Produkte 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 € -
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 € -
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 €
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Wie entsteht Big Data?
Big Data entsteht durch die Sammlung und Speicherung einer großen Menge von Daten aus verschiedenen Quellen wie Sensoren, Social Media, Transaktionen und mehr. Diese Daten werden dann mithilfe von speziellen Tools und Technologien analysiert und verarbeitet, um Muster, Trends und Erkenntnisse zu identifizieren. Durch die kontinuierliche Erfassung und Analyse von Daten in Echtzeit können Unternehmen fundierte Entscheidungen treffen und ihre Geschäftsprozesse optimieren. Letztendlich ermöglicht Big Data eine tiefere Einblicke in das Verhalten von Kunden, Trends auf dem Markt und ermöglicht die Entwicklung innovativer Produkte und Dienstleistungen.
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Wie funktioniert Big Data?
Wie funktioniert Big Data?
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Was ist Big Data?
Big Data bezieht sich auf große Mengen an Daten, die mit hoher Geschwindigkeit und Vielfalt generiert werden. Diese Daten können aus verschiedenen Quellen stammen, wie zum Beispiel sozialen Medien, Sensoren oder Transaktionen. Big Data ermöglicht es Unternehmen, Muster und Trends zu identifizieren, um fundierte Entscheidungen zu treffen und ihre Geschäftsprozesse zu optimieren.
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Was ist das Big Data?
Was ist das Big Data? Big Data bezieht sich auf die riesigen Mengen an Daten, die in unserer digitalen Welt generiert werden. Diese Daten stammen aus verschiedenen Quellen wie sozialen Medien, Sensoren, Mobilgeräten und mehr. Big Data zeichnet sich durch die 3Vs aus: Volumen, Vielfalt und Geschwindigkeit. Unternehmen nutzen Big Data, um Muster und Trends zu erkennen, fundierte Entscheidungen zu treffen und ihre Geschäftsprozesse zu optimieren. Es erfordert spezielle Tools und Technologien wie Data Mining, maschinelles Lernen und künstliche Intelligenz, um Big Data effektiv zu verarbeiten und zu analysieren.
Ähnliche Suchbegriffe für Big Data:
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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: 7.48 € | Versand*: 0 € -
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: 24.6 € | Versand*: 0 € -
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 € -
DB2 Essentials: Understanding DB2 in a Big Data World
The Easy, Visual Introduction to IBM DB2 Version 10.5 for Linux, UNIX, and WindowsForeword by Judy Huber, Vice President, Distributed Data Servers and Data Warehousing; Director, IBM Canada LaboratoryThis book covers everything you need to get productive with the latest version of IBM DB2 and apply it to today’s business challenges. It discusses key features introduced in DB2 Versions 10.5, 10.1, and 9.7, including improvements in manageability, integration, security, Big Data support, BLU Acceleration, and cloud computing.DB2 Essentials illuminates key concepts with examples drawn from the authors’ extensive experience with DB2 in enterprise environments. Raul F. Chong and Clara Liu explain how DB2 has evolved, what’s new, and how to choose the right products, editions, and tools. Next, they walk through installation, configuration, security, data access, remote connectivity, and day-to-day administration.Each chapter starts with an illustrative overview to introduce its key concepts using a big picture approach. Clearly explained figures are used extensively, and techniques are presented with intuitive screenshots, diagrams, charts, and tables. Case studies illustrate how “theory” is applied in real-life environments, and hundreds of review questions help you prepare for IBM’s newest DB2 certification exams.Coverage includes• Understanding the role of DB2 in Big Data• Preparing for and executing a smooth installation or upgrade• Understanding the DB2 environment, instances, and databases• Configuring client and server connectivity• Working with database objects• Getting started with BLU Acceleration• Implementing security: authentication and authorization• Understanding concurrency and locking• Maintaining, backing up, and recovering data• Using basic SQL in DB2 environments• Diagnosing and solving DB2 problemsThis book is for anyone who plans to work with DB2, including DBAs, system administrators, developers, and consultants. It will be a great resource whether you’re upgrading from an older version of DB2, migrating from a competitive database, or learning your first database platform.
Preis: 29.95 € | Versand*: 0 €
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Wie funktioniert Big Data Analytics?
Wie funktioniert Big Data Analytics? Big Data Analytics beinhaltet die Verarbeitung und Analyse großer Mengen von Daten, um Muster, Trends und Erkenntnisse zu identifizieren. Zunächst werden die Daten gesammelt und gespeichert, dann werden sie mithilfe von speziellen Tools und Algorithmen analysiert. Durch den Einsatz von Data Mining, maschinellem Lernen und künstlicher Intelligenz können Unternehmen wertvolle Einblicke gewinnen und fundierte Entscheidungen treffen. Die Ergebnisse der Analyse können für verschiedene Anwendungen genutzt werden, wie z.B. zur Verbesserung von Produkten und Dienstleistungen, zur Optimierung von Geschäftsprozessen oder zur Vorhersage von zukünftigen Entwicklungen.
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Wo wird Big Data gespeichert?
Big Data wird in speziellen Datenbanken und Datenlagern gespeichert, die für die Verarbeitung und Analyse großer Datenmengen optimiert sind. Oft werden dafür auch Cloud-Speicherlösungen genutzt, die skalierbar sind und eine hohe Verfügbarkeit bieten. Zudem können Unternehmen ihre Big Data in eigenen Rechenzentren oder auf dedizierten Servern speichern. Ein weiterer Trend ist die Nutzung von verteilten Systemen wie Hadoop oder Spark, die es ermöglichen, große Datenmengen auf mehreren Servern zu verteilen und parallel zu verarbeiten. Letztendlich hängt die Wahl des Speicherorts für Big Data von den individuellen Anforderungen und Ressourcen eines Unternehmens ab.
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Wie wichtig ist Big Data?
Wie wichtig ist Big Data? Big Data spielt heutzutage eine entscheidende Rolle in nahezu allen Branchen, da Unternehmen immer mehr Daten sammeln und analysieren, um fundierte Entscheidungen zu treffen. Durch die Analyse großer Datenmengen können Unternehmen wertvolle Einblicke gewinnen, Trends erkennen und ihre Geschäftsstrategien optimieren. Zudem ermöglicht Big Data die Personalisierung von Produkten und Dienstleistungen, um die Bedürfnisse der Kunden besser zu verstehen und zu erfüllen. Insgesamt ist Big Data also von großer Bedeutung für den Erfolg und die Wettbewerbsfähigkeit von Unternehmen in der heutigen digitalen Welt.
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Ist Big Data eine Technologie?
Ist Big Data eine Technologie? Big Data ist eigentlich kein spezifisches Technologieprodukt, sondern vielmehr ein Konzept oder eine Herangehensweise, um große Mengen an Daten zu sammeln, zu speichern, zu analysieren und zu nutzen. Es umfasst verschiedene Technologien und Tools wie Datenbanken, Data Mining, maschinelles Lernen und künstliche Intelligenz, die verwendet werden, um Erkenntnisse aus den Daten zu gewinnen. Daher kann man sagen, dass Big Data eher eine Strategie oder ein Framework ist, das auf verschiedenen Technologien basiert, anstatt eine eigenständige Technologie zu sein. Letztendlich zielt Big Data darauf ab, Unternehmen dabei zu unterstützen, fundierte Entscheidungen auf der Grundlage von Daten zu treffen und Wettbewerbsvorteile zu erlangen.
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