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Data and Analytics Playbook: Proven Methods for Governed Data and Analytic Quality [Pehme köide]

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(Managing Director, K2 Solutions, USA), (President, K2 Solutions, USA), (Former Professor at Daniels College of Business, Denver University, Denver, CO, USA)
  • Formaat: Paperback / softback, 292 pages, kõrgus x laius: 235x191 mm, kaal: 520 g
  • Ilmumisaeg: 08-Sep-2016
  • Kirjastus: Morgan Kaufmann Publishers In
  • ISBN-10: 0128023074
  • ISBN-13: 9780128023075
Teised raamatud teemal:
Data and Analytics Playbook: Proven Methods for Governed Data and Analytic QualitySuurem pilt
  • Formaat: Paperback / softback, 292 pages, kõrgus x laius: 235x191 mm, kaal: 520 g
  • Ilmumisaeg: 08-Sep-2016
  • Kirjastus: Morgan Kaufmann Publishers In
  • ISBN-10: 0128023074
  • ISBN-13: 9780128023075
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9780128023075.html
Märksõnad:

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 implementation
  • Features 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

Arvustused

"...a guide to proper implementation of data management methods and procedures for modern data usage and exploitation...If you are at all involved in your organizations data management and analytics practice, do yourself a favor and grab a copy of this book today." --Data and Technology Today

Muu info

This book presents methods that provide reliable governance, controls, and risk and exposure management for enterprise data and the programs that rely on it
Author Biographies xi
Acknowledgments xiii
Introduction xv
Chapter 1 Purpose, Scope and Audience
1(22)
Spotting the Need for Data and Analytics Governance: Industry Examples
1(7)
Industry: You and Your Country
1(1)
Industry: Manufacturing
2(2)
Industry: Financial Services
4(2)
Industry: Healthcare
6(2)
What This Book Is About and Why It Is Needed Now
8(2)
Basic Concepts
10(8)
Information and Data Management
11(1)
Business Intelligence
12(1)
Math, Statistics, Data Mining, Artificial Intelligence, Analytics, and More
13(1)
Big Data, NoSQL, Data Scientists, Clouds and Social Media
14(2)
Maturity Model
16(2)
The Play book as an Organizing Process Model
18(1)
What You Can Get From This Book
19(2)
Summary
21(2)
Chapter 2 Executive Call to Action---How Chief Data Officers and Business Sponsors Can Empower Results
23(22)
Executive Call to Action---What Do We Need From You?
23(3)
Scope and Focus Area Definition
26(1)
Traditional Approach to (Data) Governance
27(3)
Data Leadership Cycle---Framing Your Mandate
30(2)
Taking a More Sustainable Approach
32(1)
Data Leadership Roles---Leveraging More Than the CDO---The Power of Data Officers
33(10)
Chiefs of Data, Governance and Analytics
33(2)
Demand Management Model
35(3)
Modeling Effective Communication
38(5)
Summing It Up
43(2)
Chapter 3 Assessing Conditions, Controls and Capabilities
45(20)
Assessment Methods
53(3)
Assessing Data Controls: Audit and Balance Controls
56(1)
Controls Reporting---ABC Control Levels
57(1)
Capability Measurement
58(1)
Data and Analytic Conditions Reporting---A Risk and Exposure Approach
59(2)
Overall Reporting and Visualization
61(2)
Summary
63(2)
Chapter 4 Detailed Playbook Activities
65(72)
Playbook Framework: Capability Orientation
65(3)
Comparative Views of Industry Maturity Models
65(3)
Playbook Framework: Capabilities
68(3)
Playbook Framework: Activities
71(1)
Playbook Framework
72(65)
Chapter 5 Aligning the Language of Business: The Business Glossary
137(22)
Why Do We Need a Business Glossary?
137(3)
What Is a Business Glossary?
140(1)
The Glossary Is a Critical Deliverable of the Data Governance Team
141(3)
Identifying Users of the Business Glossary
144(1)
Creating the Business Glossary Structure
145(3)
Initial Attributes of the Glossary
145(3)
The Standards of a Business Glossary
148(1)
Creating Business Terms Definitions and Term Names
148(2)
Term Definition
149(1)
Term Name
150(1)
Best Practices
150(5)
Business Term Definition Recommendations
152(3)
Creating Glossary Taxonomies and Hierarchies (Ontology/Taxonomy)
155(2)
Business Glossary for Big Data Analytics
157(2)
Chapter 6 The Business Data Governance Toolkit
159(18)
Chapter Overview
159(2)
Data Governance Technology Considerations
161(2)
Method for Technology Selection Overview
163(2)
Process for Tool Selection
164(1)
Process Steps
164(1)
Categories and Sections for DG Technology Selection
165(4)
Process for Evaluation Scoring
169(4)
What Happens After Scoring (We Are Done, Right?)
173(1)
Technology Leaders to Consider Today
174(3)
Chapter 7 Playbook Deployment
177(22)
What Do We Mean by Deployment?
177(8)
Mapping Your Deployment Priorities
185(1)
The Overall Process of Deployment Planning
186(1)
Deployment Patterns
187(3)
Data Cycle
187(1)
Data Sprints
188(2)
Communicating Data Sprints
190(1)
Data Risk and Exposure
191(3)
Deployment Scoping and Planning
194(3)
Conclusion
197(2)
Chapter 8 Data Governance as an Operations Process
199(1)
Operations
199(6)
Report Creation
200(1)
Service Center
201(1)
Finance and Accounting
202(1)
Data Governance Operational Model
203(2)
Planning and Acquiring the Budget
205(4)
Ramping
205(1)
Ongoing
206(1)
Addressing Concerns
207(2)
Iterations
209(1)
Extending the Reach
210(11)
Continuous Performance Improvement
210(1)
Audit and Compliance
211(2)
"Metrics" Projects
213(2)
IT Projects (eg, Project-Level Data Governance)
215(2)
Enterprise Architecture
217(1)
Labeling for Success
218(2)
Cashing the Check
220(1)
Corporate Politics
221(8)
IT Wants to Own Data Governance
222(1)
Business Groups Are Too Busy
223(1)
Lack of Senior Management Buy-In
224(1)
Everyone Wants to Do It Their Way
225(1)
Data Stewards Have No Idea What to Do and Don't Care
226(1)
The Wrong People Run Data Governance
227(2)
Customizing and Maintaining the Playbook
229(1)
Types of Customizations
230(1)
Customization and Maintenance Process
231(1)
Update Frequency
232(1)
Update Deployment
232
Lowell is responsible for directing thought leadership and advisory services in the Customer Success practice of Collibra. He has been a practitioner in the data management industry for three decades and is recognized as a leader in data governance, analytics and data quality having hands-on experience with implementations across most industries. Lowell is a co-author of the book Business Metadata; Capturing Enterprise Knowledge”. Lowell is a past adjunct professor at Daniels College of Business, Denver University, a past President and current VP of Education for DAMA-I Rocky Mountain Chapter (RMC), a DAMA-I Charter member and member of the Data Governance Professionals Organization. He is also an author and reviewer on the DAMA-I Data Management Book of Knowledge (DMBOK). He focuses on practical data governance practices and has trained thousands of professionals in data governance, data warehousing, data management and data quality techniques. You can read his Data Governance Blogs at https://www.collibra.com/blog/ Gregory Lampshire has started and led consulting practices and product development efforts in multiple industries including financial services, healthcare, life sciences, telecommunications and energy. His work in work in playbook development and deployment extends to multiple data sprints addressing complex financial crimes detection and prevention solutions in large financial services institutions. He has a strong background in advanced sales and marketing strategy and analytics, sales & marketing processes including strategic and operational segmentation, targeting, acquisition and retention. He has built and deployed multiple front-line CRM applications. His clients and companies have won a variety of innovation awards win awards in bringing analytics to customer touchpoints. Dan Meers serves as the President of K2 Solutions LLC, and manages the Reston, VA based consultancy solving complex data centric problems with asset based consulting services. He has over 25 of experience with clients in financial, retail, manufacturing, government and other markets. Dan regularly addresses enterprise risk issues including information assurance and security, anti-money laundering and broader financial crime detection & prevention, and integration of social media data. Dan has worked with Bill Inmon and John Zachman in the development and application of Corporate Information Factory and other models for global firms including Shell Oil Services, BP, Target and others.