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Produkt zum Begriff Predictive Analytics:
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Chabert, Antoine: SAP Analytics Cloud: Predictive Analytics
SAP Analytics Cloud: Predictive Analytics , Today's organizations must be prepared for tomorrow's events. Forecast future behavior in SAP Analytics Cloud with this comprehensive guide to predictive analytics! Start by learning about the data types, scenarios, and methods used in predictive analytics projects. Then follow step-by-step instructions to build, analyze, and apply predictive models to your business data using classification, time series forecasting, and regression analysis. Automate your models and dive into the data science with this all-in-one guide! In this book, you'll learn about: a. Predictive Scenarios and Projects Understand the basics of predictive analytics in SAP Analytics Cloud: scenarios, data types, and actions. Then plan your predictive project, including identifying the key stakeholders and reviewing the methodology. b. Build, Train, Analyze, and Apply Master predictive models from end to end. Create classification, time series, and regression models; then train them to identify business patterns. Analyze and apply the results of your models to data in SAP Analytics Cloud. c. Practical Demonstrations See predictive analytics in action! Identify use cases for predictive modeling. For each data model, understand practical applications through curated examples with sample business data. Highlights include: 1) Predictive scenarios 2) Predictive forecasts 3) Data modeling 4) Planning 5) Time series model 6) Classification model 7) Regression model 8) Multi-actions 9) Data science 10) Stories and dashboards , Schule & Ausbildung > Fachbücher, Lernen & Nachschlagen
Preis: 81.99 € | Versand*: 0 € -
Web and Network Data Science: Modeling Techniques in Predictive Analytics
Master modern web and network data modeling: both theory and applications. In Web and Network Data Science, a top faculty member of Northwestern University’s prestigious analytics program presents the first fully-integrated treatment of both the business and academic elements of web and network modeling for predictive analytics. Some books in this field focus either entirely on business issues (e.g., Google Analytics and SEO); others are strictly academic (covering topics such as sociology, complexity theory, ecology, applied physics, and economics). This text gives today's managers and students what they really need: integrated coverage of concepts, principles, and theory in the context of real-world applications. Building on his pioneering Web Analytics course at Northwestern University, Thomas W. Miller covers usability testing, Web site performance, usage analysis, social media platforms, search engine optimization (SEO), and many other topics. He balances this practical coverage with accessible and up-to-date introductions to both social network analysis and network science, demonstrating how these disciplines can be used to solve real business problems.
Preis: 36.37 € | Versand*: 0 € -
Predictive Analytics: Data Mining, Machine Learning and Data Science for Practitioners
Use Predictive Analytics to Uncover Hidden Patterns and Correlations and Improve Decision-MakingUsing predictive analytics techniques, decision-makers can uncover hidden patterns and correlations in their data and leverage these insights to improve many key business decisions. In this thoroughly updated guide, Dr. Dursun Delen illuminates state-of-the-art best practices for predictive analytics for both business professionals and students. Delen's holistic approach covers key data mining processes and methods, relevant data management techniques, tools and metrics, advanced text and web mining, big data integration, and much more. Balancing theory and practice, Delen presents intuitive conceptual illustrations, realistic example problems, and real-world case studiesincluding lessons from failed projects. It's all designed to help you gain a practical understanding you can apply for profit.* Leverage knowledge extracted via data mining to make smarter decisions* Use standardized processes and workflows to make more trustworthy predictions* Predict discrete outcomes (via classification), numeric values (via regression), and changes over time (via time-series forecasting)* Understand predictive algorithms drawn from traditional statistics and advanced machine learning* Discover cutting-edge techniques, and explore advanced applications ranging from sentiment analysis to fraud detection
Preis: 37.44 € | Versand*: 0 € -
Modeling Techniques in Predictive Analytics: Business Problems and Solutions with R
Today, successful firms compete and win based on analytics. Modeling Techniques in Predictive Analytics brings together all the concepts, techniques, and R code you need to excel in any role involving analytics. Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, appealing to managers, analysts, programmers, and students alike. Miller addresses multiple business challenges and business cases, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and even spatio-temporal data. For each problem, Miller explains why the problem matters, what data is relevant, how to explore your data once you’ve identified it, and then how to successfully model that data. You’ll learn how to model data conceptually, with words and figures; and then how to model it with realistic R programs that deliver actionable insights and knowledge. Miller walks you through model construction, explanatory variable subset selection, and validation, demonstrating best practices for improving out-of-sample predictive performance. He employs data visualization and statistical graphics in exploring data, presenting models, and evaluating performance. All example code is presented in R, today’s #1 system for applied statistics, statistical research, and predictive modeling; code is set apart from other text so it’s easy to find for those who want it (and easy to skip for those who don’t).
Preis: 36.37 € | Versand*: 0 €
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Wie kann der Google Analytics Cookie ein First-Party-Cookie sein?
Der Google Analytics Cookie kann als First-Party-Cookie betrachtet werden, da er von der Website selbst gesetzt wird, auf der er verwendet wird. Dies bedeutet, dass der Cookie Informationen über das Verhalten des Benutzers auf dieser spezifischen Website sammelt und speichert. Es handelt sich also um ein Cookie, das von der Website selbst kontrolliert wird und keine Informationen von anderen Websites sammelt.
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Wie können Unternehmen mithilfe von Web-Analytics ihre Online-Präsenz und Marketingstrategien verbessern? Was sind die wichtigsten Kennzahlen, die durch Web-Analytics erfasst werden und wie können sie für die Optimierung der Website genutzt werden?
Unternehmen können mithilfe von Web-Analytics das Nutzerverhalten auf ihrer Website analysieren, um Schwachstellen zu identifizieren und ihre Marketingstrategien zu verbessern. Die wichtigsten Kennzahlen, die erfasst werden, sind z.B. Seitenaufrufe, Verweildauer, Absprungrate und Conversion-Rate. Diese Daten können genutzt werden, um die Benutzerfreundlichkeit der Website zu optimieren, das Kundenverhalten zu verstehen und die Effektivität von Marketingkampagnen zu messen.
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Wie kann die Nutzung von Web Analytics-Tools dazu beitragen, die Effektivität einer Website zu verbessern?
Web Analytics-Tools liefern detaillierte Informationen über das Nutzerverhalten auf einer Website, wie z.B. Seitenaufrufe, Verweildauer und Klickpfade. Durch die Analyse dieser Daten können Schwachstellen identifiziert und Optimierungsmaßnahmen abgeleitet werden. So kann die Website gezielt an die Bedürfnisse der Nutzer angepasst werden, um die Effektivität zu steigern.
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Wie können Analytics-Tools Unternehmen dabei unterstützen, ihre Daten zu analysieren und fundierte Geschäftsentscheidungen zu treffen?
Analytics-Tools können Unternehmen dabei unterstützen, ihre Daten zu analysieren, indem sie große Datenmengen schnell verarbeiten und relevante Informationen extrahieren. Sie bieten auch Visualisierungen und Berichte, um komplexe Daten verständlich darzustellen und Trends aufzuzeigen. Auf dieser Grundlage können Unternehmen fundierte Geschäftsentscheidungen treffen und ihre Leistung verbessern.
Ähnliche Suchbegriffe für Predictive Analytics:
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Marketing Data Science: Modeling Techniques in Predictive Analytics with R and Python
Now, a leader of Northwestern University's prestigious analytics program presents a fully-integrated treatment of both the business and academic elements of marketing applications in predictive analytics. Writing for both managers and students, Thomas W. Miller explains essential concepts, principles, and theory in the context of real-world applications. Building on Miller's pioneering program, Marketing Data Science thoroughly addresses segmentation, target marketing, brand and product positioning, new product development, choice modeling, recommender systems, pricing research, retail site selection, demand estimation, sales forecasting, customer retention, and lifetime value analysis. Starting where Miller's widely-praised Modeling Techniques in Predictive Analytics left off, he integrates crucial information and insights that were previously segregated in texts on web analytics, network science, information technology, and programming. Coverage includes: The role of analytics in delivering effective messages on the web Understanding the web by understanding its hidden structures Being recognized on the web – and watching your own competitors Visualizing networks and understanding communities within them Measuring sentiment and making recommendations Leveraging key data science methods: databases/data preparation, classical/Bayesian statistics, regression/classification, machine learning, and text analytics Six complete case studies address exceptionally relevant issues such as: separating legitimate email from spam; identifying legally-relevant information for lawsuit discovery; gleaning insights from anonymous web surfing data, and more. This text's extensive set of web and network problems draw on rich public-domain data sources; many are accompanied by solutions in Python and/or R. Marketing Data Science will be an invaluable resource for all students, faculty, and professional marketers who want to use business analytics to improve marketing performance.
Preis: 36.37 € | Versand*: 0 € -
Modeling Techniques in Predictive Analytics: Business Problems and Solutions with R, Revised and Expanded Edition
To succeed with predictive analytics, you must understand it on three levels: Strategy and management Methods and models Technology and code This up-to-the-minute reference thoroughly covers all three categories. Now fully updated, this uniquely accessible book will help you use predictive analytics to solve real business problems and drive real competitive advantage. If you’re new to the discipline, it will give you the strong foundation you need to get accurate, actionable results. If you’re already a modeler, programmer, or manager, it will teach you crucial skills you don’t yet have. Unlike competitive books, this guide illuminates the discipline through realistic vignettes and intuitive data visualizations–not complex math. Thomas W. Miller, leader of Northwestern University’s pioneering program in predictive analytics, guides you through defining problems, identifying data, crafting and optimizing models, writing effective R code, interpreting results, and more. Every chapter focuses on one of today’s key applications for predictive analytics, delivering skills and knowledge to put models to work–and maximize their value. Reflecting extensive student and instructor feedback, this edition adds five classroom-tested case studies, updates all code for new versions of R, explains code behavior more clearly and completely, and covers modern data science methods even more effectively. All data sets, extensive R code, and additional examples available for download at http://www.ftpress.com/miller If you want to make the most of predictive analytics, data science, and big data, this is the book for you. Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, appealing to managers, analysts, programmers, and students alike. Miller addresses multiple business cases and challenges, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and spatio-temporal data. You’ll learn why each problem matters, what data are relevant, and how to explore the data you’ve identified. Miller guides you through conceptually modeling each data set with words and figures; and then modeling it again with realistic R programs that deliver actionable insights. You’ll walk through model construction, explanatory variable subset selection, and validation, mastering best practices for improving out-of-sample predictive performance. Throughout, Miller employs data visualization and statistical graphics to help you explore data, present models, and evaluate performance. This edition adds five new case studies, updates all code for the newest versions of R, adds more commenting to clarify how the code works, and offers a more detailed and up-to-date primer on data science methods. Gain powerful, actionable, profitable insights about: Advertising and promotion Consumer preference and choice Market baskets and related purchases Economic forecasting Operations management Unstructured text and language Customer sentiment Brand and price Sports team performance And much more
Preis: 36.37 € | Versand*: 0 € -
Modern Analytics Methodologies: Driving Business Value with Analytics
Create a complete roadmap for capitalizing on analytics to grow topline revenue and build shareholder value in your unique organization! Modern Analytics Methodologies goes far beyond the classic Analytics Maturity Model to help you overcome the gaps between your current analytics capabilities and where you need to go. Pioneering analytics experts Michele Chambers and Thomas Dinsmore help you implement analytics that supports your strategy, aligns with your culture, and serves your customers and stakeholders. Drawing on work with dozens of leading enterprises, Michele Chambers and Thomas Dinsmore describe high-value applications from many industries, and help you systematically identify and deliver on your company's best opportunities. Writing for both professionals and students, they show how to: Leverage the convergence of macro trends ranging from "flattening" and "green" to Big Data and machine learning Go beyond the Analytics Maturity Model: power your unique business strategy with an equally focused analytics strategy Link key business objectives with core characteristics of your organization, value chain, and stakeholders Take advantage of game changing opportunities before competitors do Effectively integrate the managerial and operational aspects of analytics Measure performance with dashboards, scorecards, visualization, simulation, and more Prioritize and score prospective analytics projects Identify "Quick Wins" you can implement while you're planning for the long-term Build an effective Analytic Program Office to make your roadmap persistent Update and revise your roadmap for new needs and technologies Modern Analytics Methodologies will be an indispensable resource for any executive or professional concerned with analytics, including Chief Analytics Officers; Chief Data Officers; Chief Scientists; Chief Marketing Officers; Chief Risk Officers; Chief Strategy Officers; VPs of Analytics or Big Data; data scientists; business strategists; and line-of-business executives.
Preis: 27.81 € | Versand*: 0 € -
Key Business Analytics
Key Business Analytics will help managers apply tools to turn data into insights that help them better understand their customers, optimise their internal processes and identify cost savings and growth opportunities. It includes analysis techniques within the following categories: Financial analytics – cashflow, profitability, sales forecasts Market analytics – market size, market trends, marketing channels Customer analytics – customer lifetime values, social media, customer needs Employee analytics – capacity, performance, leadership Operational analytics – supply chains, competencies, environmental impact Bare business analytics – sentiments, text, correlations Each tool will follow the bestselling Key format of being 5-6 pages long, broken into short sharp advice on the essentials: What is it? When should I use it? How do I use it? Tips and pitfalls Further reading The full text downloaded to your computer With eBooks you can: search for key concepts, words and phrases make highlights and notes as you study share your notes with friends eBooks are downloaded to your computer and accessible either offline through the Bookshelf (available as a free download), available online and also via the iPad and Android apps. Upon purchase, you'll gain instant access to this eBook. Time limit The eBooks products do not have an expiry date. You will continue to access your digital ebook products whilst you have your Bookshelf installed.
Preis: 27.81 € | Versand*: 0 €
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Wie kann Analytics dabei helfen, Daten zu interpretieren und für die Optimierung von Unternehmensprozessen zu nutzen?
Analytics kann Daten sammeln, analysieren und visualisieren, um Muster und Trends zu identifizieren. Durch die Interpretation dieser Daten können Unternehmen Schwachstellen in ihren Prozessen erkennen und optimieren. Analytics ermöglicht es, fundierte Entscheidungen zu treffen und die Effizienz und Rentabilität von Unternehmensprozessen zu verbessern.
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Wie kann Google Analytics zur Verbesserung der Website-Performance und zur Erhöhung der Conversions genutzt werden?
Google Analytics kann genutzt werden, um das Nutzerverhalten auf der Website zu analysieren und Schwachstellen zu identifizieren. Durch die Auswertung von Daten wie Seitenaufrufen, Verweildauer und Absprungrate können gezielte Optimierungen vorgenommen werden. Außerdem können Conversions durch das Tracking von Zielen und Ereignissen verbessert werden, indem man die Effektivität von Marketingkampagnen und Website-Änderungen messen und anpassen kann.
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Wie beeinflusst die zunehmende Medienkonzentration die Vielfalt und Unabhängigkeit der Medienlandschaft?
Die zunehmende Medienkonzentration führt dazu, dass weniger Unternehmen die Medienlandschaft kontrollieren, was die Vielfalt einschränken kann. Durch die Konzentration von Medienunternehmen können auch Interessenkonflikte entstehen, die die Unabhängigkeit der Berichterstattung beeinträchtigen. Es besteht die Gefahr, dass kritische Stimmen unterdrückt werden und eine einseitige Berichterstattung die Meinungsvielfalt einschränkt.
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Was sind die wichtigsten Kennzahlen, die Unternehmen im Bereich Analytics verfolgen sollten, um ihre Leistung zu messen und zu verbessern?
Die wichtigsten Kennzahlen, die Unternehmen im Bereich Analytics verfolgen sollten, sind Umsatz, Conversion-Rate und Kundenbindung. Diese Kennzahlen helfen dabei, den Erfolg von Marketingkampagnen, Vertriebsstrategien und Kundenbeziehungen zu messen und zu optimieren. Durch die Analyse dieser Kennzahlen können Unternehmen ihre Leistung steigern und ihre Geschäftsziele effektiver erreichen.
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