Produkte zum Begriff Big Data Analytics:
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Applied Business Analytics: Integrating Business Process, Big Data, and Advanced Analytics
Bridge the gap between analytics and execution, and actually translate analytics into better business decision-making! Now that you've collected data and crunched numbers, Applied Business Analytics reveals how to fully apply the information and knowledge you've gleaned from quants and tech teams. Nathaniel Lin explains why "analytics value chains" often break due to organizational and cultural issues, and offers "in the trenches" guidance for overcoming these obstacles. You'll discover why a special breed of "analytics deciders" is indispensable for any organization that seeks to compete on analytics… how to become one of those deciders… and how to identify, foster, support, empower, and reward others to join you. Lin draws on actual cases and examples from his own experience, augmenting them with hands-on examples and exercises to integrate analytics at all levels: from top-level business questions to low-level technical details. Along the way, you'll learn how to bring together analytics team members with widely diverse goals, knowledge, and backgrounds. Coverage includes: How analytical and conventional decision making differ — and the challenging implications How to determine who your analytics deciders are, and ought to be Proven best practices for actually applying analytics to decision-making How to optimize your use of analytics as an analyst, manager, executive, or C-level officer Applied Business Analytics will be invaluable to wide audiences of professionals, decision-makers, and consultants involved in analytics, including Chief Analytics Officers, Chief Data Officers, Chief Scientists, Chief Marketing Officers, Chief Risk Officers, Chief Strategy Officers, VPs of Analytics and/or Big Data, data scientists, business strategists, and line of business executives. It will also be exceptionally useful to students of analytics in any graduate, undergraduate, or certificate program, including candidates for INFORMS certification.
Preis: 29.95 € | Versand*: 0 € -
Applied Business Analytics: Integrating Business Process, Big Data, and Advanced Analytics
Bridge the gap between analytics and execution, and actually translate analytics into better business decision-making! Now that you've collected data and crunched numbers, Applied Business Analytics reveals how to fully apply the information and knowledge you've gleaned from quants and tech teams. Nathaniel Lin explains why "analytics value chains" often break due to organizational and cultural issues, and offers "in the trenches" guidance for overcoming these obstacles. You'll discover why a special breed of "analytics deciders" is indispensable for any organization that seeks to compete on analytics… how to become one of those deciders… and how to identify, foster, support, empower, and reward others to join you. Lin draws on actual cases and examples from his own experience, augmenting them with hands-on examples and exercises to integrate analytics at all levels: from top-level business questions to low-level technical details. Along the way, you'll learn how to bring together analytics team members with widely diverse goals, knowledge, and backgrounds. Coverage includes: How analytical and conventional decision making differ — and the challenging implications How to determine who your analytics deciders are, and ought to be Proven best practices for actually applying analytics to decision-making How to optimize your use of analytics as an analyst, manager, executive, or C-level officer Applied Business Analytics will be invaluable to wide audiences of professionals, decision-makers, and consultants involved in analytics, including Chief Analytics Officers, Chief Data Officers, Chief Scientists, Chief Marketing Officers, Chief Risk Officers, Chief Strategy Officers, VPs of Analytics and/or Big Data, data scientists, business strategists, and line of business executives. It will also be exceptionally useful to students of analytics in any graduate, undergraduate, or certificate program, including candidates for INFORMS certification.
Preis: 39.58 € | Versand*: 0 € -
Analytics Across the Enterprise: How IBM Realizes Business Value from Big Data and Analytics
How to Transform Your Organization with Analytics: Insider Lessons from IBM’s Pioneering ExperienceAnalytics is not just a technology: It is a better way to do business. Using analytics, you can systematically inform human judgment with data-driven insight. This doesn’t just improve decision-making: It also enables greater innovation and creativity in support of strategy. Your transformation won’t happen overnight; however, it is absolutely achievable, and the rewards are immense.This book demystifies your analytics journey by showing you how IBM has successfully leveraged analytics across the enterprise, worldwide. Three of IBM’s pioneering analytics practitioners share invaluable real-world perspectives on what does and doesn’t work and how you can start or accelerate your own transformation. This book provides an essential framework for becoming a smarter enterprise and shows through 31 case studies how IBM has derived value from analytics throughout its business.Coverage Includes Creating a smarter workforce through big data and analytics More effectively optimizing supply chain processes Systematically improving financial forecasting Managing financial risk, increasing operational efficiency, and creating business value Reaching more B2B or B2C customers and deepening their engagement Optimizing manufacturing and product management processes Deploying your sales organization to increase revenue and effectiveness Achieving new levels of excellence in services delivery and reducing risk Transforming IT to enable wider use of analytics “Measuring the immeasurable” and filling gaps in imperfect data Whatever your industry or role, whether a current or future leader, analytics can make you smarter and more competitive. Analytics Across the Enterprise shows how IBM did it--and how you can, too. Learn more about IBM Analytics
Preis: 13.9 € | Versand*: 0 € -
Analytics Across the Enterprise: How IBM Realizes Business Value from Big Data and Analytics
How to Transform Your Organization with Analytics: Insider Lessons from IBM’s Pioneering ExperienceAnalytics is not just a technology: It is a better way to do business. Using analytics, you can systematically inform human judgment with data-driven insight. This doesn’t just improve decision-making: It also enables greater innovation and creativity in support of strategy. Your transformation won’t happen overnight; however, it is absolutely achievable, and the rewards are immense.This book demystifies your analytics journey by showing you how IBM has successfully leveraged analytics across the enterprise, worldwide. Three of IBM’s pioneering analytics practitioners share invaluable real-world perspectives on what does and doesn’t work and how you can start or accelerate your own transformation. This book provides an essential framework for becoming a smarter enterprise and shows through 31 case studies how IBM has derived value from analytics throughout its business.Coverage Includes Creating a smarter workforce through big data and analytics More effectively optimizing supply chain processes Systematically improving financial forecasting Managing financial risk, increasing operational efficiency, and creating business value Reaching more B2B or B2C customers and deepening their engagement Optimizing manufacturing and product management processes Deploying your sales organization to increase revenue and effectiveness Achieving new levels of excellence in services delivery and reducing risk Transforming IT to enable wider use of analytics “Measuring the immeasurable” and filling gaps in imperfect data Whatever your industry or role, whether a current or future leader, analytics can make you smarter and more competitive. Analytics Across the Enterprise shows how IBM did it--and how you can, too. Learn more about IBM Analytics
Preis: 18.18 € | 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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Wie können Big Data Analytics-Technologien im Projektmanagement eingesetzt werden?
Big Data Analytics-Technologien können im Projektmanagement eingesetzt werden, um große Mengen an Daten aus verschiedenen Quellen zu sammeln und zu analysieren. Dies ermöglicht es Projektmanagern, Trends und Muster zu erkennen, Risiken frühzeitig zu identifizieren und fundierte Entscheidungen zu treffen. Darüber hinaus können Big Data Analytics-Technologien auch zur Vorhersage von Projektverzögerungen oder zur Optimierung von Ressourcen eingesetzt werden.
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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?
Ähnliche Suchbegriffe für 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: 22.46 € | 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 € -
Data Analytics with Spark Using Python
Solve Data Analytics Problems with Spark, PySpark, and Related Open Source ToolsSpark is at the heart of today’s Big Data revolution, helping data professionals supercharge efficiency and performance in a wide range of data processing and analytics tasks. In this guide, Big Data expert Jeffrey Aven covers all you need to know to leverage Spark, together with its extensions, subprojects, and wider ecosystem.Aven combines a language-agnostic introduction to foundational Spark concepts with extensive programming examples utilizing the popular and intuitive PySpark development environment. This guide’s focus on Python makes it widely accessible to large audiences of data professionals, analysts, and developers—even those with little Hadoop or Spark experience.Aven’s broad coverage ranges from basic to advanced Spark programming, and Spark SQL to machine learning. You’ll learn how to efficiently manage all forms of data with Spark: streaming, structured, semi-structured, and unstructured. Throughout, concise topic overviews quickly get you up to speed, and extensive hands-on exercises prepare you to solve real problems.Coverage includes:• Understand Spark’s evolving role in the Big Data and Hadoop ecosystems• Create Spark clusters using various deployment modes• Control and optimize the operation of Spark clusters and applications• Master Spark Core RDD API programming techniques• Extend, accelerate, and optimize Spark routines with advanced API platform constructs, including shared variables, RDD storage, and partitioning• Efficiently integrate Spark with both SQL and nonrelational data stores• Perform stream processing and messaging with Spark Streaming and Apache Kafka• Implement predictive modeling with SparkR and Spark MLlib
Preis: 35.3 € | Versand*: 0 € -
Data Analytics with Spark Using Python
Solve Data Analytics Problems with Spark, PySpark, and Related Open Source ToolsSpark is at the heart of today’s Big Data revolution, helping data professionals supercharge efficiency and performance in a wide range of data processing and analytics tasks. In this guide, Big Data expert Jeffrey Aven covers all you need to know to leverage Spark, together with its extensions, subprojects, and wider ecosystem.Aven combines a language-agnostic introduction to foundational Spark concepts with extensive programming examples utilizing the popular and intuitive PySpark development environment. This guide’s focus on Python makes it widely accessible to large audiences of data professionals, analysts, and developers—even those with little Hadoop or Spark experience.Aven’s broad coverage ranges from basic to advanced Spark programming, and Spark SQL to machine learning. You’ll learn how to efficiently manage all forms of data with Spark: streaming, structured, semi-structured, and unstructured. Throughout, concise topic overviews quickly get you up to speed, and extensive hands-on exercises prepare you to solve real problems.Coverage includes:• Understand Spark’s evolving role in the Big Data and Hadoop ecosystems• Create Spark clusters using various deployment modes• Control and optimize the operation of Spark clusters and applications• Master Spark Core RDD API programming techniques• Extend, accelerate, and optimize Spark routines with advanced API platform constructs, including shared variables, RDD storage, and partitioning• Efficiently integrate Spark with both SQL and nonrelational data stores• Perform stream processing and messaging with Spark Streaming and Apache Kafka• Implement predictive modeling with SparkR and Spark MLlib
Preis: 35.3 € | Versand*: 0 €
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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.
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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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