Get a complete view of your customers and make your marketing analysis more meaningful How well do you really know your customers? Find out with the help of expert author Daniel Waisberg and Google Analytics Integrations. This unique guide takes you well beyond the basics of using Google Analytics to track metrics, showing you how to transform this simple data collection tool into a powerful, central marketing analysis platform for your organization. You'll learn how Google AdWords, AdSense, CRMs, and other data sources can be used together to deliver actionable insights about your customers and their behavior. Explains proven techniques and best practices for collecting clean and accurate information from the start Shows you how to import your organization's marketing and customer data into Google Analytics Illustrates the importance of taking a holistic view of your customers and how this knowledge can transform your business Provides step-by-step guidance on using the latest analytical tools and services to gain a complete understanding of your customers, their needs, and what motivates them to take action Google Analytics Integration is your in-depth guide to improving your data integration, behavioral analysis, and ultimately, your bottom line.

Cure for analytics insanity: the definition of insanity is doing the same thing over and over again and expecting different results. That’s what web analytics have been doing for years as data collection becomes easier and quality solutions become less expensive. Instead of focusing on your business strategy and fitting the tool to our needs, we have done the opposite; developing strategies based on what is easy to measure in our tools of choice. This session will teach us how to cure that analytics insanity by taking a strategy first approach to analytics.

A hands on guide to web scraping and text mining for both beginners and experienced users of R Introduces fundamental concepts of the main architecture of the web and databases and covers HTTP, HTML, XML, JSON, SQL. Provides basic techniques to query web documents and data sets (XPath and regular expressions). An extensive set of exercises are presented to guide the reader through each technique. Explores both supervised and unsupervised techniques as well as advanced techniques such as data scraping and text management. Case studies are featured throughout along with examples for each technique presented. R code and solutions to exercises featured in the book are provided on a supporting website.

I had the change to speak with well known Sharon Hill (@idoubtit) for the first episode of 2015. We discuss a number of interesting topics including the contributions Doubtful News makes to getting scientific and skeptical information ranked highly in search results, sink holes, why earthquakes are hard to predict, and data collection about paranormal groups via the internet.

You have installed and performed the basic customization of IBM® Tivoli® Storage Productivity Center. You have collected performance data collection and generated reports. Now it’s time to learn the best ways to use the software to manage your storage infrastructure. This IBM Redbooks® publication shows the best way to set up the software, based on your storage environment, and then how to use it to manage your infrastructure. It includes experiences from IBM clients and staff and covers the following topics: Architectural design techniques (sizing your environment, single versus multiple installations, physical versus virtual servers, deployment in a large, existing storage infrastructure) Database and server considerations (database backup and restoration methods and scripts, using IBM Data Studio Client for database administration, database placement and relocation, repository sizing and tuning, moving and migrating the server) Alerting, monitoring and reporting (monitoring thresholds and alerts, performance management and analysis of reports, real-time performance monitoring for IBM SAN Volume Controller) Security considerations (Tivoli Storage Productivity Center internal user IDs, user authentication configuration methods, how and why to set up and change passwords, configuring, querying, and testing LDAP and Microsoft Active Directory) Heath checks (server heath and logs, health and recoverability of IBM DB2® databases, using the Database Maintenance tool) Data management techniques (how to spot unusual growth incidents, scripted actions for Tivoli Storage manager and hierarchical storage management) This book is for storage administrators who are responsible for the performance and growth of the IT storage infrastructure.

Optimize Microsoft SQL Server 2014 queries and applications Microsoft SQL Server 2014 Query Tuning & Optimization is filled with ready-to-use techniques for creating high-performance queries and applications. The book describes the inner workings of the query processor so you can write better queries and provide the query processor with the quality information it needs to produce efficient execution plans. You’ll also get tips for troubleshooting underperforming queries. In-Memory OLTP (Hekaton), a key new feature of SQL Server 2014, is fully covered in this practical guide. Understand how the query optimizer works Troubleshoot queries using extended events, SQL trace, dynamic management views (DMVs), the data collector, and other tools Work with query operators for data access, joins, aggregations, parallelism, and updates Speed up queries and dramatically improve application performance by creating the right indexes Understand statistics and how to detect and fix cardinality estimation errors Maximize OLTP query performance using In-Memory OLTP (Hekaton) features, including memory-optimized tables and natively compiled stored procedures Monitor and promote plan caching and reuse to improve application performance Improve the performance of data warehouse queries using columnstore indexes Handle query processor limitations with hints and other methods

The industry standard guide, updated with new ideas and SPSS analysis techniques Designing and Conducting Survey Research: A Comprehensive Guide Fourth Edition is the industry standard resource that covers all major components of the survey process, updated to include new data analysis techniques and SPSS procedures with sample data sets online. The book offers practical, actionable guidance on constructing the instrument, administrating the process, and analyzing and reporting the results, providing extensive examples and worksheets that demonstrate the appropriate use of survey and data techniques. By clarifying complex statistical concepts and modern analysis methods, this guide enables readers to conduct a survey research project from initial focus concept to the final report. Public and nonprofit managers with survey research responsibilities need to stay up-to-date on the latest methods, techniques, and best practices for optimal data collection, analysis, and reporting. Designing and Conducting Survey Research is a complete resource, answering the "what", "why", and "how" every step of the way, and providing the latest information about technological advancements in data analysis. The updated fourth edition contains step-by-step SPSS data entry and analysis procedures, as well as SPSS examples throughout the text, using real data sets from real-world studies. Other new information includes topics like: Nonresponse error/bias Ethical concerns and special populations Cell phone samples in telephone surveys Subsample screening and complex skip patterns The fourth edition also contains new information on the growing importance of focus groups, and places a special emphasis on data quality including size and variability. Those who employ survey research methods will find that Designing and Conducting Survey Research contains all the information needed to better design, conduct, and analyze a more effective survey.

AN INTERDISCIPLINARY PERSPECTIVE TO THE EVOLUTION OF THEORY AND METHODOLOGY WITHIN COGNITIVE INTERVIEW PROCESSES Providing a comprehensive approach to cognitive interviewing in the field of survey methodology, Cognitive Interviewing Methodology delivers a clear guide that draws upon modern, cutting-edge research from a variety of fields. Each chapter begins by summarizing the prevailing paradigms that currently dominate the field of cognitive interviewing. Then underlying theoretical foundations are presented, which supplies readers with the necessary background to understand newly-evolving techniques in the field. The theories lead into developed and practiced methods by leading practitioners, researchers, and/or academics. Finally, the edited guide lays out the limitations of cognitive interviewing studies and explores the benefits of cognitive interviewing with other methodological approaches. With a primary focus on question evaluation, Cognitive Interviewing Methodology also includes: Step-by-step procedures for conducting cognitive interviewing studies, which includes the various aspects of data collection, questionnaire design, and data interpretation Newly developed tools to benefit cognitive interviewing studies as well as the field of question evaluation, such as Q-Notes, a data entry and analysis software application, and Q-Bank, an online resource that houses question evaluation studies A unique method for questionnaire designers, survey managers, and data users to analyze, present, and document survey data results from a cognitive interviewing study An excellent reference for survey researchers and practitioners in the social sciences who utilize cognitive interviewing techniques in their everyday work, Cognitive Interviewing Methodology is also a useful supplement for courses on survey methods at the upper-undergraduate and graduate-level.

The Analytics and Big Data collection offers a “greatest hits” digital compilation of ideas from world-renowned thought leader Thomas Davenport, who helped popularize the terms analytics and big data in the workplace. An agile and prolific thinker, Davenport has written or coauthored more than a dozen bestselling books. Several of these titles are offered together for the first time in this curated digital bundle, including: Big Data at Work, Competing on Analytics, Analytics at Work, and Keeping Up with the Quants. The collection also includes Davenport’s popular Harvard Business Review articles, “Data Scientist: The Sexiest Job of the 21st Century” (2012) and “Analytics 3.0” (2013). Combined, these works cover all the bases on analytics and big data: what each term means; the ramifications of each from a technical, consumer, and management perspective; and where each can have the biggest impact on your business. Whether you’re an executive, a manager, or a student wanting to learn more, Analytics and Big Data is the most comprehensive collection you’ll find on the ever-growing phenomenon of digital data and analysis—and how you can make this rising business trend work for you. Named one of the ten “Masters of the New Economy” by CIO magazine, Thomas Davenport has helped hundreds of companies revitalize their management practices. He combines his interests in research, teaching, and business management as the President’s Distinguished Professor of Information Technology & Management at Babson College. Davenport has also taught at Harvard Business School, the University of Chicago, Dartmouth’s Tuck School of Business, and the University of Texas at Austin and has directed research centers at Accenture, McKinsey & Company, Ernst & Young, and CSC. He is also an independent Senior Advisor to Deloitte Analytics.

A practical guide to leveraging your data to spur innovation and growth Your business generates reams of data, but what do you do with it? Reporting is only the beginning. Your data holds the key to innovation and growth - you just need the proper analytics. In Big Data, Big Innovation: Enabling Competitive Differentiation Through Business Analytics, author Evan Stubbs explores the potential gold hiding in your un-mined data. As Chief Analytics Officer for SAS Australia/New Zealand, Stubbs brings an industry insider's perspective to guide you through pattern recognition, analysis, and implementation. Big Data, Big Innovation: Enabling Competitive Differentiation Through Business Analytics details a groundbreaking approach to ensuring your company's upward trajectory. Use this guide to leverage your customer information, financial reports, performance metrics, and more to build a rock-solid foundation for future growth. Build an effective analytics team, and empower them with the right tools Learn how big data drives both evolutionary and revolutionary innovation, and who should be responsible Identify data collection and analysis opportunities and implement action plans Design the platform that suits your company's current and future needs Quantify performance with statistics, programming, and research for a more complete picture of operations Effective management means combining data, people, and analytics to create a synergistic force for innovation and growth. If you want your company to move forward with confidence, Big Data, Big Innovation: Enabling Competitive Differentiation Through Business Analytics can show you how to use what you already have and acquire what you need to succeed.

Don't squander your most valuable resource! Collectively, your workers are your company's most important and most valuable asset. To make the most of this asset, nothing beats quantitative performance and investment measurement. Learning and Development is an 80 billion-dollar industry, and every valuable employee represents a sizable investment on the part of your company. To keep your business moving forward, effective management of human capital is crucial. It generates plenty of data, and deep analysis of this data helps you provide feedback and make adjustments to capitalize on the combined knowledge, skills, and creativity of your workers. Developing Human Capital: Using Analytics to Plan and Optimize Your Learning and Development Investments provides a guidebook for collecting, organizing, and analyzing the data surrounding human capital so you can make the most of your employees' potential. Use predictive analysis to optimize human capital investments Learn effective study design and alignment Get the tools you need for measurement, surveys, and analysis Decide what to measure and how to measure it Outline your company's current and future analytics technology needs Map data sources, and overcome barriers to data collection Authors Gene Pease, Bonnie Beresford, and Lew Walker provide case studies in which major companies applied human capital analytics to guide people decisions, and expand upon the role of analytics in Learning and Development. Developing Human Capital: Using Analytics to Plan and Optimize Your Learning and Development Investments is an essential guide to 21st century human resources and management practices, and can keep you from squandering your company's most valuable resource.

PROVE THE VALUE OF YOUR HR PROGRAM WITH HARD DATA While corporate leaders may well know the value of human capital, they don’t always understand the extent to which the HR function contributes to the bottom line. So when times get tough and business budgets get cut, HR departments often take the first hit. In this groundbreaking guide, the cofounders of ROI Institute, Jack Phillips and Patti Phillips, provide the tools and techniques you need to use analytics to show top decision makers the value of HR in your organization. Focusing on three types of analytics--descriptive, predictive, and prescriptive-- Making Human Capital Analytics Work shows how you can apply analytics by: Developing relationships between variables Predicting the success of HR programs Determining the cost of intangibles that are otherwise diffi cult to value Showing the business value of particular HR programs Calculating and forecasting the ROI of various HR projects and programs Much more than a guide to using data collection and analysis, Making Human Capital Analytics Work is a template for spearheading large-scale change in your organization by dramatically influencing your department's overall image within the organization. The authors take you step-by-step through the processes of using hard data to drive decisions and demonstrate the tangible value of HR. You know that your department is more than administrative and transactional--that it's an integral player in your company's strategy. Apply the lessons in Making Human Capital Analytics Work and ensure that all other stakeholders know too.

MATLAB for Neuroscientists serves as the only complete study manual and teaching resource for MATLAB, the globally accepted standard for scientific computing, in the neurosciences and psychology. This unique introduction can be used to learn the entire empirical and experimental process (including stimulus generation, experimental control, data collection, data analysis, modeling, and more), and the 2nd Edition continues to ensure that a wide variety of computational problems can be addressed in a single programming environment. This updated edition features additional material on the creation of visual stimuli, advanced psychophysics, analysis of LFP data, choice probabilities, synchrony, and advanced spectral analysis. Users at a variety of levels—advanced undergraduates, beginning graduate students, and researchers looking to modernize their skills—will learn to design and implement their own analytical tools, and gain the fluency required to meet the computational needs of neuroscience practitioners. The first complete volume on MATLAB focusing on neuroscience and psychology applications Problem-based approach with many examples from neuroscience and cognitive psychology using real data Illustrated in full color throughout Careful tutorial approach, by authors who are award-winning educators with strong teaching experience

The Internet has been transformed in the past years from a system primarily oriented on information provision into a medium for communication and community-building. The notion of “Web 2.0”, social software, and social networking sites such as Facebook, Twitter and MySpace have emerged in this context. With such platforms comes the massive provision and storage of personal data that are systematically evaluated, marketed, and used for targeting users with advertising. In a world of global economic competition, economic crisis, and fear of terrorism after 9/11, both corporations and state institutions have a growing interest in accessing this personal data. Here, contributors explore this changing landscape by addressing topics such as commercial data collection by advertising, consumer sites and interactive media; self-disclosure in the social web; surveillance of file-sharers; privacy in the age of the internet; civil watch-surveillance on social networking sites; and networked interactive surveillance in transnational space. This book is a result of a research action launched by the intergovernmental network COST (European Cooperation in Science and Technology).

Explore the practices and cutting-edge research on the new and exciting topic of paradata Paradata are measurements related to the process of collecting survey data. Improving Surveys with Paradata: Analytic Uses of Process Information is the most accessible and comprehensive contribution to this up-and-coming area in survey methodology. Featuring contributions from leading experts in the field, Improving Surveys with Paradata: Analytic Uses of Process Information introduces and reviews issues involved in the collection and analysis of paradata. The book presents readers with an overview of the indispensable techniques and new, innovative research on improving survey quality and total survey error. Along with several case studies, topics include: Using paradata to monitor fieldwork activity in face-to-face, telephone, and web surveys Guiding intervention decisions during data collection Analysis of measurement, nonresponse, and coverage error via paradata Providing a practical, encompassing guide to the subject of paradata, the book is aimed at both producers and users of survey data. Improving Surveys with Paradata: Analytic Uses of Process The book also serves as an excellent resource for courses on data collection, survey methodology, and nonresponse and measurement error.

Logging and Log Management: The Authoritative Guide to Understanding the Concepts Surrounding Logging and Log Management introduces information technology professionals to the basic concepts of logging and log management. It provides tools and techniques to analyze log data and detect malicious activity. The book consists of 22 chapters that cover the basics of log data; log data sources; log storage technologies; a case study on how syslog-ng is deployed in a real environment for log collection; covert logging; planning and preparing for the analysis log data; simple analysis techniques; and tools and techniques for reviewing logs for potential problems. The book also discusses statistical analysis; log data mining; visualizing log data; logging laws and logging mistakes; open source and commercial toolsets for log data collection and analysis; log management procedures; and attacks against logging systems. In addition, the book addresses logging for programmers; logging and compliance with regulations and policies; planning for log analysis system deployment; cloud logging; and the future of log standards, logging, and log analysis. This book was written for anyone interested in learning more about logging and log management. These include systems administrators, junior security engineers, application developers, and managers. Comprehensive coverage of log management including analysis, visualization, reporting and more Includes information on different uses for logs -- from system operations to regulatory compliance Features case Studies on syslog-ng and actual real-world situations where logs came in handy in incident response Provides practical guidance in the areas of report, log analysis system selection, planning a log analysis system and log data normalization and correlation

Experiments are the most effective way to learn about the world. By cleverly interfering with something to see how it reacts we are able to find out how it works. In contrast to passive observation, experimenting provides us with data relevant to our research and thus less time and effort is spent separating relevant from irrelevant information. The art of experimentation is often learnt by doing, so an intuitive understanding of the experimental method usually evolves gradually through years of trial and error. This book speeds up the journey for the reader to becoming a proficient experimenter. Organized in two parts, this unique text begins by providing a general introduction to the scientific approach to experimentation. It then describes the processes and tools required, including the relevant statistical and experimental methods. Towards the end of the book a methodology is presented, which leads the reader through the three phases of an experiment: 'Planning', 'Data Collection', and 'Analysis and Synthesis'. Experiment! Provides an excellent introduction to the methodology and implementation of experimentation in the natural, engineering and medical sciences Puts practical tools into scientific context Features a number of selected actual experiments to explore what are the key characteristics of good experiments Includes examples and exercises in every chapter This book focuses on general research skills, such as adopting a scientific mindset, learning how to plan meaningful experiments and understanding the fundamentals of collecting and interpreting data. It is directed to anyone engaged in experiments, especially Ph.D. and masters students just starting to create and develop their own experiments.

Praise for Common Errors in Statistics (and How to Avoid Them) "A very engaging and valuable book for all who use statistics in any setting." —CHOICE "Addresses popular mistakes often made in data collection and provides an indispensable guide to accurate statistical analysis and reporting. The authors' emphasis on careful practice, combined with a focus on the development of solutions, reveals the true value of statistics when applied correctly in any area of research." —MAA Reviews Common Errors in Statistics (and How to Avoid Them), Fourth Edition provides a mathematically rigorous, yet readily accessible foundation in statistics for experienced readers as well as students learning to design and complete experiments, surveys, and clinical trials. Providing a consistent level of coherency throughout, the highly readable Fourth Edition focuses on debunking popular myths, analyzing common mistakes, and instructing readers on how to choose the appropriate statistical technique to address their specific task. The authors begin with an introduction to the main sources of error and provide techniques for avoiding them. Subsequent chapters outline key methods and practices for accurate analysis, reporting, and model building. The Fourth Edition features newly added topics, including: Baseline data Detecting fraud Linear regression versus linear behavior Case control studies Minimum reporting requirements Non-random samples The book concludes with a glossary that outlines key terms, and an extensive bibliography with several hundred citations directing readers to resources for further study. Presented in an easy-to-follow style, Common Errors in Statistics, Fourth Edition is an excellent book for students and professionals in industry, government, medicine, and the social sciences.

JMP Means Business: Statistical Models for Management, by Josef Schmee and Jane Oppenlander, covers basic methods and models of classical statistics. Designed for business and MBA students, as well as industry professionals who need to use and interpret statistics, JMP Means Business covers data collection, descriptive statistics, distributions, confidence intervals and hypothesis tests, analysis of variance, contingency tables, simple and multiple regression, and exponential smoothing of time series. The easy-to-use format includes verbal and graphical explanations and promotes standard problem-solving techniques, with a limited use of formulas. Examples from business and industry serve to introduce each topic. Each example starts with a problem definition and data requirements, followed by a step-by-step analysis with JMP. Relevant output from this analysis is used to explain each method and to provide the basis for interpretation. Each chapter ends with a summary and a collection of problems for further study.

Statistical analysis is essential to business decision-making and management, but the underlying theory of data collection, organization and analysis is one of the most challenging topics for business students and practitioners. This user-friendly text and CD-ROM package will help you to develop strong skills in presenting and interpreting statistical information in a business or management environment. Based entirely on using Microsoft Excel rather than more complicated applications, it includes a clear guide to using Excel with the key functions employed in the book, a glossary of terms and equations, plus a section specifically for those readers who feel rusty in basic maths. Each chapter has worked examples and explanations to illustrate the use of statistics in real life scenarios, with databases for the worked examples, cases and answers on the accompanying CD-ROM.