Big Data Analytics
From Strategic Planning to Enterprise Integration with Tools, Techniques, NoSQL, and Graph
David Loshin
Résumé
Big Data Analytics will assist managers in providing an overview of the drivers for introducing big data technology into the organization and for understanding the types of business problems best suited to big data analytics solutions, understanding the value drivers and benefits, strategic planning, developing a pilot, and eventually planning to integrate back into production within the enterprise.
L'auteur David Loshin
David Loshin is President of Knowledge Integrity, Inc., a company specializing in data management consulting. The author of numerous books on performance computing and data management, including "Master Data Management" (2008) and "Business Intelligence - The Savvy Manager's Guide" (2003), and creator of courses and tutorials on all facets of data management best practices, David is often looked to for thought leadership in the information management industry. Affiliations and Expertise
President, Knowledge Integrity Incorporated, Silver Springs, MD, USA
Sommaire
- Business Drivers for Big Data Analytics
- Business Problems that are Suited to Big Data Solutions
- Organizational Alignment for Big Data
- Developing a Strategic Plan for Integrating Big Data into the Enterprise
- Data Governance: Policies and Processes for Big Data Oversight
- High Performance Analytics Appliances
- Big Data Tools and Techniques
- Developing Big Data Applications
- NoSQL
- Graph Analytics
- Summary
Caractéristiques techniques du livre "Big Data Analytics"
| PAPIER | ||
| Éditeur(s) | Morgan Kaufmann | |
| Auteur(s) | David Loshin | |
| Parution | 30/08/2013 | |
| Nb. de pages | 142 | |
| Format | 22 x 15 | |
| Couverture | Broché | |
| Intérieur | Noir et Blanc | |
| EAN13 | 9780124173194 | |
| ISBN13 | 978-0-1241-7319-4 | |
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Consultez aussi
- Informatique Bases de données
- Informatique Informatique d'entreprise Data warehouse et data mining
- Sciences Mathématiques Mathématiques par matières Analyse Analyse numérique
- Sciences Mathématiques Mathématiques appliquées Mathématiques pour les sciences de la vie Biostatistiques
- Sciences Mathématiques Mathématiques appliquées Méthodes numériques
- Sciences Mathématiques Mathématiques appliquées Statistiques Analyse de données
