Big Data Fundamentals: Concepts, Drivers & Techniques (The Pearson Service Technology Series from Thomas Erl). Dieser Artikel ist nicht verfügbar.
Sprache: Englisch
Verlag: Pearson, 2016
Serie: Buch 11 von 14 - The Pearson Service Technology Series from Thomas Erl
- Softcover
- Gebraucht

Anbieter: World of Books (was SecondSale), Montgomery, IL, USAWorld of Books (was SecondSale)
AbeBooks-Verkäufer/-in seit 20. Dezember 2007
Zustand: Gebraucht - Befriedigend
EUR 3,15
Artikelbeschreibung vom Verkäufer
Item in good condition and has highlighting/writing on text. Used texts may not contain supplemental items such as CDs, info-trac etc.
Bestandsnummer des Verkäufers 00107055792
- Titel
- Big Data Fundamentals: Concepts, Drivers & Techniques (The Pearson Service Technology Series from Thomas Erl)
- Autor
- Erl, Thomas
- Verlag
- Pearson
- Veröffentlichungsjahr
- 2016
- Zustand
- Good
- Einband
- Softcover
- Sprache
- Englisch
- ISBN-10
- 0134291077
- ISBN-13
- 9780134291079
- Serie
- Buch 11 von 14: The Pearson Service Technology Series from Thomas Erl
“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
„Inhaltsangabe“ gehört möglicherweise zu einer anderen Auflage dieses Titels.
Über die Autorin bzw. den Autor
Wajid Khattak is a Big Data researcher and trainer at Arcitura Education Inc. His areas of interest include Big Data engineering and architecture, data science, machine learning, analytics and SOA. He has extensive .NET software development experience in the domains of business intelligence reporting solutions and GIS.
Wajid completed his MSc in Software Engineering and Security with distinction from Birmingham City University in 2008. Prior to that, in 2003, he earned his BSc (Hons) degree in Software Engineering from Birmingham City University with first-class recognition. He holds MCAD & MCTS (Microsoft), SOA Architect, Big Data Scientist, Big Data Engineer and Big Data Consultant (Arcitura) certifications.
Dr. Paul Buhler is a seasoned professional who has worked in commercial, government and academic environments. He is a respected researcher, practitioner and educator of service-oriented computing concepts, technologies and implementation methodologies. His work in XaaS naturally extends to cloud, Big Data and IoE areas. Dr. Buhler’s more recent work has been focused on closing the gap between business strategy and process execution by leveraging responsive design principles and goal-based execution.
As Chief Scientist at Modus21, Dr. Buhler is responsible for aligning corporate strategy with emerging trends in business architecture and process execution frameworks. He also holds an Affiliate Professorship at the College of Charleston, where he teaches both graduate and undergraduate computer science courses. Dr. Buhler earned his Ph.D. in Computer Engineering at the University of South Carolina. He also holds an MS degree in Computer Science from Johns Hopkins University and a BS in Computer Science from The Citadel.
„Über diesen Titel“ gehört möglicherweise zu einer anderen Auflage dieses Titels.