Description
“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, PhD The 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 science
- Understanding the business motivations and drivers behind Big Data adoption, from operational improvements through innovation
- Planning strategic, business-driven Big Data initiatives
- Addressing considerations such as data management, governance, and security
- Recognizing the 5 “V” characteristics of datasets in Big Data environments: volume, velocity, variety, veracity, and value
- Clarifying Big Data’s relationships with OLTP, OLAP, ETL, data warehouses, and data marts
- Working with Big Data in structured, unstructured, semi-structured, and metadata formats
- Increasing value by integrating Big Data resources with corporate performance monitoring
- Understanding how Big Data leverages distributed and parallel processing
- Using NoSQL and other technologies to meet Big Data’s distinct data processing requirements
- Leveraging statistical approaches of quantitative and qualitative analysis
- Applying computational analysis methods, including machine learning
LangueenVersionCouverture rigideDate de sortie initiale20 janvier 2016Nombre de pages240IllustrationsNon
Personnes impliquées
Auteur principal
Thomas Erl
Deuxième auteur
Wajid Khattak
Coauteur
Paul Buhler
Editeur principal
PREN
Informations sur le fabricant
Nom du fabricant[email protected]Adresse du fabricantSt.-Martin-Straße 82 | 81541| München| DEAdresse électronique du fabricant[email protected]Informations sur le fabricantLes informations du fabricant ne sont actuellement pas disponibles
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Hauteur de l’emballage20 mmHauteur du produit30 mmLargeur d’emballage179 mmLargeur du produit178 mmLivre d‘étudeOuiLongueur d’emballage229 mmLongueur du produit232 mmPoids de l’emballage388 gPolice de caractères extra largeNonÉdition24001
EAN
EAN9780134291079
Sécurité des produits
Opérateur économique responsable dans l’UE
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Anglais
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