Business Intelligence with SQL Server Reporting Services helps you deliver business intelligence with panache. Harness the power of the Reporting Services toolkit to combine charts, gauges, sparklines, indicators, and maps into compelling dashboards and scorecards. Create compelling visualizations that seize your audience’s attention and help business users identify and react swiftly to changing business conditions. Best of all, you'll do all these things by creating new value from software that is already installed and paid for – SQL Server and the included SQL Server Reporting Services. Businesses run on numbers, and good business intelligence systems make the critical numbers immediately and conveniently accessible. Business users want access to key performance indicators in the office, at the beach, and while riding the subway home after a day's work. Business Intelligence with SQL Server Reporting Services helps you meet these need for anywhere/anytime access by including chapters specifically showing how to deliver on modern devices such as smart phones and tablets. You'll learn to deliver the same information, with similar look-and-feel, across the entire range of devices used in business today. Key performance indicators give fast notification of business unit performance Polished dashboards deliver essential metrics and strategic comparisons Visually arresting output on multiple devices focuses attention

Discover how data science can help you gain in-depth insight into your business - the easy way! Jobs in data science abound, but few people have the data science skills needed to fill these increasingly important roles in organizations. Data Science For Dummies is the perfect starting point for IT professionals and students interested in making sense of their organization's massive data sets and applying their findings to real-world business scenarios. From uncovering rich data sources to managing large amounts of data within hardware and software limitations, ensuring consistency in reporting, merging various data sources, and beyond, you'll develop the know-how you need to effectively interpret data and tell a story that can be understood by anyone in your organization. Provides a background in data science fundamentals before moving on to working with relational databases and unstructured data and preparing your data for analysis Details different data visualization techniques that can be used to showcase and summarize your data Explains both supervised and unsupervised machine learning, including regression, model validation, and clustering techniques Includes coverage of big data processing tools like MapReduce, Hadoop, Dremel, Storm, and Spark It's a big, big data world out there - let Data Science For Dummies help you harness its power and gain a competitive edge for your organization.

Scientific progress depends on good research, and good research needs good statistics. But statistical analysis is tricky to get right, even for the best and brightest of us. You'd be surprised how many scientists are doing it wrong. Statistics Done Wrong is a pithy, essential guide to statistical blunders in modern science that will show you how to keep your research blunder-free. You'll examine embarrassing errors and omissions in recent research, learn about the misconceptions and scientific politics that allow these mistakes to happen, and begin your quest to reform the way you and your peers do statistics. You'll find advice on: Asking the right question, designing the right experiment, choosing the right statistical analysis, and sticking to the plan How to think about p values, significance, insignificance, confidence intervals, and regression Choosing the right sample size and avoiding false positives Reporting your analysis and publishing your data and source code Procedures to follow, precautions to take, and analytical software that can help Scientists: Read this concise, powerful guide to help you produce statistically sound research. Statisticians: Give this book to everyone you know. The first step toward statistics done right is Statistics Done Wrong.

The book gives a systematical presentation of stochastic approximation methods for discrete time Markov price processes. Advanced methods combining backward recurrence algorithms for computing of option rewards and general results on convergence of stochastic space skeleton and tree approximations for option rewards are applied to a variety of models of multivariate modulated Markov price processes. The principal novelty of presented results is based on consideration of multivariate modulated Markov price processes and general pay-off functions, which can depend not only on price but also an additional stochastic modulating index component, and use of minimal conditions of smoothness for transition probabilities and pay-off functions, compactness conditions for log-price processes and rate of growth conditions for pay-off functions. The volume presents results on structural studies of optimal stopping domains, Monte Carlo based approximation reward algorithms, and convergence of American-type options for autoregressive and continuous time models, as well as results of the corresponding experimental studies.

Discovering JMP 12 provides a basic introduction to using JMP. For new users of JMP, this is a great place to start. The book also includes details about importing your data into JMP, analyzing the data, and sharing the results.

JMP 12 Basic Analysis covers the initial types of analyses that you often perform in JMP, such as univariate, bivariate, and oneway analyses. Creating tables of summary statistics with the Tabulate platform is included along with approximating sampling distributions using bootstrapping. Find information about how to clean up your data before performing analyses.

JMP 12 Consumer Research focuses on analyses that help users observe and predict subject's behavior, particularly those in the market research field. The Uplift platform predicts consumer behavior based on shifts in marketing efforts. Learn how to tabulate and summarize categorical responses with the Categorical platform. Factor Analysis rotates principal components to help identify which directions have the most variation among the variables. The book also covers Item Analysis, a method for identifying latent traits that might affect an individual's choices. And read about the Choice platform, which market researchers use to estimate probability in consumer spending.

JMP 12 Design of Experiments Guide covers classic DOE designs (for example, full factorial, response surface, and mixture designs). Read about more flexible custom designs, which you generate to fit your particular experimental situation. Discover JMP’s definitive screening designs, an efficient way to identify important factor interactions using fewer runs than required by traditional designs. And read about creating designs that test systems where failures occur as a result of interactions among components or subsystems. The book also provides guidance on determining an appropriate sample size for your study.

Start with JMP 12 Essential Graphing to find the ideal graph for your data. The book begins with Graph Builder, a quick way to create graphs in a drag-and-drop window. Line charts, ellipses, box plots, and maps are just a few of the graphs available in Graph Builder. Find information about creating other types of plots: bubble plots, scatterplots, parallel plots, and more.

JMP 12 Fitting Linear Models focuses on the Fit Model platform and many of its personalities. Linear and logistic regression, analysis of variance and covariance, and stepwise procedures are covered. Also included are multivariate analysis of variance, mixed models, generalized models, and models based on penalized regression techniques.

The JMP 12 JSL Syntax Reference focuses on functions and their arguments, and messages that you send to objects and display boxes. Notes and examples are included.

JMP 12 Multivariate Methods describes techniques for analyzing several variables simultaneously. The book covers descriptive measures, such as correlations. It also describes methods that give insight into the structure of the multivariate data, such as clustering, principal components, discriminant analysis, and partial least squares.

JMP 12 Profilers covers the family of interactive profiling tools, which enable you to view cross-sections of any response surface. The book also includes details about plotting points and surfaces in a three-dimensional graph.

JMP 12 Quality and Process Methodsfocuses on the Fit Model platform and many of its personalities. Linear and logistic regression, analysis of variance and covariance, and stepwise procedures are covered. Also included are multivariate analysis of variance, mixed models, generalized models, and models based on penalized regression techniques.

JMP 12 Reliability and Survival Methods provides details about evaluating and improving reliability in a product or system and analyzing survival data for people and products. The book explains how to fit the best distribution to your time-to-event data or analyze destruction data. A few other topics include analyzing competing causes of failure, modeling reliability as improvements are made over time, and analyzing recurring events.

Scripting Guide provides details for taking advantage of the powerful JMP Scripting Language (JSL). Learn how to write and debug scripts, manipulate data tables, construct display boxes, create JMP applications, and more.

JMP 12 Specialized Models provides details about modeling techniques such as partitioning, neural networks, nonlinear regression, and time series analysis. Topics include the Gaussian platform, which is useful in analyzing computer simulation experiments. The book also covers the Response Screening platform, which is useful in testing the effect of a predictor when you have many responses.

Using JMP 12 covers the initial types of analyses that you often perform in JMP, such as univariate, bivariate, and oneway analyses. Creating tables of summary statistics with the Tabulate platform is included along with approximating sampling distributions using bootstrapping. Find information about how to clean up your data before performing analyses.

D3.js in Action is a practical tutorial for creating interactive graphics and data-driven applications using D3.js. You'll start with in-depth explanations of D3's out-of-the-box layouts, along with dozens of practical use cases that align with different types of visualizations. Then, you'll explore practical techniques for content creation, animation, and representing dynamic data—including interactive graphics and data streamed live over the web. The final chapters show you how to use D3's rich interaction model as the foundation for a complete web application. In the end, you'll be ready to integrate D3.js into your web development process and transform any site into a more engaging and sophisticated user experience. About the Technology D3.js is a JavaScript library that allows data to be represented graphically on a web page. Because it uses the broadly supported SVG standard, D3 allows you to create scalable graphs for any modern browser. You start with a structure, dataset, or algorithm and programmatically generate static, interactive, or animated images that responsively scale to any screen. About the Book D3.js in Action introduces you to the most powerful web data visualization library available and shows you how to use it to build interactive graphics and data-driven applications. You'll start with dozens of practical use cases that align with different types of charts, networks, and maps using D3's out-of-the-box layouts. Then, you'll explore practical techniques for content design, animation, and representation of dynamic data—including interactive graphics and live streaming data. What's Inside Interacting with vector graphics Expressive data visualization Creating rich mapping applications Prepping your data Complete data-driven web apps in D3 About the Reader Readers need basic HTML, CSS, and JavaScript skills. No experience with D3 or SVG is required. About the Author Elijah Meeks is a senior data visualization engineer at Netflix. His D3.js portfolio includes work at Stanford University and with well-known companies worldwide. Quotes A mandatory introduction to a very complex and powerful library. - Stephen Wakely, Thomson Reuters Quickly gets you coding amazing visualizations. - Ntino Krampis, PhD, City University of New York A remarkable exploration of the world of dataviz possibilities with D3. - Arun Noronha, Directworks Inc. A must-have book. - Arif Shaikh, Sony Pictures Entertainment One of the most comprehensive books about data visualization I have ever read. - Andrea Mostosi, The Fool s.r.l.

TIBCO Spotfire: A Comprehensive Primer is the go-to guide for mastering TIBCO Spotfire, a leading data visualization and analytics tool. Whether you are new to Spotfire or data visualization in general, this book will provide you with a solid foundation to create impactful and actionable visual insights. What this Book will help me do Understand the fundamentals of TIBCO Spotfire and its application in data analytics. Learn how to design compelling visualizations and dashboards that convey meaningful insights. Master advanced data transformations and analysis techniques in TIBCO Spotfire. Integrate Spotfire with external data sources and scripting languages, enhancing its functionality. Optimize Spotfire's performance and usability for enterprise-level implementations. Author(s) None Phillips, an experienced analytics professional and educator, specializes in creating accessible learning materials for data science tools. With a decade of experience in the field, None has helped many organizations unlock their data potential through tools like TIBCO Spotfire. Their approach emphasizes practical understanding, making complex concepts approachable for learners of all levels. Who is it for? The book is perfect for business analysts, data scientists, and other professionals involved in data-driven decision making who want to master TIBCO Spotfire. It's designed for beginners without prior exposure to data visualization or TIBCO Spotfire, offering an accessible entry into the field. Individuals aiming to gain hands-on experience and create enterprise-grade solutions will find this book invaluable. Additionally, it serves as a reference for experienced Spotfire users looking to refine their skills.