Data scientists sometimes lament, "Why can't I get anyone to use my predictions?" Great models that make accurate predictions are sometimes disconnected from organizational decision-making. This hurts the business and reduces the data scientists’ perceived value the within the organization. But it doesn't have to be this way. Leading expert James Taylor, author of Decision Management Systems: A Practical Guide to Business Rules and Predictive Analytics, has developed a practical approach you can use to improve adoption and elevate your organization.
Learn how to industrialize your analytic efforts with decision management to get the most out of predictive analytic insights, resources and investments.
James Taylor, CEO of Decision Management Solutions, introduces the key principles of Decision Management Systems and explains their role in a modern information systems architecture. You will learn what it means for Decision Management Systems to be agile, analytic and adaptive. The four principles of Decision Management Systems will be introduced and the power of Decision Management Systems will be shown with case studies.
Based on multiple client engagements, How to Build Decision Management Systems introduces our phased approach to building information systems that improve the effectiveness and efficiency of business operations.
“Part One - Decision Discovery” introduces the first step in successfully building Decision Management Systems, how to discover and model the right decisions. The webinar recording is available on our Omnovia channel.
Combining BPM with Decision Management results in simpler, more agile processes and increases straight through processing and operational effectiveness. Decision Management delivers a shared framework for cross-functional business and IT collaboration creating game-changing culture impacts. In this webinar you will learn how combining Decision Management and BPM delivers simpler, more agile business processes, keeps fast-changing decisions separate from more stable business processes, drives more customer-centric collaboration by putting customer decisions at the focus, makes clear where and how to apply business rules and business rules management systems (BRMS). Webinar recording is available at : https://decisionmanagement.omnovia.com/archives/79352
A Decision Management Solutions Webinar - Retailers see tremendous value in business intelligence and real-time analytics as a way to make sense of the vast amount of data they collect. The challenge is determining where to focus their efforts. To succeed in applying analytics, retailers need to understand how predictive analytics and decision management affect real-world decision-making scenarios.
A discussion of the value of Decision Management and decision modeling to the effective management of large, complex operations - including that of a large, global, financial services organization. Presented by James Taylor of Decision Management Solutions at the Building Business Capability Conference (BBCCon) 2015
Learn how to industrialize your analytic efforts with decision management to get the most out of predictive analytic insights, resources and investments.
James Taylor, CEO of Decision Management Solutions, introduces the key principles of Decision Management Systems and explains their role in a modern information systems architecture. You will learn what it means for Decision Management Systems to be agile, analytic and adaptive. The four principles of Decision Management Systems will be introduced and the power of Decision Management Systems will be shown with case studies.
Based on multiple client engagements, How to Build Decision Management Systems introduces our phased approach to building information systems that improve the effectiveness and efficiency of business operations.
“Part One - Decision Discovery” introduces the first step in successfully building Decision Management Systems, how to discover and model the right decisions. The webinar recording is available on our Omnovia channel.
Combining BPM with Decision Management results in simpler, more agile processes and increases straight through processing and operational effectiveness. Decision Management delivers a shared framework for cross-functional business and IT collaboration creating game-changing culture impacts. In this webinar you will learn how combining Decision Management and BPM delivers simpler, more agile business processes, keeps fast-changing decisions separate from more stable business processes, drives more customer-centric collaboration by putting customer decisions at the focus, makes clear where and how to apply business rules and business rules management systems (BRMS). Webinar recording is available at : https://decisionmanagement.omnovia.com/archives/79352
A Decision Management Solutions Webinar - Retailers see tremendous value in business intelligence and real-time analytics as a way to make sense of the vast amount of data they collect. The challenge is determining where to focus their efforts. To succeed in applying analytics, retailers need to understand how predictive analytics and decision management affect real-world decision-making scenarios.
A discussion of the value of Decision Management and decision modeling to the effective management of large, complex operations - including that of a large, global, financial services organization. Presented by James Taylor of Decision Management Solutions at the Building Business Capability Conference (BBCCon) 2015
Many organizations' agility and responsiveness is hamstrung by their legacy systems. Replacing them wholesale is impossible but the constraint they impose on the business is unacceptable. In this session James Taylor, CEO of Decision Management Solutions, will show how you can use Decision Management and business rules to avoid replacing the whole application while still maximizing agility and improving business alignment.
What you will learn:
How decision components are often the highest change, most difficult to maintain pieces of legacy applications
How Decision Management builds on SOA by externalizing decisions from legacy systems
How a business rules management system dramatically decreases maintenance costs
Why modernizing this way improves business alignment and agility
Webinar recording available at:
https://decisionmanagement.omnovia.com/archives/71756
Decision management and business rules management systems are the ideal platform for an agile and cost-effective compliance approach. In regulated industries like financial services, leading companies are building compliance into every process and system with consistency and transparency across the entire organization and with the agility to meet ever more challenging deadlines. Companies that fail to do so incur huge costs with manual checks and balances and risk significant fines.
In this webinar James Taylor, CEO of Decision Management Solutions and Jan Purchase, Director and Founder of Investment Banking Specialists Lux Magi, share know-how and best practices from their extensive experience of helping clients implement decision management and business rules management systems to conquer complexity, improve agility, lower costs and measure ongoing effectiveness in financial compliance.
The webinar includes illustrations of how the decision management approach has been applied in compliance projects and a walkthrough of real decision model from one of these.
As businesses have an increasing obligation to demonstrate compliance with regulations there is a need for a business architecture view that not only tracks regulations impact but also connects seamlessly to diverse, distributed implementations in automated systems and manual procedures. The Decision Model Notation (DMN) has been used to create a decision architecture for regulatory compliance at a leading global financial organization. This Regulatory Architecture includes business decisions impacted by a variety of global financial regulations – the Dodd Frank Act, in particular. This business architecture has been modeled in the form of decision requirement models and aligned with business process and business organization architectures. Presented by Gagan Saxena of Decision Management Solutions at the Building Business Capability Conference (BBCCon) 2015
A DMN-based full-fledged implementation of the “UServ Product Derby” decision model showing a DMN Decision Requirements Model and a set of DMN-based Decision Tables that implement it. The derby, recently renamed The Decision Management Challenge, deals with vehicle insurance problems including eligibility and premium calculation policies for a hypothetical insurance company.
Presented by James Taylor of Decision Management Solutions and Dr. Jacob Feldman of OpenRules at the Building Business Capability Conference (BBCCon) 2015.
In this webinar recording, James Taylor, CEO of Decision Management Solutions and Claye Greene, Managing Director of Government Solutions Provider TechBlue share learnings and best practices from their extensive experience helping clients modernize their legacy systems with the targeted decision management approach. You will learn why you don’t need to modernize the whole application, why focusing on business rules is not enough; decision management is the essential ingredient and how to use decision modeling to identify and scope targeted legacy modernization efforts.
Business analysts know that modeling business processes, rather than writing about them, defines them more accurately. Business process models make it easier to validate requirements, easier to see opportunities for improvement and easier to manage the process once it is implemented. Replacing traditional specifications with logical business process models based on standard notations like BPMN improves requirements and increases the likelihood of project success.
Yet over-complex processes are common. Complex process models make it harder to engage business owners and reduce the manageability of implementations. One of the prime causes of over-complex processes is the inclusion of decision-making in process designs. Business analysts that identify the decisions in their processes and model them separately – not part of the process but supporting it – find they can simplify process designs, increase agility and bring business users and IT into better alignment. With the publication of a new standard notation - OMG's Decision Model and Notation - and the inclusion of decision modeling in the BABOK, it's time for business analysts to improve their process models by modeling decisions.
Key learning points:
Decisions are central to straight through processing, process innovation and process effectiveness.
Process models obscure decision-making and become over-complex when it is embedded
A standards-based approach to decision modeling is a key technique for process analysts
The new Decision Model and Notation (DMN) standard has been used to gather requirements for and to design Enterprise IT Management dashboards at two Fortune 200 Financial Corporations. These dashboards are used to manage 100+ projects being released every 2 weeks into production across hundreds of critical applications ranging from mainframe, client-server, web and mobile applications.
Presentation from BBC2014
Decision Modeling is a new Technique in v3 of the BABOK(r) Guide. It has also become a key element of the Business Intelligence and Business Process Management Perspectives. At the June 2014 IIBA Bay Area Event, James Taylor presents Decision Modeling as a technique (following the new Decision Model and Notation standard), shows how modeling decisions improves business analysis and requirements specification, and discusses the role of decision modeling in business process, business rules, business intelligence and analytic projects.
Today’s healthcare executives are seeking performance improvement across multiple dimensions: expenses and profitability, waste, risk, and patient satisfaction and outcomes. That’s exactly what Crowe Horwath LLP’s Performance Improvement team delivers.
This brochure provides an overview our our service and value proposition.
Mainframe Assessment with Modern Systems' Portfolio Analysis ServicesModern Systems
Legacy systems have passed through many hands over many years, often without proper documentation of features or functional relationships. The most common issue with modernizing a system that very few people understand is that planning for and understanding the breadth and potential pitfalls of a project is virtually impossible without a lot of help. Undergoing a mainframe assessment using Modern Systems' Portfolio Analysis services can significantly reduce risk, cost, and project timelines.
A 2013 survey of IT leaders in the US insurance industry by Gartner reflects just how difficult planning modernizations can be.
- Only 42% of respondents said their modernization projects were completed within originally planned budget.
- Just 34% of the modernization attempts covered the originally planned scope, leaving a whopping 66% of these firms victims of dreaded and out of control scope creep.
- What’s worse, only 18% of respondents completed these projects within their originally planned timeframe.
In other words, modernization is a brutal undertaking. In order to develop well-designed applications from legacy environments, powerful tools and expertise are required to analyze the legacy system and aid in generating new programs that are architecturally sound and utilize modern design methods.
The data and reports gathered in a Modern Systems Portfolio Analysis mainframe assessment reduce risk by ensuring all technical inventory and use cases are documented and accounted for. It also reveals potential bumps in the road to modernization before they have a chance to derail a project, so mitigation plans can be established up front.
This mainframe assessment work is automated and precise, saving months of time, thousands of dollars in man hours- and ensures no critical requirements or functionality are left out of the target state design. This data also impacts regression testing, making it more accurate and efficient- reducing time to target.
In addition to the risk, cost, and time reduction, customers who undergo a Modern Systems mainframe assessment are able to reduce the scope of their modernization project by an average of 40%.
Here’s how it works:
First, Modern Systems documents the legacy environment's current state and any important dependencies or conditions such as external interfaces, data volumes, batch dependencies, etc.
From there, Modern Systems resources develop the Final Application Inventory package, containing analysis on unused code, Resource Definition and Usage, easy-to-understand visual diagrams laying out the legacy environment, highlighted areas of concentration, and much more.
Finally, the Modern Systems team holds a strategic workshop with your project stakeholders to discuss our findings, provide Optimum Solution Recommendations for areas of concentration, and to map out an informed modernization strategy and roadmap, backed by a soup-to-nuts mainframe assessment and over 3 decades of expe
2010 BDPA Natl Tech Conf Presentation Turning A Business Crisis Into A Reve...MJD Management Group
The workshop provides the audience with the opportunity to learn how to successfully resolve customer crises and how to position to facilitate sales after the crisis situation has been resolved.
IT organizations are faced with a rapidly evolving environment coupled with a
more headcount-constrained staff, where standardization on optimal systems
and procedures is a critical success factor.
Aviation Week Adv Mfg Metrics that Matter webcastJulie Fraser
Iyno's Julie Fraser participated in an Aviation Week Webcast sponsored by Deltek focused on linking business, engineering, and manufacturing. Fraser presents MESA International Pursuit of Performance Excellence data in the context of discrete project-based manufacturing.
Decision CAMP 2014 - James Taylor - Decision Management 101Decision CAMP
Decision Management is both an approach and a technology stack.
In this opening day workshop, Decision Management consultant and author James Taylor will introduce both.
We'll begin with the discovery and modeling of suitable decisions, move into the construction of decision services and wrap up with the importance of decision analysis for continuous improvement. The critical technology capabilities - managing decision logic, embedding analytics, monitoring decision performance, and optimizing results - will all be introduced and presented in a coherent architecture for building Decision Management Systems.
Different adoption paths and some best practices will conclude the session, putting you on a path to Decision Management success.
In an era of Big Data organizations are looking to use analytic insight to improve
their business. Rapidly changing competitive landscapes and the need to evaluate and
adopt new business models is pushing organizations to become more adaptive. How
can these imperatives be reflected in the way we build systems? In response to these imperatives, organizations are increasingly buying or building a new class of systems - Decision Management Systems. Decision Management Systems leverage the growing power of predictive analytics to create agile, analytic and adaptive processes and systems.
Many organizations' agility and responsiveness is hamstrung by their legacy systems. Replacing them wholesale is impossible but the constraint they impose on the business is unacceptable. In this session James Taylor, CEO of Decision Management Solutions, will show how you can use Decision Management and business rules to avoid replacing the whole application while still maximizing agility and improving business alignment.
What you will learn:
How decision components are often the highest change, most difficult to maintain pieces of legacy applications
How Decision Management builds on SOA by externalizing decisions from legacy systems
How a business rules management system dramatically decreases maintenance costs
Why modernizing this way improves business alignment and agility
Webinar recording available at:
https://decisionmanagement.omnovia.com/archives/71756
Decision management and business rules management systems are the ideal platform for an agile and cost-effective compliance approach. In regulated industries like financial services, leading companies are building compliance into every process and system with consistency and transparency across the entire organization and with the agility to meet ever more challenging deadlines. Companies that fail to do so incur huge costs with manual checks and balances and risk significant fines.
In this webinar James Taylor, CEO of Decision Management Solutions and Jan Purchase, Director and Founder of Investment Banking Specialists Lux Magi, share know-how and best practices from their extensive experience of helping clients implement decision management and business rules management systems to conquer complexity, improve agility, lower costs and measure ongoing effectiveness in financial compliance.
The webinar includes illustrations of how the decision management approach has been applied in compliance projects and a walkthrough of real decision model from one of these.
As businesses have an increasing obligation to demonstrate compliance with regulations there is a need for a business architecture view that not only tracks regulations impact but also connects seamlessly to diverse, distributed implementations in automated systems and manual procedures. The Decision Model Notation (DMN) has been used to create a decision architecture for regulatory compliance at a leading global financial organization. This Regulatory Architecture includes business decisions impacted by a variety of global financial regulations – the Dodd Frank Act, in particular. This business architecture has been modeled in the form of decision requirement models and aligned with business process and business organization architectures. Presented by Gagan Saxena of Decision Management Solutions at the Building Business Capability Conference (BBCCon) 2015
A DMN-based full-fledged implementation of the “UServ Product Derby” decision model showing a DMN Decision Requirements Model and a set of DMN-based Decision Tables that implement it. The derby, recently renamed The Decision Management Challenge, deals with vehicle insurance problems including eligibility and premium calculation policies for a hypothetical insurance company.
Presented by James Taylor of Decision Management Solutions and Dr. Jacob Feldman of OpenRules at the Building Business Capability Conference (BBCCon) 2015.
In this webinar recording, James Taylor, CEO of Decision Management Solutions and Claye Greene, Managing Director of Government Solutions Provider TechBlue share learnings and best practices from their extensive experience helping clients modernize their legacy systems with the targeted decision management approach. You will learn why you don’t need to modernize the whole application, why focusing on business rules is not enough; decision management is the essential ingredient and how to use decision modeling to identify and scope targeted legacy modernization efforts.
Business analysts know that modeling business processes, rather than writing about them, defines them more accurately. Business process models make it easier to validate requirements, easier to see opportunities for improvement and easier to manage the process once it is implemented. Replacing traditional specifications with logical business process models based on standard notations like BPMN improves requirements and increases the likelihood of project success.
Yet over-complex processes are common. Complex process models make it harder to engage business owners and reduce the manageability of implementations. One of the prime causes of over-complex processes is the inclusion of decision-making in process designs. Business analysts that identify the decisions in their processes and model them separately – not part of the process but supporting it – find they can simplify process designs, increase agility and bring business users and IT into better alignment. With the publication of a new standard notation - OMG's Decision Model and Notation - and the inclusion of decision modeling in the BABOK, it's time for business analysts to improve their process models by modeling decisions.
Key learning points:
Decisions are central to straight through processing, process innovation and process effectiveness.
Process models obscure decision-making and become over-complex when it is embedded
A standards-based approach to decision modeling is a key technique for process analysts
The new Decision Model and Notation (DMN) standard has been used to gather requirements for and to design Enterprise IT Management dashboards at two Fortune 200 Financial Corporations. These dashboards are used to manage 100+ projects being released every 2 weeks into production across hundreds of critical applications ranging from mainframe, client-server, web and mobile applications.
Presentation from BBC2014
Decision Modeling is a new Technique in v3 of the BABOK(r) Guide. It has also become a key element of the Business Intelligence and Business Process Management Perspectives. At the June 2014 IIBA Bay Area Event, James Taylor presents Decision Modeling as a technique (following the new Decision Model and Notation standard), shows how modeling decisions improves business analysis and requirements specification, and discusses the role of decision modeling in business process, business rules, business intelligence and analytic projects.
Today’s healthcare executives are seeking performance improvement across multiple dimensions: expenses and profitability, waste, risk, and patient satisfaction and outcomes. That’s exactly what Crowe Horwath LLP’s Performance Improvement team delivers.
This brochure provides an overview our our service and value proposition.
Mainframe Assessment with Modern Systems' Portfolio Analysis ServicesModern Systems
Legacy systems have passed through many hands over many years, often without proper documentation of features or functional relationships. The most common issue with modernizing a system that very few people understand is that planning for and understanding the breadth and potential pitfalls of a project is virtually impossible without a lot of help. Undergoing a mainframe assessment using Modern Systems' Portfolio Analysis services can significantly reduce risk, cost, and project timelines.
A 2013 survey of IT leaders in the US insurance industry by Gartner reflects just how difficult planning modernizations can be.
- Only 42% of respondents said their modernization projects were completed within originally planned budget.
- Just 34% of the modernization attempts covered the originally planned scope, leaving a whopping 66% of these firms victims of dreaded and out of control scope creep.
- What’s worse, only 18% of respondents completed these projects within their originally planned timeframe.
In other words, modernization is a brutal undertaking. In order to develop well-designed applications from legacy environments, powerful tools and expertise are required to analyze the legacy system and aid in generating new programs that are architecturally sound and utilize modern design methods.
The data and reports gathered in a Modern Systems Portfolio Analysis mainframe assessment reduce risk by ensuring all technical inventory and use cases are documented and accounted for. It also reveals potential bumps in the road to modernization before they have a chance to derail a project, so mitigation plans can be established up front.
This mainframe assessment work is automated and precise, saving months of time, thousands of dollars in man hours- and ensures no critical requirements or functionality are left out of the target state design. This data also impacts regression testing, making it more accurate and efficient- reducing time to target.
In addition to the risk, cost, and time reduction, customers who undergo a Modern Systems mainframe assessment are able to reduce the scope of their modernization project by an average of 40%.
Here’s how it works:
First, Modern Systems documents the legacy environment's current state and any important dependencies or conditions such as external interfaces, data volumes, batch dependencies, etc.
From there, Modern Systems resources develop the Final Application Inventory package, containing analysis on unused code, Resource Definition and Usage, easy-to-understand visual diagrams laying out the legacy environment, highlighted areas of concentration, and much more.
Finally, the Modern Systems team holds a strategic workshop with your project stakeholders to discuss our findings, provide Optimum Solution Recommendations for areas of concentration, and to map out an informed modernization strategy and roadmap, backed by a soup-to-nuts mainframe assessment and over 3 decades of expe
2010 BDPA Natl Tech Conf Presentation Turning A Business Crisis Into A Reve...MJD Management Group
The workshop provides the audience with the opportunity to learn how to successfully resolve customer crises and how to position to facilitate sales after the crisis situation has been resolved.
IT organizations are faced with a rapidly evolving environment coupled with a
more headcount-constrained staff, where standardization on optimal systems
and procedures is a critical success factor.
Aviation Week Adv Mfg Metrics that Matter webcastJulie Fraser
Iyno's Julie Fraser participated in an Aviation Week Webcast sponsored by Deltek focused on linking business, engineering, and manufacturing. Fraser presents MESA International Pursuit of Performance Excellence data in the context of discrete project-based manufacturing.
Decision CAMP 2014 - James Taylor - Decision Management 101Decision CAMP
Decision Management is both an approach and a technology stack.
In this opening day workshop, Decision Management consultant and author James Taylor will introduce both.
We'll begin with the discovery and modeling of suitable decisions, move into the construction of decision services and wrap up with the importance of decision analysis for continuous improvement. The critical technology capabilities - managing decision logic, embedding analytics, monitoring decision performance, and optimizing results - will all be introduced and presented in a coherent architecture for building Decision Management Systems.
Different adoption paths and some best practices will conclude the session, putting you on a path to Decision Management success.
In an era of Big Data organizations are looking to use analytic insight to improve
their business. Rapidly changing competitive landscapes and the need to evaluate and
adopt new business models is pushing organizations to become more adaptive. How
can these imperatives be reflected in the way we build systems? In response to these imperatives, organizations are increasingly buying or building a new class of systems - Decision Management Systems. Decision Management Systems leverage the growing power of predictive analytics to create agile, analytic and adaptive processes and systems.
Predictive Analytics at the Speed of Business -
How decision management and a real-time infrastructure get predictive analytics where and when you need them.
Organizations are looking to maximize the value of their analytics investment. They need to accelerate the deployment process, reduce costs and get the analytic insight where they need it, when they need it. Increasingly organizations must deploy and manage many models, use those models in real-time and integrate predictive analytics into a wide range of operational systems – in the cloud, on-premise, for Hadoop and in-database. In this webinar you will learn how Decision Management and ADAPA – a proven approach and real-time infrastructure – transform passive models into operational success. This webinar is jointly presented by James Taylor, CEO of Decision Management Solutions and Dr. Alex Guazzelli, Vice President of Analytics at Zementis.
To ensure that Decision Management Systems are analytic and adaptive you must embed the results of data mining and predictive analytics in them. In this webinar you will learn what can be discovered using data mining and predictive analytic techniques and how this can be applied to the decision-making embedded in Decision Management Systems. The role of analytics in predicting risk, fraud and opportunity and the importance of continuous improvement and learning is also be covered.
Deploying analytics with a rules-based infrastructure, James Taylor, CEO of Decision Management Solutions, presentation at Predictive Analytics World, SF 2011. #pawcon
The second in our 3 part series on How to Build Decision Management Systems. Part 2 Decision Services describes the core of a Decision Management System, a set of software components that make these decisions accurately, reliably and responsively, leveraging advanced analytics and business rules management systems.
A presentation on Customer Decision Management and how it results in more accurate, more real-time, more consistent, more agile and more scalable customer decisions. Presented at Teradata Partners 2013
Predictive analytic models are not new within many analytical organizations. However, the use of predictive analytics is growing rapidly. Data-driven decision-making initiatives are compelling more and more enterprises to move their analytics efforts beyond the basics. Enterprises must go from measurement and reporting to predictions and decision management. With ever-increasing amounts of historical data ready for mining, the right predictive analytic models can help an enterprise understand future behavior – adherence to medical prescriptions, increased or decreased spending, loan repayment, and more. By driving better decision-making, such insights can be transformative. Join us as we look into best-practices for building a predictive enterprise, technology tips for using and implementing predictive analytics tools, and guidelines for building predictive models.
This webinar focuses on business rules and on Business Rules Management Systems as a platform for Decision Management Systems. You will learn how a Business Rules Management System makes the agility and transparency you need possible and what the key components are for an effective Business Rules Management System. The power of business rules to support both policy and analytic rules and the role of decisions in effective business rules solutions will also be discussed.
What opportunities are you looking for to improve your business performance? In this webinar you will learn six opportunities that are readily available when you adopt a decision management approach to business rules and predictive analytics.
The Decision Management Manifesto lays out key principles of Decision Management - why decisions are central to your requirements process, why it makes sense to explicitly design decisions before applying technology. Using real world projects this webinar explains the rationale for each part of the manifesto and shows the value it can bring to your projects now and in the future.
A rebroadcast of one of the best reviewed sessions at this year's Predictive Analytics World. Learn the critical success factors in delivering business value with advanced analytics.
Leading organizations today are looking to scale their advanced analytics capabilities, especially data mining and predictive analytics, to improve business performance, reduce fraud and improve customer responsiveness. However traditional analytic project approaches are hard to scale and difficult to implement in the real-time environment required in modern enterprise architectures.
One of the most important steps in a predictive analytic effort is correctly framing the problem a way that creates a shared understanding of the business problem across business, IT and analytics teams. A decision requirements model makes it clear how to best leverage analytics. Watch the webinar recording at http://decisionmanagement.omnovia.com/archives/223762
While many Digital Transformation initiatives are focused on improving the customer experience, often too little attention is paid to the customer-facing operational decisions that impact customers every day. To get the most from your Digital Transformation efforts, your customers’ experience and the decisions that impact it cannot be ignored.
Successful digital programs extend their Digital Business Platforms with 3 critical elements: decision modeling, predictive analytics and business rules technology. Coordinating these technologies into a virtual decision hub. Decision Management automates and improves every digital interaction and delivers agile, data-driven, real-time outcomes.
Decision management's systematic embedding of predictive analytics into automated decision-making systems complements cloud technologies and maximizes the value of predictive analytics.
Similar to Models Collecting Dust? How to Transform Your Results from Interesting to Impactful (20)
Presented to eRum (Budapest), May 2018
There are many common workloads in R that are "embarrassingly parallel": group-by analyses, simulations, and cross-validation of models are just a few examples. In this talk I'll describe the doAzureParallel package, a backend to the "foreach" package that automates the process of spawning a cluster of virtual machines in the Azure cloud to process iterations in parallel. This will include an example of optimizing hyperparameters for a predictive model using the "caret" package.
By David Smith. Presented at Microsoft Build (Seattle), May 7 2018.
Your data scientists have created predictive models using open-source tools, proprietary software, or some combination of both, and now you are interested in lifting and shifting those models to the cloud. In this talk, I'll describe how data scientists can transition their existing workflows — while using mostly the same tools and processes — to train and deploy machine learning models based on open source frameworks to Azure. I'll provide guidance on keeping connections to data sources up-to-date, evaluating and monitoring models, and deploying applications that make use of those models.
Presentation delivered by David Smith to NY R Conference https://www.rstats.nyc/, April 2018:
Minecraft is an open-world creativity game, and a hit with kids. To get kids interested in learning to program with R, we created the "miner" package. This package is a collection of simple functions that allow you to connect with a Minecraft instance, manipulate the world within by creating blocks and controlling the player, and to detect events within the world and react accordingly.
The miner package is intended mainly for kids, to inspire them to learn R while playing Minecraft. But the development of the package also provides some useful insights into how to build an R package to interface with a persistent API, and how to instruct others on its use. In this talk I'll describe how to set up your own Minecraft server, and how to use and extend the package. I'll also provide a few examples of the package in action in a live Minecraft session.
While Python is a widely-used tool for AI development, in this talk I'll make the case for considering R as a platform for developing models for intelligent applications. Firstly, R provides a first-class experience working deep learning frameworks with its keras integration. Equally importantly, it provides the most comprehensive suite of statistical data analysis tools, which are extremely useful for many intelligent applications such as transfer learning. I'll give a few high-level examples in this talk, and we'll go into further detail in the accompanying interactive code lab.
There are many common workloads in R that are "embarrassingly parallel": group-by analyses, simulations, and cross-validation of models are just a few examples. In this talk I'll describe several techniques available in R to speed up workloads like these, by running multiple iterations simultaneously, in parallel.
Many of these techniques require the use of a cluster of machines running R, and I'll provide examples of using cloud-based services to provision clusters for parallel computations. In particular, I will describe how you can use the SparklyR package to distribute data manipulations using the dplyr syntax, on a cluster of servers provisioned in the Azure cloud.
Presented by David Smith at Data Day Texas in Austin, January 27 2018.
A look at the changing perceptions of R, from the early days of the R project to today. Microsoft sponsor talk, presented by David Smith to the useR!2017 conference in Brussels, July 5 2017.
Predicting Loan Delinquency at One Million Transactions per SecondRevolution Analytics
Real-time applications of predictive models must be able to generate predictions at the rate that transactions are generated. Previously, such applications of models trained using R needed to be converted to other languages like C++ or Java to achieve the required throughput. In this talk, I’ll describe how to use the in-database R processing capabilities of Microsoft R Server to detect fraud in a SQL Server database of loan records at a rate exceeding one million transactions per second. I will also show the process of training the underlying gradient-boosted tree model on a large training set using the out-of-memory algorithms of Microsoft R.
Presented by David Smith at The Data Science Summit, Chicago, April 20 2017.
The ability to independently reproduce results is a critical issue within the scientific community today, and is equally important for collaboration and compliance in business. In this talk, I'll introduce several features available in R that help you make reproducibility a standard part of your data science workflow. The talk will include tips on working with data and files, combining code and output, and managing R's changing package ecosystem.
Presented by David Smith, R Community Lead (Microsoft), at Monktoberfest October 2016.
The value of open source isn’t just in the software itself. The communities that form around open source software provide just as much value and sometimes even more: in ongoing development, in documentation, in support, in marketing, and as a supply of ready-trained employees. Companies who build on open source tend to focus on the software, but neglect communities at their peril.
In this talk, I share some of my experiences in building community for an open-source software company, Revolution Analytics, and perspectives since the acquisition by Microsoft in 2015.
R is more than just a language. Many of the reasons why R has become such a popular tool for data science come from the ecosystem surrounding the R project. R users benefit from the many resources and packages created by the community, while commercial companies (including Microsoft) provide tools to extend and support R, and services to help people use R.
In this talk, I will give an overview of the R Ecosystem and describe how it has been a critical component of R’s success, and include several examples of Microsoft’s contributions to the ecosystem.
(Presented to EARL London, September 2016)
(Presented by David Smith at useR!2016, June 2016. Recording: https://channel9.msdn.com/Events/useR-international-R-User-conference/useR2016/R-at-Microsoft )
Since the acquisition of Revolution Analytics in April 2015, Microsoft has embarked upon a project to build R technology into many Microsoft products, so that developers and data scientists can use the R language and R packages to analyze data in their data centers and in cloud environments.
In this talk I will give an overview (and a demo or two) of how R has been integrated into various Microsoft products. Microsoft data scientists are also big users of R, and I'll describe a couple of examples of R being used to analyze operational data at Microsoft. I'll also share some of my experiences in working with open source projects at Microsoft, and my thoughts on how Microsoft works with open source communities including the R Project.
Hadoop is famously scalable. Cloud Computing is famously scalable. R – the thriving and extensible open source Data Science software – not so much. But what if we seamlessly combined Hadoop, Cloud Computing, and R to create a scalable Data Science platform? Imagine exploring, transforming, modeling, and scoring data at any scale from the comfort of your favorite R environment. Now, imagine calling a simple R function to operationalize your predictive model as a scalable, cloud-based Web Service. Learn how to leverage the magic of Hadoop on-premises or in the cloud to run your R code, thousands of open source R extension packages, and distributed implementations of the most popular machine learning algorithms at scale.
In the Adani-Hindenburg case, what is SEBI investigating.pptxAdani case
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Digital Transformation and IT Strategy Toolkit and TemplatesAurelien Domont, MBA
This Digital Transformation and IT Strategy Toolkit was created by ex-McKinsey, Deloitte and BCG Management Consultants, after more than 5,000 hours of work. It is considered the world's best & most comprehensive Digital Transformation and IT Strategy Toolkit. It includes all the Frameworks, Best Practices & Templates required to successfully undertake the Digital Transformation of your organization and define a robust IT Strategy.
Editable Toolkit to help you reuse our content: 700 Powerpoint slides | 35 Excel sheets | 84 minutes of Video training
This PowerPoint presentation is only a small preview of our Toolkits. For more details, visit www.domontconsulting.com
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25. Case study: Insurer
Business challenges Solution Benefits
Use analytics to Model and Find the decisions
improve underwriting decompose decisions that could be
Map decisions to impacted and
Embed analytics in refocused analytic
claim processing systems and
organizations effort
application
Constrained analytic
effort to ensure
successful
implementation