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Big data, data mining and machine learning: value creation for business leaders and practitions

By: Dean, Jared.
Series: Wiley Big Data Series. Publisher: New Delhi Wiley India 2014Description: xix, 265 p.ISBN: 9788126550906.Subject(s): Business intelligence - Data Mining | Management - Data processing | Database management - Big Data | Information technology - Management | Database Management - Data MiningDDC classification: 658​.05631
List(s) this item appears in: VR_Healthcare Analytics | Big data | VR_Data Analytics, Data Visualization and Big Data | IT and Decision Science | Big Data_Book Display
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Books Vikram Sarabhai Library
Slot 1870 (2 Floor, East Wing) Non-fiction 658​.05631 D3B4 (Browse shelf) Available 189317

Big data is big business. But having the data and the computational power to process it isn't nearly enough to produce meaningful results. Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners is a complete resource for technology and marketing executives looking to cut through the hype and produce real results that hit the bottom line. Providing an engaging, thorough overview of the current state of big data analytics and the growing trend toward high performance computing architectures, the book is a detail-driven look into how big data analytics can be leveraged to foster positive change and drive efficiency.

With continued exponential growth in data and ever more competitive markets, businesses must adapt quickly to gain every competitive advantage available. Big data analytics can serve as the linchpin for initiatives that drive business, but only if the underlying technology and analysis is fully understood and appreciated by engaged stakeholders. This book provides a view into the topic that executives, managers, and practitioners require, and includes:
A complete overview of big data and its notable characteristics
Details on high performance computing architectures for analytics, massively parallel processing (MPP), and in-memory databases
Comprehensive coverage of data mining, text analytics, and machine learning algorithms
A discussion of explanatory and predictive modeling, and how they can be applied to decision-making processes

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