1. What Business People Need to Know About Data Management and Data Governance Micheline Casey Principal CDO, LLC @michelinecasey michelinecasey1@gmail.com www.dataTrending.wordpress.com

2. Best-in-Class or Laggard? Best-in-class companies take 12 days on average to integrate new data sources into their analytical systems; industry average companies take 60 days; and, laggards 143 days Source: Aberdeen Group: Data Management for BI: Fueling the analytical engine with high-octane information Limits ability to achieve organizational potential and to aggressively pursue new market opportunities Limits ability to take advantage of newly emerging business opportunities Limits success in bringing high- value products and services to customers, and in retaining and winning desired business Limits ability to drive information- based insights Limits ability to be proactive

3. Data Management Framework Holistic approach to understand the information needs of the enterprise & its stakeholders Consistency for planning & process development 10 major functional areas, including governance Aligns data with business strategy (above) and technology (below) Takes into account the data lifecycle – creation through destruction Internationally recognized through Data Management Association International (DAMA)

4. Key Supporting Data Management Components to Big Data Data Governance – Exercise of authority and controls over the management of data assets. Policies, processes, standards, definitions, metrics. Councils, stewards, trustees roles and responsibilities defined Data Architecture - Defines data requirements, guides integration and control of data assets, aligns data investments with business strategy. Part of an overall enterprise architecture framework Enterprise data models, definitions, and taxonomies Enterprise data delivery Master Data Management – Control over master data values to enable consistent, contextual use across systems of the most accurate, timely and relevant version of truth about essential business entities. Meta Data Management – Descriptive tags about data, concepts, and connections between data and concepts. Business, technical, process, and stewardship Data Security – Planning, development, and execution of security policies and procedures to provide proper authentication, authorization, access, and auditing of data and information assets.

5. Framework for Data-Driven Thinking

6. Key Questions to Drive Business Value from Data What business opportunity/problem are we trying to solve? What questions do we need to answer to solve the problem? What data do we need to answer the questions? What data do we have? How can data help differentiate us in the market? What data is IP for us? Revenue generating for us? How do we integrate the right data together? How do we manage the quality of the data? What data does this relate to (master data)? Do we have all the data about this (person, event, thing, etc.)? What are the permissible purposes of the data? (compliance, regulatory environment) Who is allowed to access the data? Use this data?

7. DM Spider Map

8. Data Management Maturity in a Social Business Partial Source: Social Business by Design, Dion Hinchcliffe

9. Data Governance Council Roles and Responsibilities DGC DGP Task Forces & Tiger Teams Lines-of- Business

10. Data Governance Operational View

11. Success Measures Information is trusted Speed to market for new products or services is improved Time spent looking for data is reduced Time-to-answer ratio is inversed Questions are answerable (e.g. What is the value of a customer?) Stratification and insight of customer is achieved Customer intimacy achieved Integration and development time slashed Company is data-driven

12. What Business People Need to Know About Data Management and Data Governance Micheline Casey Principal CDO, LLC @michelinecasey michelinecasey1@gmail.com www.dataTrending.wordpress.com