Download or read book PMML in Action written by Alex Guazzelli and published by Createspace Independent Publishing Platform. This book was released on 2012-01-31 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: The data mining community has derived a broad foundation of statistical algorithms and software solutions that has allowed predictive analytics to become a standard approach used in science and industry. For many years, much emphasis has been placed on the development of predictive models. As a consequence, the market place offers a range of powerful tools, many open-source, for effective model building. However, once we turn to the operational deployment and practical application of predictive solutions within an existing IT infrastructure, we face a much more limited choice of options. Often it takes months for models to be integrated and deployed via custom code or proprietary processes. The Predictive Model Markup Language (PMML) standard has reached a significant stage of maturity and has obtained broad industry support, allowing users to develop predictive solutions within one application and use another to execute them. Previously, this was very difficult, but with PMML, the exchange of predictive solutions between compliant applications is now straightforward. The aim of this book is to present PMML from a practical perspective. It contains a variety of code snippets so that concepts are made clear through the use of examples. Readers are assumed to have a basic knowledge of predictive analytics and its techniques and so the book is intended for data mining movers and shakers: anyone interested in moving predictive analytic solutions between applications, including students and scientists. PMML in Action is a great way to learn how to represent your predictive solutions through a mature and refined open standard. For the 2nd edition, the book has been completely revised for PMML 4.1, the latest version of PMML. It includes new chapters and an expanded description of how to represent multiple models in PMML, including model ensemble, segmentation, chaining, and composition. The book is divided into six parts, taking you in a PMML journey in which language elements and attributes are used to represent not only modeling techniques but also data pre- and post-processing. With PMML, users benefit from a single and concise standard to represent predictive models, thus avoiding the need for custom code and proprietary solutions. You too can join the PMML movement! Unleash the power of predictive analytics and data mining today

Download or read book Collective Intelligence in Action written by Satnam Alag and published by Simon and Schuster. This book was released on 2008-09-30 with total page 609 pages. Available in PDF, EPUB and Kindle. Book excerpt: There's a great deal of wisdom in a crowd, but how do you listen to a thousand people talking at once? Identifying the wants, needs, and knowledge of internet users can be like listening to a mob. In the Web 2.0 era, leveraging the collective power of user contributions, interactions, and feedback is the key to market dominance. A new category of powerful programming techniques lets you discover the patterns, inter-relationships, and individual profiles-the collective intelligence--locked in the data people leave behind as they surf websites, post blogs, and interact with other users. Collective Intelligence in Action is a hands-on guidebook for implementing collective intelligence concepts using Java. It is the first Java-based book to emphasize the underlying algorithms and technical implementation of vital data gathering and mining techniques like analyzing trends, discovering relationships, and making predictions. It provides a pragmatic approach to personalization by combining content-based analysis with collaborative approaches. This book is for Java developers implementing Collective Intelligence in real, high-use applications. Following a running example in which you harvest and use information from blogs, you learn to develop software that you can embed in your own applications. The code examples are immediately reusable and give the Java developer a working collective intelligence toolkit. Along the way, you work with, a number of APIs and open-source toolkits including text analysis and search using Lucene, web-crawling using Nutch, and applying machine learning algorithms using WEKA and the Java Data Mining (JDM) standard. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.

Download or read book Apache Pulsar in Action written by David Kjerrumgaard and published by Simon and Schuster. This book was released on 2021-12-14 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Distributed applications demand reliable, high-performance messaging. The Apache Pulsar server-to-server messaging system provides a secure, stable platform without the need for a stream processing engine like Spark. Contributed by Yahoo to the Apache Foundation, Pulsar is mature and battle-tested, handling millions of messages per second for over three years at Yahoo. Apache Pulsar in Action is a comprehensive and practical guide to building high-traffic applications with Pulsar, delivering extreme levels of speed and durability. about the technology Pulsar is a streaming messaging system designed for high performance server-to-server messaging. Built and tested under intense conditions at Yahoo, Pulsar has been proven in production and can handle millions of messages per second. Now free and open-source, Pulsar''s unique architecture helps solve some of the challenges of modern development. Pulsar avoids latency in streaming data transmission, making it a powerful tool for IoT Edge analytics. Its unified messaging model improves the performance of microservices architecture, and its tiered storage capabilities allow for larger volumes of data to be handled without fear of data loss. Pulsar''s flexible API interface works with Java, C++, Python, and Go, making it easy to incorporate Pulsar into your stack. about the book Apache Pulsar in Action is a hands-on guide to building scalable streaming messaging systems for distributed applications and microservices systems. You''ll start with Pulsar''s fundamentals, each illustrated by real-world examples, as you get to grips with Pulsar''s unique architecture. Pulsar contributor David Kjerrumgaard teaches the skills you need to deploy a Pulsar server, ingest data from third-party systems, and deploy lightweight computing logic with simple functions. You''ll learn to employ Pulsar''s seamless scalability through relatable case studies, including an IOT analytics application that can be deployed within a resource constrained environment and a microservices application based on Pulsar functions. At the end of this practical book, you''ll be ready to fully take advantage of Pulsar to create high-traffic message-driven applications. what''s inside Publish from Apache Pulsar into third-party data repositories and platforms Design and develop Apache Pulsar functions Perform interactive SQL queries against data stored in Apache Pulsar Examples of Pulsar-based microservices that you can download and try yourself about the reader Written for experienced Java developers. No prior knowledge of Pulsar is needed. about the author David Kjerrumgaard is the Director of Solution Architecture at Streamlio, and a contributor to the Apache Pulsar and Apache NiFi projects.

Download or read book R Predictive Analysis written by Tony Fischetti and published by Packt Publishing Ltd. This book was released on 2017-03-31 with total page 1065 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master the art of predictive modeling About This Book Load, wrangle, and analyze your data using the world's most powerful statistical programming language Familiarize yourself with the most common data mining tools of R, such as k-means, hierarchical regression, linear regression, Naive Bayes, decision trees, text mining and so on. We emphasize important concepts, such as the bias-variance trade-off and over-fitting, which are pervasive in predictive modeling Who This Book Is For If you work with data and want to become an expert in predictive analysis and modeling, then this Learning Path will serve you well. It is intended for budding and seasoned practitioners of predictive modeling alike. You should have basic knowledge of the use of R, although it's not necessary to put this Learning Path to great use. What You Will Learn Get to know the basics of R's syntax and major data structures Write functions, load data, and install packages Use different data sources in R and know how to interface with databases, and request and load JSON and XML Identify the challenges and apply your knowledge about data analysis in R to imperfect real-world data Predict the future with reasonably simple algorithms Understand key data visualization and predictive analytic skills using R Understand the language of models and the predictive modeling process In Detail Predictive analytics is a field that uses data to build models that predict a future outcome of interest. It can be applied to a range of business strategies and has been a key player in search advertising and recommendation engines. The power and domain-specificity of R allows the user to express complex analytics easily, quickly, and succinctly. R offers a free and open source environment that is perfect for both learning and deploying predictive modeling solutions in the real world. This Learning Path will provide you with all the steps you need to master the art of predictive modeling with R. We start with an introduction to data analysis with R, and then gradually you'll get your feet wet with predictive modeling. You will get to grips with the fundamentals of applied statistics and build on this knowledge to perform sophisticated and powerful analytics. You will be able to solve the difficulties relating to performing data analysis in practice and find solutions to working with “messy data”, large data, communicating results, and facilitating reproducibility. You will then perform key predictive analytics tasks using R, such as train and test predictive models for classification and regression tasks, score new data sets and so on. By the end of this Learning Path, you will have explored and tested the most popular modeling techniques in use on real-world data sets and mastered a diverse range of techniques in predictive analytics. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Data Analysis with R, Tony Fischetti Learning Predictive Analytics with R, Eric Mayor Mastering Predictive Analytics with R, Rui Miguel Forte Style and approach Learn data analysis using engaging examples and fun exercises, and with a gentle and friendly but comprehensive "learn-by-doing" approach. This is a practical course, which analyzes compelling data about life, health, and death with the help of tutorials. It offers you a useful way of interpreting the data that's specific to this course, but that can also be applied to any other data. This course is designed to be both a guide and a reference for moving beyond the basics of predictive modeling.

Download or read book Enterprise Data Workflows with Cascading written by Paco Nathan and published by "O'Reilly Media, Inc.". This book was released on 2013-07-11 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is an easier way to build Hadoop applications. With this hands-on book, you’ll learn how to use Cascading, the open source abstraction framework for Hadoop that lets you easily create and manage powerful enterprise-grade data processing applications—without having to learn the intricacies of MapReduce. Working with sample apps based on Java and other JVM languages, you’ll quickly learn Cascading’s streamlined approach to data processing, data filtering, and workflow optimization. This book demonstrates how this framework can help your business extract meaningful information from large amounts of distributed data. Start working on Cascading example projects right away Model and analyze unstructured data in any format, from any source Build and test applications with familiar constructs and reusable components Work with the Scalding and Cascalog Domain-Specific Languages Easily deploy applications to Hadoop, regardless of cluster location or data size Build workflows that integrate several big data frameworks and processes Explore common use cases for Cascading, including features and tools that support them Examine a case study that uses a dataset from the Open Data Initiative

Download or read book Fundamentals of Stream Processing written by Henrique C. M. Andrade and published by Cambridge University Press. This book was released on 2014-02-13 with total page 559 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stream processing is a novel distributed computing paradigm that supports the gathering, processing and analysis of high-volume, heterogeneous, continuous data streams, to extract insights and actionable results in real time. This comprehensive, hands-on guide combining the fundamental building blocks and emerging research in stream processing is ideal for application designers, system builders, analytic developers, as well as students and researchers in the field. This book introduces the key components of the stream computing paradigm, including the distributed system infrastructure, the programming model, design patterns and streaming analytics. The explanation of the underlying theoretical principles, illustrative examples and implementations using the IBM InfoSphere Streams SPL language and real-world case studies provide students and practitioners with a comprehensive understanding of such applications and the middleware that supports them.

Download or read book Learning Analytics written by Johann Ari Larusson and published by Springer. This book was released on 2014-07-04 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt: In education today, technology alone doesn't always lead to immediate success for students or institutions. In order to gauge the efficacy of educational technology, we need ways to measure the efficacy of educational practices in their own right. Through a better understanding of how learning takes place, we may work toward establishing best practices for students, educators, and institutions. These goals can be accomplished with learning analytics. Learning Analytics: From Research to Practice updates this emerging field with the latest in theories, findings, strategies, and tools from across education and technological disciplines. Guiding readers through preparation, design, and examples of implementation, this pioneering reference clarifies LA methods as not mere data collection but sophisticated, systems-based analysis with practical applicability inside the classroom and in the larger world. Case studies illustrate applications of LA throughout academic settings (e.g., intervention, advisement, technology design), and their resulting impact on pedagogy and learning. The goal is to bring greater efficiency and deeper engagement to individual students, learning communities, and educators, as chapters show diverse uses of learning analytics to: Enhance student and faculty performance. Improve student understanding of course material. Assess and attend to the needs of struggling learners. Improve accuracy in grading. Allow instructors to assess and develop their own strengths. Encourage more efficient use of resources at the institutional level. Researchers and practitioners in educational technology, IT, and the learning sciences will hail the information in Learning Analytics: From Research to Practice as a springboard to new levels of student, instructor, and institutional success.

Download or read book Pmml Second Edition written by Gerardus Blokdyk and published by 5starcooks. This book was released on 2019-02-26 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Has the PMML work been fairly and/or equitably divided and delegated among team members who are qualified and capable to perform the work? Has everyone contributed? At what point will vulnerability assessments be performed once PMML is put into production (e.g., ongoing Risk Management after implementation)? How can you negotiate PMML successfully with a stubborn boss, an irate client, or a deceitful coworker? Are there any constraints known that bear on the ability to perform PMML work? How is the team addressing them? Will PMML have an impact on current business continuity, disaster recovery processes and/or infrastructure? This powerful PMML self-assessment will make you the assured PMML domain assessor by revealing just what you need to know to be fluent and ready for any PMML challenge. How do I reduce the effort in the PMML work to be done to get problems solved? How can I ensure that plans of action include every PMML task and that every PMML outcome is in place? How will I save time investigating strategic and tactical options and ensuring PMML costs are low? How can I deliver tailored PMML advice instantly with structured going-forward plans? There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all PMML essentials are covered, from every angle: the PMML self-assessment shows succinctly and clearly that what needs to be clarified to organize the required activities and processes so that PMML outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced PMML practitioners. Their mastery, combined with the easy elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in PMML are maximized with professional results. Your purchase includes access details to the PMML self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows you exactly what to do next. Your exclusive instant access details can be found in your book. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific PMML Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.

Download or read book Learning Predictive Analytics with R written by Eric Mayor and published by Packt Publishing Ltd. This book was released on 2015-09-24 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get to grips with key data visualization and predictive analytic skills using R About This Book Acquire predictive analytic skills using various tools of R Make predictions about future events by discovering valuable information from data using R Comprehensible guidelines that focus on predictive model design with real-world data Who This Book Is For If you are a statistician, chief information officer, data scientist, ML engineer, ML practitioner, quantitative analyst, and student of machine learning, this is the book for you. You should have basic knowledge of the use of R. Readers without previous experience of programming in R will also be able to use the tools in the book. What You Will Learn Customize R by installing and loading new packages Explore the structure of data using clustering algorithms Turn unstructured text into ordered data, and acquire knowledge from the data Classify your observations using Naive Bayes, k-NN, and decision trees Reduce the dimensionality of your data using principal component analysis Discover association rules using Apriori Understand how statistical distributions can help retrieve information from data using correlations, linear regression, and multilevel regression Use PMML to deploy the models generated in R In Detail R is statistical software that is used for data analysis. There are two main types of learning from data: unsupervised learning, where the structure of data is extracted automatically; and supervised learning, where a labeled part of the data is used to learn the relationship or scores in a target attribute. As important information is often hidden in a lot of data, R helps to extract that information with its many standard and cutting-edge statistical functions. This book is packed with easy-to-follow guidelines that explain the workings of the many key data mining tools of R, which are used to discover knowledge from your data. You will learn how to perform key predictive analytics tasks using R, such as train and test predictive models for classification and regression tasks, score new data sets and so on. All chapters will guide you in acquiring the skills in a practical way. Most chapters also include a theoretical introduction that will sharpen your understanding of the subject matter and invite you to go further. The book familiarizes you with the most common data mining tools of R, such as k-means, hierarchical regression, linear regression, association rules, principal component analysis, multilevel modeling, k-NN, Naive Bayes, decision trees, and text mining. It also provides a description of visualization techniques using the basic visualization tools of R as well as lattice for visualizing patterns in data organized in groups. This book is invaluable for anyone fascinated by the data mining opportunities offered by GNU R and its packages. Style and approach This is a practical book, which analyzes compelling data about life, health, and death with the help of tutorials. It offers you a useful way of interpreting the data that's specific to this book, but that can also be applied to any other data.

Download or read book Wikibook of Health Informatics written by and published by PediaPress. This book was released on with total page 661 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Journeys to Data Mining written by Mohamed Medhat Gaber and published by Springer Science & Business Media. This book was released on 2012-07-20 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining, an interdisciplinary field combining methods from artificial intelligence, machine learning, statistics and database systems, has grown tremendously over the last 20 years and produced core results for applications like business intelligence, spatio-temporal data analysis, bioinformatics, and stream data processing. The fifteen contributors to this volume are successful and well-known data mining scientists and professionals. Although by no means an exhaustive list, all of them have helped the field to gain the reputation and importance it enjoys today, through the many valuable contributions they have made. Mohamed Medhat Gaber has asked them (and many others) to write down their journeys through the data mining field, trying to answer the following questions: 1. What are your motives for conducting research in the data mining field? 2. Describe the milestones of your research in this field. 3. What are your notable success stories? 4. How did you learn from your failures? 5. Have you encountered unexpected results? 6. What are the current research issues and challenges in your area? 7. Describe your research tools and techniques. 8. How would you advise a young researcher to make an impact? 9. What do you predict for the next two years in your area? 10. What are your expectations in the long term? In order to maintain the informal character of their contributions, they were given complete freedom as to how to organize their answers. This narrative presentation style provides PhD students and novices who are eager to find their way to successful research in data mining with valuable insights into career planning. In addition, everyone else interested in the history of computer science may be surprised about the stunning successes and possible failures computer science careers (still) have to offer.

Download or read book Machine Learning and Data Mining in Pattern Recognition written by Petra Perner and published by Springer Science & Business Media. This book was released on 2009-07-21 with total page 837 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is no royal road to science, and only those who do not dread the fatiguing climb of its steep paths have a chance of gaining its luminous summits. Karl Marx A Universial Genius of the 19th Century Many scientists from all over the world during the past two years since the MLDM 2007 have come along on the stony way to the sunny summit of science and have worked hard on new ideas and applications in the area of data mining in pattern r- ognition. Our thanks go to all those who took part in this year's MLDM. We appre- ate their submissions and the ideas shared with the Program Committee. We received over 205 submissions from all over the world to the International Conference on - chine Learning and Data Mining, MLDM 2009. The Program Committee carefully selected the best papers for this year’s program and gave detailed comments on each submitted paper. There were 63 papers selected for oral presentation and 17 papers for poster presentation. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data-mining methods for the different multimedia data types such as image mining, text mining, video mining and Web mining. Among these topics this year were special contributions to subtopics such as attribute discre- zation and data preparation, novelty and outlier detection, and distances and simila- ties.

Download or read book Data Mining with Rattle and R written by Graham Williams and published by Springer Science & Business Media. This book was released on 2011-08-04 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining is the art and science of intelligent data analysis. By building knowledge from information, data mining adds considerable value to the ever increasing stores of electronic data that abound today. In performing data mining many decisions need to be made regarding the choice of methodology, the choice of data, the choice of tools, and the choice of algorithms. Throughout this book the reader is introduced to the basic concepts and some of the more popular algorithms of data mining. With a focus on the hands-on end-to-end process for data mining, Williams guides the reader through various capabilities of the easy to use, free, and open source Rattle Data Mining Software built on the sophisticated R Statistical Software. The focus on doing data mining rather than just reading about data mining is refreshing. The book covers data understanding, data preparation, data refinement, model building, model evaluation, and practical deployment. The reader will learn to rapidly deliver a data mining project using software easily installed for free from the Internet. Coupling Rattle with R delivers a very sophisticated data mining environment with all the power, and more, of the many commercial offerings.

Download or read book Optimization and Decision Science Methodologies and Applications written by Antonio Sforza and published by Springer. This book was released on 2017-11-03 with total page 607 pages. Available in PDF, EPUB and Kindle. Book excerpt: This proceedings volume highlights the state-of-the-art knowledge related to optimization, decisions science and problem solving methods, as well as their application in industrial and territorial systems. It includes contributions tackling these themes using models and methods based on continuous and discrete optimization, network optimization, simulation and system dynamics, heuristics, metaheuristics, artificial intelligence, analytics, and also multiple-criteria decision making. The number and the increasing size of the problems arising in real life require mathematical models and solution methods adequate to their complexity. There has also been increasing research interest in Big Data and related challenges. These challenges can be recognized in many fields and systems which have a significant impact on our way of living: design, management and control of industrial production of goods and services; transportation planning and traffic management in urban and regional areas; energy production and exploitation; natural resources and environment protection; homeland security and critical infrastructure protection; development of advanced information and communication technologies. The chapters in this book examine how to deal with new and emerging practical problems arising in these different fields through the presented methodologies and their applications. The chapter topics are applicable for researchers and practitioners working in these areas, but also for the operations research community. The contributions were presented during the international conference “Optimization and Decision Science” (ODS2017), held at Hilton Sorrento Palace Conference Center, Sorrento, Italy, September 4 – 7, 2017. ODS 2017, was organized by AIRO, Italian Operations Research Society, in cooperation with DIETI (Department of Electrical Engineering and Information Technology) of University “Federico II” of Naples.

Download or read book Semantic Web Rules written by Mike Dean and published by Springer. This book was released on 2010-10-05 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the International RuleML Symposium on Rule Interchange and Applications, RuleML 2010, held in Washington, DC, USA, in October 2010 - collocated with the 13th International Business Rules Forum Conference 2010. The 14 revised full papers and 7 revised short papers presented together with the abstracts of 3 keynote lectures were carefully reviewed and selected from 42 submissions. The accepted papers address a wide range of rule topics, including traditional topics, such as rules and uncertainty, rule-based event processing and reaction rules, rules and inferencing, rule transformation and extraction, rules, semantic technology, and cross-industry standards, rules and norms, rule-based distributed/multi-agent systems, and miscellaneous rule topics.

Download or read book Global Business Analytics Models written by Hokey Min and published by FT Press. This book was released on 2016-03-05 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: THE COMPLETE GUIDE TO USING ANALYTICS TO MANAGE RISK AND UNCERTAINTY IN COMPLEX GLOBAL BUSINESS ENVIRONMENTS Practical techniques for developing reliable, actionable intelligence–and using it to craft strategy Analytical opportunities to solve key managerial problems in global enterprises Written for working managers: packed with realistic, useful examples This guide helps global managers use modern analytics to gain reliable, actionable, and timely business intelligence–and use it to manage risk, build winning strategies, and solve urgent problems. Dr. Hokey Min offers a practical, easy-to-understand overview of business analytics in a global context, focusing especially on managerial and strategic implications. After demystifying today’s core quantitative tools, he demonstrates them at work in a wide spectrum of global applications. You’ll build models to help segment global markets, forecast demand, assess risk, plan financing, optimize supply chains, and more. Along the way, you’ll find practical guidance for developing analytic thinking, operationalizing Big Data in global environments, and preparing for future analytical innovations. Whether you’re a global executive, strategist, analyst, marketer, supply chain professional, student or researcher, this book will help you drive real value from analytics–in smarter decisions, improved strategy, and better management. In today’s global business environments characterized by growing complexity, volatility, and uncertainty, business analytics has become an indispensable tool for managing these challenges. Specifically, global managers need analytics expertise to solve problems, identify opportunities, shape strategy, mitigate risk, and improve their day-to-day operational efficiency. Now, for the first time, there’s an analytics guide designed specifically for decision-makers in global organizations. Leveraging his experience teaching a number of students and training hundreds of managers and executives, Dr. Hokey Min demystifies the principles and tools of modern business analytics, and demonstrates their real-world use in global business. First, Dr. Min identifies key success factors and mindsets, helping you establish the preconditions for effective analysis. Next, he walks you through the practicalities of collecting, organizing, and analyzing Big Data, and developing models to transform them into actionable insight. Building on these foundations, he illustrates core analytical applications in finance, healthcare, and global supply chains. He concludes by previewing emerging trends in analytics, including the newest tools for automated decision-making. Compare today’s key quantitative tools Stats, data mining, OR, and simulation: how they work, when to use them Get the right data... ...and get the data right Predict the future... ...and sense its arrival sooner than others can

Download or read book E agriculture in action written by Food and Agriculture Organization of the United Nations and published by Food & Agriculture Org.. This book was released on 2019-07-15 with total page 96 pages. Available in PDF, EPUB and Kindle. Book excerpt: According to Forbes, we generate almost 2.5 quintillion bytes of data every day. The next generation of agriculture heavily depends on data. The ability to capture, sort, analyze and extract actionable intelligence from large data sets to reveal patterns (human, climate, market) and related trends is an important emerging field. The increase in the use of Internet of Things (IoT) devices would only add to this data deluge. The Economist rightly called data as the world’s most valuable resource , while some calling data the new oil . Agriculture would be one of the major users of IoTs. How can individuals, organizations and governments build capacities and processes in place to take advantage of this huge influx of data. This coupled with existing data streams (weather, satellite imagery, markets etc.,) would create an ecosystem which if managed efficiently would provide rich dividents especially in the agriculture sector where the right information at the right time will make a great influence in the livelihoods of people involved in agriculture and allied activities. This publication looks at how various initiatives are leveraging data, related to agriculture value chains, to influence decision making and efficient service delivery together with addressing key building blocks such as interoperability, data sharing, data security and the necessary policies and regulations that are needed to be implemented to sustain the data ecosystem.