Produkt zum Begriff Big Data Analytics:
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Enterprise Analytics: Optimize Performance, Process, and Decisions Through Big Data
The Definitive Guide to Enterprise-Level Analytics Strategy, Technology, Implementation, and Management Organizations are capturing exponentially larger amounts of data than ever, and now they have to figure out what to do with it. Using analytics, you can harness this data, discover hidden patterns, and use this knowledge to act meaningfully for competitive advantage. Suddenly, you can go beyond understanding “how, when, and where” events have occurred, to understand why – and use this knowledge to reshape the future. Now, analytics pioneer Tom Davenport and the world-renowned experts at the International Institute for Analytics (IIA) have brought together the latest techniques, best practices, and research on analytics in a single primer for maximizing the value of enterprise data. Enterprise Analytics is today’s definitive guide to analytics strategy, planning, organization, implementation, and usage. It covers everything from building better analytics organizations to gathering data; implementing predictive analytics to linking analysis with organizational performance. The authors offer specific insights for optimizing supply chains, online services, marketing, fraud detection, and many other business functions. They support their powerful techniques with many real-world examples, including chapter-length case studies from healthcare, retail, and financial services. Enterprise Analytics will be an invaluable resource for every business and technical professional who wants to make better data-driven decisions: operations, supply chain, and product managers; product, financial, and marketing analysts; CIOs and other IT leaders; data, web, and data warehouse specialists, and many others.
Preis: 29.95 € | Versand*: 0 € -
Network Security with Netflow and IPFIX: Big Data Analytics for Information Security
A comprehensive guide for deploying, configuring, and troubleshooting NetFlow and learning big data analytics technologies for cyber security Today’s world of network security is full of cyber security vulnerabilities, incidents, breaches, and many headaches. Visibility into the network is an indispensable tool for network and security professionals and Cisco NetFlow creates an environment where network administrators and security professionals have the tools to understand who, what, when, where, and how network traffic is flowing. Network Security with NetFlow and IPFIX is a key resource for introducing yourself to and understanding the power behind the Cisco NetFlow solution. Omar Santos, a Cisco Product Security Incident Response Team (PSIRT) technical leader and author of numerous books including the CCNA Security 210-260 Official Cert Guide, details the importance of NetFlow and demonstrates how it can be used by large enterprises and small-to-medium-sized businesses to meet critical network challenges. This book also examines NetFlow’s potential as a powerful network security tool. Network Security with NetFlow and IPFIX explores everything you need to know to fully understand and implement the Cisco Cyber Threat Defense Solution. It also provides detailed configuration and troubleshooting guidance, sample configurations with depth analysis of design scenarios in every chapter, and detailed case studies with real-life scenarios. You can follow Omar on Twitter: @santosomar NetFlow and IPFIX basics Cisco NetFlow versions and features Cisco Flexible NetFlow NetFlow Commercial and Open Source Software Packages Big Data Analytics tools and technologies such as Hadoop, Flume, Kafka, Storm, Hive, HBase, Elasticsearch, Logstash, Kibana (ELK) Additional Telemetry Sources for Big Data Analytics for Cyber Security Understanding big data scalability Big data analytics in the Internet of everything Cisco Cyber Threat Defense and NetFlow Troubleshooting NetFlow Real-world case studies
Preis: 33.16 € | 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 € -
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 €
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Was sind interessante Anwendungsbereiche im Bereich der Digitalisierung, Big Data und Künstlichen Intelligenz?
Interessante Anwendungsbereiche im Bereich der Digitalisierung, Big Data und Künstlichen Intelligenz sind beispielsweise die personalisierte Medizin, bei der mithilfe von Datenanalyse und KI individuelle Behandlungspläne erstellt werden können. Auch in der Logistikbranche können durch die Analyse großer Datenmengen Effizienzsteigerungen erzielt werden, zum Beispiel durch optimierte Routenplanung. Zudem ermöglicht KI auch im Bereich der Sprach- und Bilderkennung neue Anwendungen, wie beispielsweise automatische Übersetzungen oder Gesichtserkennung.
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Was versteht man unter dem Begriff Big Data?
Was versteht man unter dem Begriff Big Data? Big Data bezieht sich auf die große Menge an Daten, die in hoher Geschwindigkeit generiert werden und die herkömmliche Datenverarbeitungstechniken überfordern. Diese Daten können strukturiert oder unstrukturiert sein und stammen aus verschiedenen Quellen wie sozialen Medien, Sensoren, Mobilgeräten und mehr. Das Ziel von Big Data ist es, diese Daten zu analysieren, um wertvolle Erkenntnisse zu gewinnen und fundierte Entscheidungen zu treffen. Unternehmen nutzen Big Data, um Trends zu identifizieren, Kundenverhalten vorherzusagen und ihre Geschäftsprozesse zu optimieren.
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Wie beeinflusst Big Data die Geschäftsentscheidungen in verschiedenen Branchen?
Big Data ermöglicht Unternehmen, fundierte Entscheidungen auf Basis von umfangreichen Datenanalysen zu treffen. In der Finanzbranche werden Risikomanagement und Kundenverhalten analysiert, während im Gesundheitswesen Daten zur personalisierten Medizin genutzt werden. In der Einzelhandelsbranche werden Verkaufstrends und Kundenpräferenzen analysiert, um das Angebot zu optimieren.
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Wie beeinflusst die Analyse von Big Data unsere Gesellschaft und Geschäftspraktiken?
Die Analyse von Big Data ermöglicht es Unternehmen, fundierte Entscheidungen zu treffen und ihre Geschäftspraktiken zu optimieren. Sie ermöglicht auch eine personalisierte Kundenansprache und die Entwicklung neuer Produkte und Dienstleistungen. In der Gesellschaft kann die Analyse von Big Data zu Datenschutzbedenken führen und die Art und Weise, wie wir Informationen konsumieren, beeinflussen.
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SQL Mastery for Data Analytics & Reporting John Academy Code
Entdecken Sie die Macht der Daten mit unserem Kurs „SQL Masterclass: SQL für Datenanalyse" . Dieser Kurs richtet sich sowohl an Anfänger als auch an Profis, die SQL für die Datenanalyse verwenden möchten. Erfahren Sie, wie Sie Daten mit SQL effizient strukturieren, verwalten und analysieren. So können Sie datengesteuerte Aufgaben bewältigen und fundierte Entscheidungen treffen. Merkmale: Interaktives Lernen: Nehmen Sie an praktischen SQL-Projekten und -Übungen teil und üben Sie die Manipulati...
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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: 38.51 € | 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 € -
Enterprise Analytics: Optimize Performance, Process, and Decisions Through Big Data
The Definitive Guide to Enterprise-Level Analytics Strategy, Technology, Implementation, and Management Organizations are capturing exponentially larger amounts of data than ever, and now they have to figure out what to do with it. Using analytics, you can harness this data, discover hidden patterns, and use this knowledge to act meaningfully for competitive advantage. Suddenly, you can go beyond understanding “how, when, and where” events have occurred, to understand why – and use this knowledge to reshape the future. Now, analytics pioneer Tom Davenport and the world-renowned experts at the International Institute for Analytics (IIA) have brought together the latest techniques, best practices, and research on analytics in a single primer for maximizing the value of enterprise data. Enterprise Analytics is today’s definitive guide to analytics strategy, planning, organization, implementation, and usage. It covers everything from building better analytics organizations to gathering data; implementing predictive analytics to linking analysis with organizational performance. The authors offer specific insights for optimizing supply chains, online services, marketing, fraud detection, and many other business functions. They support their powerful techniques with many real-world examples, including chapter-length case studies from healthcare, retail, and financial services. Enterprise Analytics will be an invaluable resource for every business and technical professional who wants to make better data-driven decisions: operations, supply chain, and product managers; product, financial, and marketing analysts; CIOs and other IT leaders; data, web, and data warehouse specialists, and many others.
Preis: 22.46 € | Versand*: 0 €
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Wie kann die Nutzung von Big Data dazu beitragen, effizientere Geschäftsentscheidungen zu treffen?
Durch die Analyse großer Datenmengen können Unternehmen Muster und Trends erkennen, die bei der Entscheidungsfindung helfen. Big Data ermöglicht eine genauere Vorhersage von Marktentwicklungen und Kundenverhalten. Durch die Nutzung von Big Data können Unternehmen ihre Prozesse optimieren und Kosten senken.
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Welche Auswirkungen hat die Nutzung von Big Data auf die Wirtschaft und Gesellschaft?
Die Nutzung von Big Data ermöglicht Unternehmen, fundierte Entscheidungen zu treffen und effizienter zu arbeiten. Sie kann jedoch auch zu Datenschutzproblemen und Ungleichheiten führen. In der Gesellschaft kann Big Data dazu beitragen, Probleme wie Kriminalität oder Gesundheitsprobleme besser zu verstehen und anzugehen.
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Welche medizinischen Anwendungen könnten in Zukunft durch die Entwicklung von Künstlicher Intelligenz und Big Data ermöglicht werden?
Durch Künstliche Intelligenz und Big Data könnten personalisierte Medikamente entwickelt werden, die auf individuelle genetische Profile zugeschnitten sind. Diagnosen könnten schneller und genauer gestellt werden, indem große Datenmengen analysiert werden. Zudem könnten präventive Maßnahmen zur Vermeidung von Krankheiten aufgrund von Frühwarnsystemen verbessert werden.
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Hat Data Science Zukunft?
Ja, Data Science hat definitiv Zukunft. Mit der zunehmenden Digitalisierung und dem wachsenden Bedarf an datenbasierten Entscheidungen in Unternehmen wird die Nachfrage nach Data Science-Fachleuten weiter steigen. Zudem ermöglicht Data Science die Entwicklung neuer Technologien und Lösungen in verschiedenen Bereichen wie Gesundheitswesen, Finanzen, Marketing und vielen anderen. Daher wird Data Science auch in Zukunft eine wichtige Rolle spielen.
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