Produkt zum Begriff Big Data:
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Big Data Demystified
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. 'Big Data' refers to a new class of data, to which 'big' doesn't quite do it justice. Much like an ocean is more than simply a deeper swimming pool, big data is fundamentally different to traditional data and needs a whole new approach. Packed with examples and case studies, this clear, comprehensive book will show you how to accumulate and utilise 'big data' in order to develop your business strategy. Big Data Demystified is your practical guide to help you draw deeper insights from the vast information at your fingertips; you will be able to understand customer motivations, speed up production lines, and even offer personalised experiences to each and every customer. With 20 years of industry experience, David Stephenson shows how big data can give you the best competitive edge, and why it is integral to the future of your business.
Preis: 16.04 € | Versand*: 0 € -
Understanding Big Data Scalability: Big Data Scalability Series, Part I
Get Started Scaling Your Database Infrastructure for High-Volume Big Data Applications “Understanding Big Data Scalability presents the fundamentals of scaling databases from a single node to large clusters. It provides a practical explanation of what ‘Big Data’ systems are, and fundamental issues to consider when optimizing for performance and scalability. Cory draws on many years of experience to explain issues involved in working with data sets that can no longer be handled with single, monolithic relational databases.... His approach is particularly relevant now that relational data models are making a comeback via SQL interfaces to popular NoSQL databases and Hadoop distributions.... This book should be especially useful to database practitioners new to scaling databases beyond traditional single node deployments.” —Brian O’Krafka, software architect Understanding Big Data Scalability presents a solid foundation for scaling Big Data infrastructure and helps you address each crucial factor associated with optimizing performance in scalable and dynamic Big Data clusters. Database expert Cory Isaacson offers practical, actionable insights for every technical professional who must scale a database tier for high-volume applications. Focusing on today’s most common Big Data applications, he introduces proven ways to manage unprecedented data growth from widely diverse sources and to deliver real-time processing at levels that were inconceivable until recently. Isaacson explains why databases slow down, reviews each major technique for scaling database applications, and identifies the key rules of database scalability that every architect should follow. You’ll find insights and techniques proven with all types of database engines and environments, including SQL, NoSQL, and Hadoop. Two start-to-finish case studies walk you through planning and implementation, offering specific lessons for formulating your own scalability strategy. Coverage includes Understanding the true causes of database performance degradation in today’s Big Data environments Scaling smoothly to petabyte-class databases and beyond Defining database clusters for maximum scalability and performance Integrating NoSQL or columnar databases that aren’t “drop-in” replacements for RDBMSes Scaling application components: solutions and options for each tier Recognizing when to scale your data tier—a decision with enormous consequences for your application environment Why data relationships may be even more important in non-relational databases Why virtually every database scalability implementation still relies on sharding, and how to choose the best approach How to set clear objectives for architecting high-performance Big Data implementations The Big Data Scalability Series is a comprehensive, four-part series, containing information on many facets of database performance and scalability. Understanding Big Data Scalability is the first book in the series. Learn more and join the conversation about Big Data scalability at bigdatascalability.com.
Preis: 6.41 € | Versand*: 0 € -
Jankowski, Timo: Fußball - Von Big Data zu Smart Data
Fußball - Von Big Data zu Smart Data , Das Thema Big Data ist unaufhaltsam in die Fußballwelt eingezogen und wird mit Sicherheit auch nicht mehr verschwinden. Es wird weiterhin an Bedeutung gewinnen, da die Datenqualität und die praktische Umsetzung dieser Daten bereits zahlreiche beeindruckende Erfolge vorweisen können. Zu Beginn des Buchs wird auf die Problematik des Schwarz-Weiß-Denkens, das im Fußball weit verbreitet ist, eingegangen. Im zweiten Teil rückt dann das Thema Big Data im Fußball in den Vordergrund. Dies geschieht vor allem immer im Hinblick auf die Umwandlung in Smart Data mit vielen praktischen Beispielen, sodass jeder Trainer und Interessierte zahlreiche Anregungen für die eigene Arbeit in der Planung, auf dem Platz und in der Evaluierung bekommt. Zahlreiche Key-Performance-Indikatoren (KPIs) werden unter die Lupe genommen und es wird aufgezeigt, wie Datenanalyse auf dem Weg zum Erfolg helfen kann. Ziel dieses Werks ist es, das Thema Big Data im Fußball zu entmystifizieren, weshalb im letzten Abschnitt die erfolgreiche Qualifikation der Juniorennationalmannschaft von Fidschi für die U20-Weltmeisterschaft 2023 beschrieben wird. Dieses Beispiel zeigt, wie die richtige Mischung aus objektiven Daten und den menschlichen Komponenten in der Praxis zum Erfolg führen kann. Dieses Buch plädiert dafür, die tief verwurzelten Werte und die Ursprünglichkeit des Fußballs unbedingt beizubehalten und zeigt auf, wie sich beide Seiten - Bauchgefühl und Datenanalyse - gewinnbringend miteinander verbinden lassen. Fußball - von Big Data zu Smart Data ist DAS Standardwerk für alle Trainer, die das Thema Big Data angehen wollen und Tipps für die Umsetzung auf dem Platz benötigen. , Bücher > Bücher & Zeitschriften
Preis: 28.00 € | Versand*: 0 € -
Digital Exhaust: What Everyone Should Know About Big Data, Digitization and Digitally Driven Innovation
Will "Big Data" supercharge the economy, tyrannize us, or both? Data Exhaust is the definitive primer for everyone who wants to understand all the implications of Big Data, digitally driven innovation, and the accelerating Internet Economy. Renowned digital expert Dale Neef clearly explains: What Big Data really is, and what's new and different about it How Big Data works, and what you need to know about Big Data technologies Where the data is coming from: how Big Data integrates sources ranging from social media to machine sensors, smartphones to financial transactions How companies use Big Data analytics to gain a more nuanced, accurate picture of their customers, their own performance, and the newest trends How governments and individual citizens can also benefit from Big Data How to overcome obstacles to success with Big Data – including poor data that can magnify human error A realistic assessment of Big Data threats to employment and personal privacy, now and in the future Neef places the Big Data phenomenon where it belongs: in the context of the broader global shift to the Internet economy, with all that implies. By doing so, he helps businesses plan Big Data strategy more effectively – and helps citizens and policymakers identify sensible policies for preventing its misuse. By conservative estimate, the global Big Data market will soar past $50 billion by 2018. But those direct expenses represent just the "tip of the iceberg" when it comes to Big Data's impact. Big Data is now of acute strategic interest for every organization that aims to succeed – and it is equally important to everyone else. Whoever you are, Data Exhaust tells you exactly what you need to know about Big Data – and what to do about it, too.
Preis: 22.46 € | Versand*: 0 €
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Warum ist Big Data so wichtig?
Warum ist Big Data so wichtig? Big Data ist wichtig, weil es Unternehmen dabei hilft, fundierte Entscheidungen zu treffen, indem es ihnen Einblicke in Trends, Muster und Verhaltensweisen ihrer Kunden liefert. Durch die Analyse großer Datenmengen können Unternehmen auch Effizienzsteigerungen vornehmen, Kosten senken und ihre Wettbewerbsfähigkeit verbessern. Zudem ermöglicht Big Data die Personalisierung von Produkten und Dienstleistungen, was zu einer besseren Kundenzufriedenheit führt. Nicht zuletzt spielt Big Data eine wichtige Rolle bei der Entwicklung neuer Technologien und Innovationen in verschiedenen Branchen.
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Was sind die Herausforderungen und Chancen der Nutzung von Big Data für Unternehmen?
Die Herausforderungen der Nutzung von Big Data für Unternehmen sind die Sicherstellung der Datenqualität, der Datenschutz und die Integration von verschiedenen Datenquellen. Die Chancen liegen in der Möglichkeit, fundierte Entscheidungen auf Basis von Daten zu treffen, die Identifizierung neuer Geschäftsmöglichkeiten und die Optimierung von Prozessen. Unternehmen können durch die Nutzung von Big Data ihre Wettbewerbsfähigkeit steigern und innovative Produkte und Dienstleistungen entwickeln.
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Was sind die Vorteile und Herausforderungen bei der Nutzung von Big Data für Unternehmen?
Die Vorteile von Big Data für Unternehmen sind die Möglichkeit, fundierte Entscheidungen auf Basis von Daten zu treffen, die Identifizierung von Trends und Mustern, sowie die Verbesserung der Kundenerfahrung. Die Herausforderungen liegen in der Sicherstellung der Datenqualität, dem Schutz der Privatsphäre der Nutzer und der Bewältigung der enormen Datenmengen. Es erfordert außerdem spezialisierte Fachkräfte und die richtige Infrastruktur, um Big Data effektiv nutzen zu können.
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Was sind die potenziellen Vorteile und Herausforderungen beim Umgang mit Big Data in verschiedenen Branchen?
Potenzielle Vorteile von Big Data in verschiedenen Branchen sind die Möglichkeit, fundierte Entscheidungen zu treffen, Effizienz zu steigern und neue Geschäftsmöglichkeiten zu identifizieren. Herausforderungen können Datenschutzbedenken, hohe Kosten für Infrastruktur und Fachkräftemangel sein. Eine erfolgreiche Implementierung erfordert daher eine klare Strategie, angemessene Ressourcen und kontinuierliche Schulungen.
Ähnliche Suchbegriffe für Big Data:
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Big Data Fundamentals: Concepts, Drivers & Techniques
“This text should be required reading for everyone in contemporary business.” --Peter Woodhull, CEO, Modus21 “The one book that clearly describes and links Big Data concepts to business utility.” --Dr. Christopher Starr, PhD“Simply, this is the best Big Data book on the market!” --Sam Rostam, Cascadian IT Group“...one of the most contemporary approaches I’ve seen to Big Data fundamentals...” --Joshua M. Davis, PhDThe Definitive Plain-English Guide to Big Data for Business and Technology Professionals Big Data Fundamentals provides a pragmatic, no-nonsense introduction to Big Data. Best-selling IT author Thomas Erl and his team clearly explain key Big Data concepts, theory and terminology, as well as fundamental technologies and techniques. All coverage is supported with case study examples and numerous simple diagrams. The authors begin by explaining how Big Data can propel an organization forward by solving a spectrum of previously intractable business problems. Next, they demystify key analysis techniques and technologies and show how a Big Data solution environment can be built and integrated to offer competitive advantages.Discovering Big Data’s fundamental concepts and what makes it different from previous forms of data analysis and data scienceUnderstanding the business motivations and drivers behind Big Data adoption, from operational improvements through innovationPlanning strategic, business-driven Big Data initiativesAddressing considerations such as data management, governance, and securityRecognizing the 5 “V” characteristics of datasets in Big Data environments: volume, velocity, variety, veracity, and valueClarifying Big Data’s relationships with OLTP, OLAP, ETL, data warehouses, and data martsWorking with Big Data in structured, unstructured, semi-structured, and metadata formatsIncreasing value by integrating Big Data resources with corporate performance monitoringUnderstanding how Big Data leverages distributed and parallel processingUsing NoSQL and other technologies to meet Big Data’s distinct data processing requirementsLeveraging statistical approaches of quantitative and qualitative analysisApplying computational analysis methods, including machine learning
Preis: 18.18 € | 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: 29.95 € | Versand*: 0 € -
Big Data Demystified
Big Data is a big topic, based on simple principles. Guided by leading expert in the field, David Stephenson, you will be amazed at how you can transform your company, and significantly improve KPIs across a broad range of business units and applications.Find out how an ecommerce company avoided two million product returns per year, how a newspaper saw triple-digit annual growth in digital subscriptions, how researchers in England learned to better detect pending cardiovascular problems, and how AI programs taught themselves to win games using techniques that even their human programmers didn’t understand, all thanks to big data. Find out also how one company realized it could swap a million dollar hardware system with a twenty thousand dollar replacement.With simple and straightforward chapters that allow you to map examples onto your own business, Big Data Demystified will help you:· Know which data is most useful to collect now and why it’s important to start collecting that data as soon as possible.· Understand big data and data science and how they can help you reach your business goals and gain competitive advantage.· Use big data to understand where you are now and how you can improve in the future.· Understand factors in choosing a big data system, including whether to go with cloud-based solutions.· Construct your big data team in a way that supports an effective strategy and helps make your business more data-driven.BIG DATA MAKES A BIG DIFFERENCE “ Read this book! It is an essential guide to using data in a practical way that drives results." Ian McHenry, CEO Beyond Pricing “ This is the book we’ve been missing: big data explained without the complexity.” Marc Salomon, Professor in Decision Sciences and Dean at University of Amsterdam Business School " Big Data for the rest of us! I have never come across a book that is so full of practical advice, actionable examples and helpful explanations. Read this one book and start executing Big Data at your workplace tomorrow!" Tobias Wann CEO at @Leisure Group
Preis: 21.39 € | Versand*: 0 € -
Big Data Demystified
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. 'Big Data' refers to a new class of data, to which 'big' doesn't quite do it justice. Much like an ocean is more than simply a deeper swimming pool, big data is fundamentally different to traditional data and needs a whole new approach. Packed with examples and case studies, this clear, comprehensive book will show you how to accumulate and utilise 'big data' in order to develop your business strategy. Big Data Demystified is your practical guide to help you draw deeper insights from the vast information at your fingertips; you will be able to understand customer motivations, speed up production lines, and even offer personalised experiences to each and every customer. With 20 years of industry experience, David Stephenson shows how big data can give you the best competitive edge, and why it is integral to the future of your business.
Preis: 16.04 € | Versand*: 0 €
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Was sind die potenziellen Auswirkungen von Big Data auf die Datenschutzgesetze und die Privatsphäre von Individuen?
Big Data kann dazu führen, dass persönliche Daten in großem Umfang gesammelt und analysiert werden, was die Privatsphäre gefährden kann. Datenschutzgesetze müssen möglicherweise angepasst werden, um den Schutz der persönlichen Daten in einer Big Data-Umgebung zu gewährleisten. Es besteht die Gefahr, dass individuelle Rechte auf Privatsphäre und Datenschutz durch den Einsatz von Big Data eingeschränkt werden könnten.
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Was macht ein Data Analyst?
Ein Data Analyst sammelt, analysiert und interpretiert große Mengen von Daten, um Einblicke und Trends zu identifizieren. Sie verwenden statistische Methoden und Software, um Muster in den Daten zu erkennen und Geschäftsentscheidungen zu unterstützen. Data Analysts erstellen Berichte, Dashboards und Visualisierungen, um komplexe Informationen verständlich darzustellen. Sie arbeiten eng mit anderen Teams zusammen, um Daten zu verstehen und Empfehlungen für Verbesserungen oder Optimierungen zu geben. Insgesamt helfen Data Analysts dabei, datengesteuerte Entscheidungen zu treffen und das Geschäftswachstum voranzutreiben.
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Wann ist Data Luv geboren?
Wann ist Data Luv geboren?
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Sind Data Warehouses spaltenorientiert?
Data Warehouses können sowohl spaltenorientiert als auch zeilenorientiert sein. Bei spaltenorientierten Data Warehouses werden die Daten nach Spalten gruppiert und gespeichert, was Vorteile bei der Aggregation und Analyse großer Datenmengen bietet. Zeilenorientierte Data Warehouses hingegen speichern die Daten nach Zeilen und eignen sich besser für Transaktionsverarbeitung und schnellen Zugriff auf einzelne Datensätze. Die Wahl zwischen spalten- und zeilenorientierter Speicherung hängt von den spezifischen Anforderungen und Nutzungsszenarien des Data Warehouses ab.
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