Business Intelligence for the Chief Data Officer

Transcription

1 Aug 20, 2014 DAMA - CHICAGO Business Intelligence for the Chief Data Officer Don Soulsby Sandhill Consultants

2 Who we are: Sandhill Consultants Sandhill is a global company servicing the data, process modeling community in its varied needs. Educators & Architects Standards Framework Onsite & Web Based- Training Services Reference Material, Guides Technical Support Don Soulsby Enterprise Architect Practice Leader Data/Process modeler Information Management Product Manager EA, DW, BI, Metadata Consultant Industry Speaker 2

3 The New Cx Executives CDO Chief Data Officer Organizations, Processes Come and Go, Data Persists

4 CDO A chief data officer (CDO) is a corporate officer responsible for enterprise-wide governance and utilisation of information as an asset, via data processing, analysis, data mining information trading and other means. The Chief Data Officer has a significant measure of business responsibility for determining what kinds of information the enterprise will choose to capture, retain and exploit and for what purposes

5 This is your world

6 2013 CDO facts CDO Fact #1 There are over 100 chief data officers (carrying that actual job title) serving in large enterprises today. That s more than double the number we counted in CDO Fact #2 Banking, Government and Insurance are the top 3 industries for Chief Data Officers in that order. However we are now seeing other industries rising. CDO Fact #3 65% of Chief Data Officers are in the United States. 20% are in the UK. There are now CDOs in over a dozen countries. CDO Fact #4 Over 25% Of all Chief Data Officers are in New York or DC. It s a regulatory catalyzed trend at least in the early stages. CDO Fact #5 Over 25% of Chief Data Officers are women. In case you are wondering - that s almost twice as high as for CIOs (13%) 5 Facts About Chief Data Officers, by Mark Raskino Member of the Gartner Blog Network, November 6, 2013

7 Data Governance The act or process of directing, leading and assuring that information is managed effectively as an enterprise resource, including resolving information conflicts, across the enterprise. Larry English

8 Trust and Traceability Do Executives Trust Data or Intuition in Decision-Making? By Bob ViolinoJUN 9, :44pm ET Compliance ALL DATA, Great and Small Doveryay, No Proveryay, Trust yes, but verify."

9 TRUST Firm reliance on the integrity, ability, or character of a person or thing Custody; care. Something committed into the care of another; charge.

10 TRUST in IT context Gatekeeping o etrust, Security, Intrusion detection Stewardship o Ownership vs Information Resource Meaning/Quality Governance o Information Accountability

11 Building TRUST through Food Assurance Public confidence has been shaken in recent times by food scares and associated media sensationalism. In particular this is made us, as both consumers and participants in supply chain, uncertain of who or how to have trust in the food chain. - R.N.Baines & W.P.Davies Royal Agricultural College Cirencester, Glousteshire, UK

12 THIS FISH FROM FIN TO FORK

13 Many to Many Problem Many Sources Many Uses

14 Many to Many Solution Many Sources Many Uses Enterprise Data Warehouse

15 Data Management Maturity Model METADATA OVERSIGHT

16 Information Flow $$ Business IT Information $$ META DATA

17 Business Intelligence Unstructured Applications ERP Data ETL Data Modeling Metadata Data Warehouse Repository Data Mart BI Analytics Analysis Cube Information Delivery

18 DMM Categories, Components Data Management Strategy Data Governance Data Quality Data Operations Platform & Architecture Data Management Strategy Governance Management DQ Strategy Data Requirements Definition Architectural Approach Communications Business Glossary Data Profiling Data Lifecycle Management Architectural Standards Data Management Function Metadata Management DQ Assessment Provider Management Data Management Platform Business Case Data Cleansing Data Integration Funding Historical Data, Archiving

19 Metadata - Information UNDERSTANDIBILITY Synonyms, Homonyms, Artifacts

20 BI for IT Data Collection Data Delivery Metadata Repository

21 Metadata Maturity Model Level 1 Performed metadata documentation is developed, stored and accessible. Level 2 Managed metadata management process defined capture data interdependencies. impact analysis on potential data changes metadata categories, properties, and standards Level 3 Defined metadata management strategy phased implementation plan centralizes metadata management efforts data governance approves change measures and, metrics architecture validation Level 4 Measured integrated metamodel uniform data types and data definitions metadata repository exchange data standards historical measurement of objectives quantitative objectives statistical analysis of processes Level 5 Optimized root cause analysis performance prediction models improvement objectives planned data changes continuous improvement

22 Metadata Management PURPOSE Establish the processes and infrastructure for specifying and extending clear and organized information about the data assets under management, fostering and supporting data sharing, ensuring compliant use of data, improving responsiveness to business changes, and reducing data related risks.

23 Introduction Effective metadata management, and build out of the organization s metadata catalogue facilitates, supports and contributes to achievement of critical data management activities and objectives, such as: Data architecture Data requirements Data lineage Data integration Data provenance Data standards

24 Model Driven Change Management Human Oriented TAXONOMY Business Domain Conceptual Data Model Forward Engineering Logical Data Model Middle Out Model Management Physical Data Model Reverse Engineering Computer Oriented DATABASE Technology Domain

25 Not Just Data DATA PROCESS Business Change Conceptual Data Mode AS IS (?) Conceptual Data Model TO BE Business Dynamics Model Logical Data Model AS IS Logical Data Model TO BE System Dynamics Model Reverse Engineered Physical Model Data Delivery Model Function Dynamics Model Application Database Change

26 Data Lineage Graphical data linage across multiple models Design Layers Data Movement Domains

27 Reporting & Publishing

28 Asset Management Management of an organization's assets, both physical assets, called "tangible", and nonphysical, "intangible" assets. Physical asset management Infrastructure asset management Fixed assets management IT asset management Digital asset management

29 Managing Data as an Asset Asset Lifecycle o Planning o Procurement o Deployment o Management & Maintenance o Disposition Asset Valuation o Capital Cost o Expense o Depreciation o Salvage Value

30 The Rise of Management by the Numbers While glancing out the window Return on Assets = Net Income Total Assets Inventory Turnover = Cost of Sales Avg. Inventory

31 Measurement "You can't manage, what you can't measure. Measure = Observation Standard Enterprise Modelling Set of Standards

32 How Does EM-SOS! Work Corporate Policies Design Standards Design Processes Forms & Reports EM-SOS! Glossaries Design Templates Data Management Life Cycle & Procedures Reusable Object Repository Business Requirements Conceptual Logical Physical Models Databases Apps Development & Operations

33 Metrics & Measurement

34 Social Media - Metadata Study exposes social media sites that delete photographs metadata.

35 Thank You! [shuǐtóu] [bù] [qīngshuǐ] [wěi] [hún] If upstream is dirty, downstream will be muddy Donald J. Soulsby Enterprise Architecture Practice Leader Sandhill Consultants

36 How Sandhill Can Help Product Standards & Best Practices Sandhill EMSOS tm Data Architecture Process Enterprise Modeling Application Architecture People Place Tools & Technologies Sandhill Training Security Architecture Network Architecture