Step-by-step guidance for implementing an effective statewide longitudinal data system Every U.S. state faces challenges in its efforts to ensure the highest-quality education for students. To address these challenges, a growing number of states are establishing statewide longitudinal data systems (SLDSs), a data-rich system integrating relevant data about a student's education. Implementing Statewide Longitudinal Data Systems for Education presents a detailed and contextualized discussion of SLDSs, which will serve as a recipe for states that want to implement an SLDS, develop design and enactment of new and existing SLDS systems, addressing implementation, operation and optimization. Provides a contextualized discussion of the history and purpose of SLDSs Describes how to plan for and implement an SLDS, including best practices regarding data governance, standards and privacy Discusses proven methods of data management, and details the two most popular methods of database architectures used for SLDSs Provides 5 case studies of states successfully using SLDSs Offers suggestions for expansion and inclusion of new datasets over time This essential book addresses the culture of data concept, providing a guide for states to usher in a new era in their education system where data is invaluable and used by everyone, not simply the newest version of the old system. A robust LDS initiative includes linked student records, teacher records, test scores, course selection, finances, certifications, licensure, salary and more. Concluding with a discussion of the potential future uses of SLDS, this book is the ultimate guide to SLDS implementation and understanding.

A better development and implementation framework for credit risk scorecards Intelligent Credit Scoring presents a business-oriented process for the development and implementation of risk prediction scorecards. The credit scorecard is a powerful tool for measuring the risk of individual borrowers, gauging overall risk exposure and developing analytically driven, risk-adjusted strategies for existing customers. In the past 10 years, hundreds of banks worldwide have brought the process of developing credit scoring models in-house, while ‘credit scores' have become a frequent topic of conversation in many countries where bureau scores are used broadly. In the United States, the ‘FICO' and ‘Vantage' scores continue to be discussed by borrowers hoping to get a better deal from the banks. While knowledge of the statistical processes around building credit scorecards is common, the business context and intelligence that allows you to build better, more robust, and ultimately more intelligent, scorecards is not. As the follow-up to Credit Risk Scorecards, this updated second edition includes new detailed examples, new real-world stories, new diagrams, deeper discussion on topics including WOE curves, the latest trends that expand scorecard functionality and new in-depth analyses in every chapter. Expanded coverage includes new chapters on defining infrastructure for in-house credit scoring, validation, governance, and Big Data. Black box scorecard development by isolated teams has resulted in statistically valid, but operationally unacceptable models at times. This book shows you how various personas in a financial institution can work together to create more intelligent scorecards, to avoid disasters, and facilitate better decision making. Key items discussed include: Following a clear step by step framework for development, implementation, and beyond Lots of real life tips and hints on how to detect and fix data issues How to realise bigger ROI from credit scoring using internal resources Explore new trends and advances to get more out of the scorecard Credit scoring is now a very common tool used by banks, Telcos, and others around the world for loan origination, decisioning, credit limit management, collections management, cross selling, and many other decisions. Intelligent Credit Scoring helps you organise resources, streamline processes, and build more intelligent scorecards that will help achieve better results.

Explore the game-changing technology that allows mobile learning to effectively reach K-12 students Mobile Learning: A Handbook for Developers, Educators and Learners provides research-based foundations for developing, evaluating, and integrating effective mobile learning pedagogy. Twenty-first century students require twenty-first century technology, and mobile devices provide new and effective ways to educate children. But with new technologies come new challenges—therefore, this handbook presents a comprehensive look at mobile learning by synthesizing relevant theories and drawing practical conclusions for developers, educators, and students. Mobile devices—in ways that the laptop, the personal computer, and netbook computers have not—present the opportunity to make learning more engaging, interactive, and available in both traditional classroom settings and informal learning environments. From theory to practice, Mobile Learning explores how mobile devices are different than their technological predecessors, makes the case for developers, teachers, and parents to invest in the technology, and illustrates the many ways in which it is innovative, exciting, and effective in educating K-12 students. Explores how mobile devices can support the needs of students Provides examples, screenshots, graphics, and visualizations to enhance the material presented in the book Provides developers with the background necessary to create the apps their audience requires Presents the case for mobile learning in and out of classrooms as early as preschool Discusses how mobile learning enables better educational opportunities for the visually impaired, students with Autism, and adult learners. If you're a school administrator, teacher, app developer, or parent, this topical book provides a theoretical, well-researched discussion of the pedagogical theory and mobile learning, as well as practical advice in setting up a mobile learning strategy.

Raise the skill and competency level of project finance organizations Project Finance for Business Development helps readers understand how to develop a competitive advantage through project finance. Most importantly, it shows how different elements of project finance, such as opportunity screening and evaluation, project development, risk management, and due diligence come together to structure viable and financeable projects—which are crucial pieces missing from the current literature. Eliminating misconceptions about what is really important for successful project financings, this book shows you how to develop, structure, and implement projects successfully by creating competitive advantage. By shedding light on project finance failures, it also helps you avoid failures of your own. • Offers a roadmap for successful financing, participant roles and responsibilities, and assessing and testing project viability • Considers project finance from a broad business development and competitive advantage • Provides a strategic decision-forecasting perspective • Delves deeper than existing treatments of project finance into decisions needed to create and implement effective financing plans Helping readers develop, structure, and implement projects successfully by creating competitive advantage, this book is a useful tool for project sponsors and developers, helping them structure and implement projects by creating competitive advantage.

Maximize profit and optimize decisions with advanced business analytics Profit-Driven Business Analytics provides actionable guidance on optimizing the use of data to add value and drive better business. Combining theoretical and technical insights into daily operations and long-term strategy, this book acts as a development manual for practitioners seeking to conceive, develop, and manage advanced analytical models. Detailed discussion delves into the wide range of analytical approaches and modeling techniques that can help maximize business payoff, and the author team draws upon their recent research to share deep insight about optimal strategy. Real-life case studies and examples illustrate these techniques at work, and provide clear guidance for implementation in your own organization. From step-by-step instruction on data handling, to analytical fine-tuning, to evaluating results, this guide provides invaluable guidance for practitioners seeking to reap the advantages of true business analytics. Despite widespread discussion surrounding the value of data in decision making, few businesses have adopted advanced analytic techniques in any meaningful way. This book shows you how to delve deeper into the data and discover what it can do for your business. Reinforce basic analytics to maximize profits Adopt the tools and techniques of successful integration Implement more advanced analytics with a value-centric approach Fine-tune analytical information to optimize business decisions Both data stored and streamed has been increasing at an exponential rate, and failing to use it to the fullest advantage equates to leaving money on the table. From bolstering current efforts to implementing a full-scale analytics initiative, the vast majority of businesses will see greater profit by applying advanced methods. Profit-Driven Business Analytics provides a practical guidebook and reference for adopting real business analytics techniques.

It’s time to get your head in the cloud! In today’s business environment, more and more people are requesting cloud-based solutions to help solve their business challenges. So how can you not only anticipate your clients’ needs but also keep ahead of the curve to ensure their goals stay on track? With the help of this accessible book, you’ll get a clear sense of cloud computing and understand how to communicate the benefits, drawbacks, and options to your clients so they can make the best choices for their unique needs. Plus, case studies give you the opportunity to relate real-life examples of how the latest technologies are giving organizations worldwide the opportunity to thrive as supply chain solutions in the cloud. Demonstrates how improvements in forecasting, collaboration, and inventory optimization can lead to cost savings Explores why cloud computing is becoming increasingly important Takes a close look at the types of cloud computing Makes sense of demand-driven forecasting using Amazon's cloud Whether you work in management, business, or IT, this is the dog-eared reference you’ll want to keep close by as you continue making sense of the cloud.

An essential guide to healthcare data problems, sources, and solutions Strategies in Biomedical Data Science provides medical professionals with much-needed guidance toward managing the increasing deluge of healthcare data. Beginning with a look at our current top-down methodologies, this book demonstrates the ways in which both technological development and more effective use of current resources can better serve both patient and payer. The discussion explores the aggregation of disparate data sources, current analytics and toolsets, the growing necessity of smart bioinformatics, and more as data science and biomedical science grow increasingly intertwined. You'll dig into the unknown challenges that come along with every advance, and explore the ways in which healthcare data management and technology will inform medicine, politics, and research in the not-so-distant future. Real-world use cases and clear examples are featured throughout, and coverage of data sources, problems, and potential mitigations provides necessary insight for forward-looking healthcare professionals. Big Data has been a topic of discussion for some time, with much attention focused on problems and management issues surrounding truly staggering amounts of data. This book offers a lifeline through the tsunami of healthcare data, to help the medical community turn their data management problem into a solution. Consider the data challenges personalized medicine entails Explore the available advanced analytic resources and tools Learn how bioinformatics as a service is quickly becoming reality Examine the future of IOT and the deluge of personal device data The sheer amount of healthcare data being generated will only increase as both biomedical research and clinical practice trend toward individualized, patient-specific care. Strategies in Biomedical Data Science provides expert insight into the kind of robust data management that is becoming increasingly critical as healthcare evolves.

Real-life examples of how to apply intelligence in the healthcare industry through innovative analytics Healthcare analytics offers intelligence for making better healthcare decisions. Identifying patterns and correlations contained in complex health data, analytics has applications in hospital management, patient records, diagnosis, operating and treatment costs, and more. Helping healthcare managers operate more efficiently and effectively. Transforming Healthcare Analytics: The Quest for Healthy Intelligence shares real-world use cases of a healthcare company that leverages people, process, and advanced analytics technology to deliver exemplary results. This book illustrates how healthcare professionals can transform the healthcare industry through analytics. Practical examples of modern techniques and technology show how unified analytics with data management can deliver insight-driven decisions. The authors—a data management and analytics specialist and a healthcare finance executive—share their unique perspectives on modernizing data and analytics platforms to alleviate the complexity of the healthcare, distributing capabilities and analytics to key stakeholders, equipping healthcare organizations with intelligence to prepare for the future, and more. This book: Explores innovative technologies to overcome data complexity in healthcare Highlights how analytics can help with healthcare market analysis to gain competitive advantage Provides strategies for building a strong foundation for healthcare intelligence Examines managing data and analytics from end-to-end, from diagnosis, to treatment, to provider payment Discusses the future of technology and focus areas in the healthcare industry Transforming Healthcare Analytics: The Quest for Healthy Intelligence is an important source of information for CFO’s, CIO, CTO, healthcare managers, data scientists, statisticians, and financial analysts at healthcare institutions.

Reality-based modeling for today's unique economic recovery Economic Modeling in the Post Great Recession Era presents a more realistic approach to modeling, using direct statistical applications to address the characteristics and trends central to current market behaviors. This book's unique focus on the reality of today's markets makes it an invaluable resource for students and practitioners seeking a comprehensive guide to more accurate forecasting. While most books treat the economy as if it were in a vacuum, building models around idealized or perception-biased behaviors, this book deals with the economy as it currently stands—in a state of recovery, limited by financial constraints, imperfect information, and lags and disparities in price movements. The authors identify how these characteristics impact various markets' behaviors, and quantify those behaviors using SAS as the primary statistical tool. Today's economy bears a number of unique attributes that usual modeling methods fail to consider. This book describes how to approach modeling based on real-world, observable data in order to make better-informed decisions in today's markets. Discover the three economic characteristics with the greatest impact on various markets Create economic models that mirror the current post-recession reality Adopt statistical methods that identify and adapt to structural breaks and lags Factor real-world imperfections into modeling for more accurate forecasting The past few years have shown a clear demarcation between policymakers' forecasts and actual outcomes. As the dust settles on the Great Recession, after-effects linger—and impact our current recovery in ways that diverge from past experience and theoretical expectations. Economic Modeling in the Post Great Recession Era provides comprehensive guidance grounded in reality for today's economic decision-makers.

Go beyond technique to master the difficult judgement calls of forecasting A variety of software can be used effectively to achieve accurate forecasting, but no software can replace the essential human component. You may be new to forecasting, or you may have mastered the statistical theory behind the software’s predictions, and even more advanced “power user” techniques for the software itself—but your forecasts will never reach peak accuracy unless you master the complex judgement calls that the software cannot make. Profit From Your Forecasting Software addresses the issues that arise regularly, and shows you how to make the correct decisions to get the most out of your software. Taking a non-mathematical approach to the various forecasting models, the discussion covers common everyday decisions such as model choice, forecast adjustment, product hierarchies, safety stock levels, model fit, testing, and much more. Clear explanations help you better understand seasonal indices, smoothing coefficients, mean absolute percentage error, and r-squared, and an exploration of psychological biases provides insight into the decision to override the software’s forecast. With a focus on choice, interpretation, and judgement, this book goes beyond the technical manuals to help you truly grasp the more intangible skills that lead to better accuracy. Explore the advantages and disadvantages of alternative forecasting methods in different situations Master the interpretation and evaluation of your software’s output Learn the subconscious biases that could affect your judgement toward intervention Find expert guidance on testing, planning, and configuration to help you get the most out of your software Relevant to sales forecasters, demand planners, and analysts across industries, Profit From Your Forecasting Software is the much sought-after “missing piece” in forecasting reference.