Produkt zum Begriff Data Analytics:
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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 € -
Getting Started with Data Science: Making Sense of Data with Analytics
Master Data Analytics Hands-On by Solving Fascinating Problems You’ll Actually Enjoy!Harvard Business Review recently called data science “The Sexiest Job of the 21st Century.” It’s not just sexy: For millions of managers, analysts, and students who need to solve real business problems, it’s indispensable. Unfortunately, there’s been nothing easy about learning data science–until now.Getting Started with Data Science takes its inspiration from worldwide best-sellers like Freakonomics and Malcolm Gladwell’s Outliers: It teaches through a powerful narrative packed with unforgettable stories.Murtaza Haider offers informative, jargon-free coverage of basic theory and technique, backed with plenty of vivid examples and hands-on practice opportunities. Everything’s software and platform agnostic, so you can learn data science whether you work with R, Stata, SPSS, or SAS. Best of all, Haider teaches a crucial skillset most data science books ignore: how to tell powerful stories using graphics and tables. Every chapter is built around real research challenges, so you’ll always know why you’re doing what you’re doing.You’ll master data science by answering fascinating questions, such as:• Are religious individuals more or less likely to have extramarital affairs?• Do attractive professors get better teaching evaluations?• Does the higher price of cigarettes deter smoking?• What determines housing prices more: lot size or the number of bedrooms?• How do teenagers and older people differ in the way they use social media?• Who is more likely to use online dating services?• Why do some purchase iPhones and others Blackberry devices?• Does the presence of children influence a family’s spending on alcohol?For each problem, you’ll walk through defining your question and the answers you’ll need; exploring howothers have approached similar challenges; selecting your data and methods; generating your statistics;organizing your report; and telling your story. Throughout, the focus is squarely on what matters most:transforming data into insights that are clear, accurate, and can be acted upon.
Preis: 18.18 € | Versand*: 0 € -
Visual Analytics Fundamentals: Creating Compelling Data Narratives with Tableau
Master the Fundamentals of Modern Visual Analytics--and Craft Compelling Visual Narratives in Tableau! Do you need to persuade or inform people? Do you have data? Then you need to master visual analytics and visual storytelling. Today, the #1 tool for telling visual stories with data is Tableau, and demand for Tableau skills is soaring. In Visual Analytics Fundamentals, renowned visual storyteller and analytics professor Lindy Ryan introduces all the fundamental visual analytics knowledge, cognitive and perceptual concepts, and hands-on Tableau techniques you'll need. Ryan puts core analytics and visual concepts upfront, so you'll always know exactly what you're trying to accomplish and can apply this knowledge with any tool. Building on this foundation, she presents classroom-proven guided exercises for translating ideas into reality with Tableau 2022. You'll learn how to organize data and structure analysis with stories in mind, embrace exploration and visual discovery, and articulate your findings with rich data, well-curated visualizations, and skillfully crafted narrative frameworks. Ryan's insider tips take you far beyond the basics--and you'll rely on her expert checklists for years to come. Communicate more powerfully by applying scientific knowledge of the human brain Get started with the Tableau platform and Tableau Desktop 2022 Connect data and quickly prepare it for analysis Ask questions that help you keep data firmly in context Choose the right charts, graphs, and maps for each project--and avoid the wrong ones Craft storyboards that reflect your message and audience Direct attention to what matters most Build data dashboards that guide people towards meaningful outcomes Master advanced visualizations, including timelines, Likert scales, and lollipop charts This book has only one prerequisite: your desire to communicate insights from data in ways that are memorable and actionable. It's for executives and professionals sharing important results, students writing reports or presentations, teachers cultivating data literacy, journalists making sense of complex trends. . . . practically everyone! Don't even have Tableau? Download your free trial of Tableau Desktop and let's get started!
Preis: 47.07 € | Versand*: 0 € -
Data Analytics for IT Networks: Developing Innovative Use Cases
Use data analytics to drive innovation and value throughout your network infrastructureNetwork and IT professionals capture immense amounts of data from their networks. Buried in this data are multiple opportunities to solve and avoid problems, strengthen security, and improve network performance. To achieve these goals, IT networking experts need a solid understanding of data science, and data scientists need a firm grasp of modern networking concepts. Data Analytics for IT Networks fills these knowledge gaps, allowing both groups to drive unprecedented value from telemetry, event analytics, network infrastructure metadata, and other network data sources. Drawing on his pioneering experience applying data science to large-scale Cisco networks, John Garrett introduces the specific data science methodologies and algorithms network and IT professionals need, and helps data scientists understand contemporary network technologies, applications, and data sources.After establishing this shared understanding, Garrett shows how to uncover innovative use cases that integrate data science algorithms with network data. He concludes with several hands-on, Python-based case studies reflecting Cisco Customer Experience (CX) engineers’ supporting its largest customers. These are designed to serve as templates for developing custom solutions ranging from advanced troubleshooting to service assurance.Understand the data analytics landscape and its opportunities in Networking See how elements of an analytics solution come together in the practical use casesExplore and access network data sources, and choose the right data for your problemInnovate more successfully by understanding mental models and cognitive biasesWalk through common analytics use cases from many industries, and adapt them to your environmentUncover new data science use cases for optimizing large networksMaster proven algorithms, models, and methodologies for solving network problemsAdapt use cases built with traditional statistical methodsUse data science to improve network infrastructure analysisAnalyze control and data planes with greater sophisticationFully leverage your existing Cisco tools to collect, analyze, and visualize data
Preis: 43.86 € | Versand*: 0 €
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Kann man mit Wirtschaftsinformatik Data Scientist oder Data Analyst werden?
Ja, mit einem Studium der Wirtschaftsinformatik kann man sowohl Data Scientist als auch Data Analyst werden. Wirtschaftsinformatik vermittelt Kenntnisse in den Bereichen Informatik und Betriebswirtschaft, die für diese Berufe relevant sind. Zusätzliche Weiterbildungen oder Spezialisierungen in den Bereichen Data Science oder Data Analytics können jedoch von Vorteil sein.
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Wie heißt Data Luv?
Data Luv heißt mit bürgerlichem Namen Luca Fuchs. Er ist ein deutscher Rapper und Produzent, der vor allem für seine Autotune-geschwängerten Songs bekannt ist. Sein Stil ist geprägt von eingängigen Melodien und modernen Trap-Beats. Data Luv hat sich in der deutschen Rap-Szene einen Namen gemacht und ist besonders bei jüngeren Hörern beliebt. Sein Künstlername spielt auf die Bedeutung von Daten in der heutigen digitalen Welt an und verleiht ihm eine moderne und futuristische Note.
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Wie Data Scientist werden?
Um Data Scientist zu werden, solltest du zuerst ein starkes Fundament in Mathematik und Statistik aufbauen. Es ist auch wichtig, Programmiersprachen wie Python oder R zu beherrschen. Praktische Erfahrung durch Projekte oder Praktika kann ebenfalls hilfreich sein. Zudem ist es ratsam, sich fortlaufend weiterzubilden und auf dem neuesten Stand der Technologien und Methoden zu bleiben. Hast du bereits Erfahrungen in diesem Bereich gesammelt oder möchtest du noch mehr darüber erfahren?
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Wie funktioniert ein Data Warehouse?
Ein Data Warehouse ist eine spezialisierte Datenbank, die große Mengen an strukturierten und unstrukturierten Daten aus verschiedenen Quellen sammelt, speichert und verwaltet. Es dient dazu, Daten zu konsolidieren, zu analysieren und für Entscheidungsfindungen zugänglich zu machen. Um ein Data Warehouse zu erstellen, werden Daten aus verschiedenen operativen Systemen extrahiert, transformiert und geladen (ETL-Prozess). Die Daten werden dann in einem zentralen Repository gespeichert, wo sie für Analysen und Berichterstellung zur Verfügung stehen. Data Warehouses verwenden spezielle Datenmodellierungstechniken wie den Stern- oder Schneeflockenschema, um Daten effizient zu strukturieren und abzufragen. Business Intelligence Tools werden häufig verwendet, um Daten aus dem Data Warehouse zu extrahieren, zu analysieren und in aussagekräftige Berichte und Dashboards umzuwandeln. Durch die zentrale Speicherung und Aufbereitung von Daten ermöglicht ein Data Warehouse Unternehmen, fundierte Entscheidungen zu treffen, Trends zu identifizieren und Geschäftsprozesse zu optimieren.
Ähnliche Suchbegriffe für Data Analytics:
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Business Intelligence, Analytics, Data Science, and AI, Global Edition
Business Intelligence, Analytics, Data Science, and AI is your guide to the business-related impact of artificial intelligence, data science and analytics, designed to prepare you for a managerial role. The text's vignettes and cases feature modern companies and non-profit organizations and illustrate capabilities, costs and justifications of BI across various business units. With coverage of many data science/AI applications, you'll explore tools, then learn from various organizations' experiences employing such applications. Ample hands-on practice is provided, can be completed with a range of software, and will help you use analytics as a future manager. The 5th Edition integrates the fully updated content of Analytics, Data Science, and Artificial Intelligence, 11/e and Business Intelligence, Analytics, and Data Science, 4/e into one textbook, strengthened by 4 new chapters that will equip you for today's analytics and AI tech, such as ChatGPT. Examples explore analytics in sports, gaming, agriculture and data for good.
Preis: 81.32 € | Versand*: 0 € -
Product Analytics: Applied Data Science Techniques for Actionable Consumer Insights
Use Product Analytics to Understand and Change Consumer Behavior at ScaleProduct Analytics is a complete, hands-on guide to generating actionable business insights from customer data. Experienced data scientist and enterprise manager Joanne Rodrigues introduces practical statistical techniques for determining why things happen and how to change, at scale, what people do. She complements these with powerful social science techniques for creating better theories, designing better metrics, and driving more rapid and sustained behavior change.This book fills the gaps that many other data science book leave behind: how to start a new data science project; how to conceptualize complex ideas; building metrics from the statistic and demographic fundamentals; projecting consumer populations and material needs for a business; and causal inference beyond simple A/B testing techniques, such as difference-in-difference, regression discontinuity, propensity score matching, and uplift modelling.Writing for entrepreneurs, product managers, marketers, and other business analytics professionals, Rodrigues teaches through intuitive examples from both web and offline environments. Avoiding math-heavy explanations, she guides you step by step through choosing the right techniques and algorithms for each application, running analyses in the R programming language, and getting answers you can trust.Whatever your product or service, this guide can help you create precision-targeted marketing campaigns, improve consumer satisfaction and engagement, and grow revenue and profits.Develop core metrics and effective KPIs for user analytics in any web productTruly understand statistical inference, and the differences between correlation and causationBuild intuitive predictive models to capture user behavior in productsTease out causal effects from observational data using modern, quasi-experimental designs and statistical matchingImprove response through uplift modeling and other sophisticated targeting methodsProject business costs and product population changes via advanced demographic techniquesRegister your book for convenient access to downloads, updates, and/or corrections as they become available. See inside the book for details.
Preis: 37.44 € | Versand*: 0 € -
Real-World Data Mining: Applied Business Analytics and Decision Making
Use the latest data mining best practices to enable timely, actionable, evidence-based decision making throughout your organization! Real-World Data Mining demystifies current best practices, showing how to use data mining to uncover hidden patterns and correlations, and leverage these to improve all aspects of business performance. Drawing on extensive experience as a researcher, practitioner, and instructor, Dr. Dursun Delen delivers an optimal balance of concepts, techniques and applications. Without compromising either simplicity or clarity, he provides enough technical depth to help readers truly understand how data mining technologies work. Coverage includes: processes, methods, techniques, tools, and metrics; the role and management of data; text and web mining; sentiment analysis; and Big Data integration. Throughout, Delen's conceptual coverage is complemented with application case studies (examples of both successes and failures), as well as simple, hands-on tutorials. Real-World Data Mining will be valuable to professionals on analytics teams; professionals seeking certification in the field; and undergraduate or graduate students in any analytics program: concentrations, certificate-based, or degree-based.
Preis: 36.37 € | Versand*: 0 € -
Getting Started with Data Science: Making Sense of Data with Analytics
Harvard Business Review recently called data science "The Sexiest Job of the 21st Century." It's not just sexy: for millions of managers and students who need to solve business problems with big data, it's indispensable. Unfortunately, there's been nothing sexy about learning data science -- until now. Getting Started with Data Science takes its approach from worldwide best-sellers like Freakonomics and the books of Malcolm Gladwell: it teaches through a powerful narrative packed with unforgettable stories. Murtaza Haider offers careful, jargon-free coverage of basic theory and technique, backed with plenty of clear examples and practice opportunities. Everything's software and platform independent, so you can learn what you need whether you work with R, Stata, SPSS, SAS, or another toolset. Best of all, Haider teaches a crucial skillset most academic data science books ignore: how to transform data into narratives, graphics, and tables that make it vivid and actionable. For each problem, you'll walk through identifying the right data and methods, creating summary statistics, describing and visualizing findings, and seeing how others have handled the challenge. In advanced chapters, you'll also learn sophisticated statistical modeling techniques. Throughout, the focus is on data: finding it, using it, and powerfully communicating its meaning.
Preis: 24.6 € | Versand*: 0 €
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Wie alt ist Data Love?
Data Love ist ein Kunstwerk, das von dem Künstler Refik Anadol geschaffen wurde. Es wurde erstmals im Jahr 2019 präsentiert, was bedeutet, dass es etwa zwei Jahre alt ist. Das Kunstwerk kombiniert künstliche Intelligenz, Datenvisualisierung und digitale Medien, um eine immersive Erfahrung zu schaffen. Es erforscht die Beziehung zwischen Mensch und Technologie und reflektiert über die zunehmende Bedeutung von Daten in unserer Gesellschaft. Data Love hat seit seiner Enthüllung weltweit Aufmerksamkeit erregt und wurde bereits in verschiedenen Ausstellungen und Veranstaltungen gezeigt.
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Was ist ein Data Plug?
Ein Data Plug ist ein Gerät, das in der Lage ist, Daten von verschiedenen Quellen zu sammeln, zu analysieren und zu übertragen. Es wird oft verwendet, um Daten aus verschiedenen Systemen oder Geräten zu extrahieren und in einem zentralen System zu konsolidieren. Dadurch können Unternehmen wichtige Erkenntnisse gewinnen und fundierte Entscheidungen treffen. Data Plugs können auch dazu beitragen, die Effizienz von Geschäftsprozessen zu verbessern und die Datensicherheit zu erhöhen. Insgesamt ermöglicht ein Data Plug eine nahtlose Integration und Analyse von Daten aus verschiedenen Quellen.
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Was ist VW Data Plug?
Was ist VW Data Plug? Der VW Data Plug ist ein kleines Gerät, das in den OBD-II-Anschluss eines Volkswagen-Fahrzeugs eingesteckt wird. Es sammelt Daten über das Fahrverhalten, den Zustand des Fahrzeugs und die Fahrzeugnutzung. Diese Daten können dann über eine Smartphone-App abgerufen werden, um dem Fahrer Einblicke in sein Fahrverhalten zu geben und ihm dabei zu helfen, seinen Fahrstil zu verbessern. Der VW Data Plug kann auch dazu beitragen, den Fahrzeugzustand zu überwachen und frühzeitig auf mögliche Probleme hinzuweisen.
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Was ist mit "data" gemeint?
Mit "data" ist in der Regel die Sammlung von Informationen oder Daten gemeint. Es kann sich dabei um verschiedene Arten von Daten handeln, wie zum Beispiel numerische Werte, Texte, Bilder oder Videos. Data wird oft verwendet, um Informationen zu analysieren, Muster zu erkennen oder Entscheidungen zu treffen.
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