RapidGen Software is based in London, UK.  With its extensive experience in decision-table based logic programming, the company’s software is integral to business-critical applications in large scale sites in Europe and North America including aerospace parts tracking, mobile telecoms billing, sales distribution and nuclear power. Read more about RapidGen here. Read about current sponsors and sponsorship benefits here.

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Complete DMN Level 3 Executable Solution for Business Users

Posted on April 18, 2017 by decisionmanagementcommunity

DMN-ExecuteBruce Silver and Edson Tirelli will be presenting a new executable DMN solution at the bpmNEXT on April 19 in Santa Barbara, CA. This solution integrates Trisotech DMN Modeler, Red Hat DMN execution software and Bruce Silver’s methodology known as DMN Method and Style.  According to the authors, a new DMN implementation provides a complete DMN Level 3 solution with full boxed expression and FEEL support, in-tool execution, and deployment to a cloud-based decision service. See a related LinkedIn discussion.       ==     The actual presentation is now available at youtube

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NoOps vs DevOps

Posted on April 13, 2017 by decisionmanagementcommunity

In 2011 Mike Gualtieri of Forrester Research coined the term NoOps in his controversial blog post “I don’t want DevOps. I want NoOps.” In particular, Gualtieri said: “Developers should look to spend more of their time getting closer to the business, not getting closer to the hardware. I think DevOps is a step backward. Instead I propose NoOps. Like DevOps the goal of NoOps is also to improve the process of deploying applications. But, NoOps means that application developers will never have to speak with an operations professional again. NoOps will achieve this nirvana, by using cloud infrastructure-as-a-service and platform-as-a-service to get the resources they need when they need them.” Read the latest take on this topic in the new post “Is NoOps the End of DevOps? Think Again” by Jordan Bash.

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Meet DMN Book Authors at DecisionCAMP-2017

Posted on April 13, 2017 by decisionmanagementcommunity

You have an opportunity to meet face-to-face with the authors of major Decision Modeling books at DecisionCAMP in London in July. Here they are:

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Building Business Capability on Nov 6-10, 2017 in Orlando, FL

Posted on April 6, 2017 by decisionmanagementcommunity

Join 1500 of business analysts, decision management practitioners, vendors and leading experts on November at the Loews Pacific Resort in Orlando, Florida for BBC 2017. This is the major annual conference that provides insight into Business Analysis, Business Architecture, Business Process, Business Rules, Business Decisions, and Business Strategy & Transformation toward the pursuit of business excellence.

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Transforming “Dark Data” into Data-Driven Insights

Posted on April 6, 2017 by decisionmanagementcommunity

A new paper, written by Tho Nguyen of Teradata and James Taylor of Decision Management Solutions, examines “Dark Data” that includes sensor and streaming data, image data, audio and video data, as well as semi-structured data (e.g., log files, survey data, notes or presentations, email correspondence, and financial statements). New analytic technologies—such as artificial intelligence, cognitive, deep learning and machine learning—are shining new light on dark data, allowing organizations to gain more business value from a wider spectrum of data.

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