In the current fast-paced and constantly changing business environment, it is more important than ever for organizations to be agile, monitor business performance, and meet with increasingly stringent compliance requirements. Written by pioneering consultants and bestselling authors with track records of international success, The Decision Model: A

Nowadays Business Decision Modeling is one of the major technological and methodological approaches that support decision-making processes across a wide range of business problems from loan origination and insurance underwriting to clinical guidelines and product recommendations. Business decision modeling is oriented to subject matter experts who build and maintain operational decision models incorporated into modern enterprise architectures.This guide explains how to create and maintain operational decision models for your own business environment in a step-by-step easy to understand style. It consists of a series of dialog-sessions in which an AUTHOR explains major concepts and a READER asks questions and implements the concepts. As a result, you will participate in building complete decision models being able to learn practical decision modeling techniques by example. Starting with a simple decision model, you will learn how to represent more complex decision logic using more and more complex examples. You will end up with a deep understanding of practical decision modeling methods and even learn how to build and use domain-specific libraries of decision models. The guide is based on the Goal-Oriented Approach that provides an intuitive and simple way for building decision models. Starting with high-level business goals and subgoals, you will be able to represent their business logic using Excel-based decision tables, to create and execute test cases, and to analyze produced decisions. The guide is accompanied by open source software commonly known as "OpenRules." Along with the software, you will be able to download, execute and analyze all considered decision models yourself directly in Excel. You can make changes in any provided decision model or create and execute your own decision models. http: //OpenRules.com/Book.htm

Would you like to know how a rules-based decision model can be constructed by a non-programmer? Do you plan to build an operational decision model for your own business environment? This guide explains how to do it in a step-by-step easy to understand style. It consists of a series of dialog-sessions in which an AUTHOR explains basic concepts and a READER asks questions and implements the concepts. As a result, you will participate in building complete decision models being able to learn practical decision modeling techniques by example. The guide is based on the Decision Model and Notation (DMN) Standard and utilizes the popular open source system commonly known as "OpenRules." The guide is accompanied by open source software which allows the reader to download and analyze all considered decision models. The reader can make changes in any provided decision model or write a new one using only MS Excel. Then the reader may execute a modified decision model and analyze the produced results. www.DMNinACTION.com

Internet-of-Things (IoT) Analytics are an integral element of most IoT applications, as it provides the means to extract knowledge, drive actuation services and optimize decision making. IoT analytics will be a major contributor to IoT business value in the coming years, as it will enable organizations to process and fully leverage large amounts of IoT data, which are nowadays largely underutilized. The Building Blocks of IoT Analytics is devoted to the presentation the main technology building blocks that comprise advanced IoT analytics systems. It introduces IoT analytics as a special case of BigData analytics and accordingly presents leading edge technologies that can be deployed in order to successfully confront the main challenges of IoT analytics applications. Special emphasis is paid in the presentation of technologies for IoT streaming and semantic interoperability across diverse IoT streams. Furthermore, the role of cloud computing and BigData technologies in IoT analytics are presented, along with practical tools for implementing, deploying and operating non-trivial IoT applications. Along with the main building blocks of IoT analytics systems and applications, the book presents a series of practical applications, which illustrate the use of these technologies in the scope of pragmatic applications. Technical topics discussed in the book include: Cloud Computing and BigData for IoT analyticsSearching the Internet of ThingsDevelopment Tools for IoT Analytics ApplicationsIoT Analytics-as-a-ServiceSemantic Modelling and Reasoning for IoT AnalyticsIoT analytics for Smart BuildingsIoT analytics for Smart CitiesOperationalization of IoT analyticsEthical aspects of IoT analytics This book contains both research oriented and applied articles on IoT analytics, including several articles reflecting work undertaken in the scope of recent European Commission funded projects in the scope of the FP7 and H2020 programmes. These articles present results of these projects on IoT analytics platforms and applications. Even though several articles have been contributed by different authors, they are structured in a well thought order that facilitates the reader either to follow the evolution of the book or to focus on specific topics depending on his/her background and interest in IoT and IoT analytics technologies. The compilation of these articles in this edited volume has been largely motivated by the close collaboration of the co-authors in the scope of working groups and IoT events organized by the Internet-of-Things Research Cluster (IERC), which is currently a part of EU's Alliance for Internet of Things Innovation (AIOTI).

FINALIST: Business Book Awards 2020 - Specialist Book Category FINALIST: PMI UK National Project Awards 2019 - Project Management Literature Category The business analyst role can cover a wide range of responsibilities, including the elicitation and documenting of business requirements, upfront strategic work, design and implementation phases. Typical difficulties faced by analysts include stakeholders who disagree or don't know their requirements, handling estimates and project deadlines that conflict, and what to do if all the requirements are top priority. The Business Analysis Handbook offers practical solutions to these and other common problems which arise when uncovering requirements or conducting business analysis. Getting requirements right is difficult; this book offers guidance on delivering the right project results, avoiding extra cost and work, and increasing the benefits to the organization. The Business Analysis Handbook provides an understanding of the analyst role and the soft skills required, and outlines industry standard tools and techniques with guidelines on their use to suit the most appropriate situations. Covering numerous techniques such as Business Process Model and Notation (BPMN), use cases and user stories, this essential guide also includes standard templates to save time and ensure nothing important is missed.

In a world on the brink of a global recession caused by the COVID-19 global pandemic, the infrastructure efforts of today and tomorrow are more crucial than ever. For one, they are an indispensable countercyclical tool to mitigate the negative effects of the economic paralysis. But they also constitute a pivotal component for a country's development, raising its competitiveness in the long term. That is why infrastructure will continue to play a critical role even when the pandemic crisis has been tamed. Rapid demographic growth, increasing urbanization, especially in developing countries, coupled with the ounting challenge posed by climate change, are trends that are not going to disappear with the virus. How to cope with these global, long-term trends? How to finance the increasing need for infrastructure? Which major international actors will take the lead? And what role will technology play in shaping the future of infrastructure?

For decades researchers and programmers have used SAS to analyze, summarize, and report clinical trial data. Now Chris Holland and Jack Shostak have updated their popular Implementing CDISC Using SAS, the first comprehensive book on applying clinical research data and metadata to the Clinical Data Interchange Standards Consortium (CDISC) standards. Implementing CDISC Using SAS: An End-to-End Guide, Revised Second Edition, is an all-inclusive guide on how to implement and analyze the Study Data Tabulation Model (SDTM) and the Analysis Data Model (ADaM) data and prepare clinical trial data for regulatory submission. Updated to reflect the 2017 FDA mandate for adherence to CDISC standards, this new edition covers creating and using metadata, developing conversion specifications, implementing and validating SDTM and ADaM data, determining solutions for legacy data conversions, and preparing data for regulatory submission. The book covers products such as Base SAS, SAS Clinical Data Integration, and the SAS Clinical Standards Toolkit, as well as JMP Clinical. Topics included in this edition include an implementation of the Define-XML 2.0 standard, new SDTM domains, validation with Pinnacle 21 software, event narratives in JMP Clinical, STDM and ADAM metadata spreadsheets, and of course new versions of SAS and JMP software. The second edition was revised to add the latest C-Codes from the most recent release as well as update the make_define macro that accompanies this book in order to add the capability to handle C-Codes. The metadata spreadsheets were updated accordingly. Any manager or user of clinical trial data in this day and age is likely to benefit from knowing how to either put data into a CDISC standard or analyzing and finding data once it is in a CDISC format. If you are one such person--a data manager, clinical and/or statistical programmer, biostatistician, or even a clinician--then this book is for you.

This is a problem-solution guide that starts with an introduction to a problem and continues with a discussion of the possible solution. The book covers best practices when working with Drools. The examples and their solutions are accompanied by plenty of code listings and figures providing a better view of the problem. The book is for Java developers who want to create rules-based business logic using the Drools platform. Basic knowledge of Java is essential.

This book provides fresh insights into concepts, methods and new research findings on the causes of excessive food price volatility. It also discusses the implications for food security and policy responses to mitigate excessive volatility. The approaches applied by the contributors range from on-the-ground surveys, to panel econometrics and innovative high-frequency time series analysis as well as computational economics methods. It offers policy analysts and decision-makers guidance on dealing with extreme volatility.

This book takes a practical approach, with step-by-step instructions. It doesn't hesitate to talk about the technologies, but takes time to explain them (to an Excel power-user level). There is a good use of graphics and code where necessary. If you are a business analyst – somebody involved with enterprise IT but at a high level, understanding problems and planning solutions, rather than coding in-depth implementations – then this book is for you. If you are a business user who needs to write rules, or a technical person who needs to support rules, this book is for you. If you are looking for an introduction to rule engine technology, this book will satisfy your needs. If you are a business user and want to write rules using Guvnor/JBoss IDE, this book will be suitable for you. This book will also suit your need if you are a business user and want to understand what Drools can do and how it works, but would rather leave the implementation to a developer.