Kniha Data and Analytics Playbook Lowell Fryman

Data and Analytics Playbook

Proven Methods for Governed Data and Analytic Quality

Jazyk: Angličtina
Vazba: Brožovaná
Vydavatel: Elsevier Books
Dostupnost: Skladem u dodavatele
Odesíláme za 10-18 dnů
1 458
The Data and Analytics Playbook: Proven Methods for Governed Data and Analytic Quality explores the...

Informace o knize

Jazyk
Angličtina
Vazba
Kniha - Brožovaná
Vydáno
2016
Stránek
292
EAN
9780128023075
ISBN
0128023074
Enbook ID
02820050
Vydavatel
Hmotnost
590
Rozměry
236 x 193 x 15

Kompletní popis

The Data and Analytics Playbook: Proven Methods for Governed Data and Analytic Quality explores the way in which data continues to dominate budgets, along with the varying efforts made across a variety of business enablement projects, including applications, web and mobile computing, big data analytics, and traditional data integration. The book teaches readers how to use proven methods and accelerators to break through data obstacles to provide faster, higher quality delivery of mission critical programs. Drawing upon years of practical experience, and using numerous examples and an easy to understand playbook, Lowell Fryman, Gregory Lampshire, and Dan Meers discuss a simple, proven approach to the execution of multiple data oriented activities. In addition, they present a clear set of methods to provide reliable governance, controls, risk, and exposure management for enterprise data and the programs that rely upon it, and discuss a cost-effective approach to providing sustainable governance and quality outcomes that enhance project delivery, while also ensuring ongoing controls. Example activities, templates, outputs, resources, and roles are explored, along with different organizational models in common use today and how they can be mapped to leverage playbook data governance throughout the organization. Provides a mature and proven playbook approach (methodology) to enabling data governance that supports agile implementationFeatures specific examples of current industry challenges in enterprise risk management, including anti-money laundering and fraud prevention Describes business benefit measures and funding approaches using exposure based cost models that augment risk models for cost avoidance analysis, and accelerated delivery approaches using data integration sprints for application, integration, and information delivery success

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