DAMA + Wilshire Meta-Data Conference - Data Strategy Track
About This Tutorial
Almost every large government agency or Global 2000 company is struggling to properly manage their enterprise's data and its architecture. This difficulty is the direct result of the highly distributed, disjoined and overly expensive IT environments which currently exist throughout our industry. This situation has triggered the reemergence of corporations looking to establish truly proactive Enterprise Data Architecture organizations.

This course will look to move enterprise data architecture theory into a practical set of steps (roadmap) to achieving true value from your enterprise data architecture initiative. Moreover, it will present the specific meta data inputs and outputs that are required for each of the most common enterprise data architecture focus areas. In addition, data governance and stewardship approaches and structures will be presented for each of these areas.

What You Will Learn
  1. Enterprise Data Architecture Defined
  2. Enterprise Data Architecture ROI
  3. Foundational Components of Enterprise Data Architecture
    • Meta Data Management
    • Data Governance and Stewardship
  4. Focus Areas of Enterprise Data Architecture
    • Enterprise Data Model
      • Common Objectives
      • Value to the Organization
      • Roadmap for Implementation
      • Meta Data Management Inputs/Outputs
      • Data Governance & Stewardship Structure
    • Master Data Management
      • Common Objectives
      • Value to the Organization
      • Roadmap for Implementation
      • Meta Data Management Inputs/Outputs
      • Data Governance & Stewardship Structure
    • Data Quality
      • Common Objectives
      • Value to the Organization
      • Roadmap for Implementation
      • Meta Data Management Inputs/Outputs
      • Data Governance & Stewardship Structure
    • IT Portfolio Management
      • Common Objectives
      • Value to the Organization
      • Roadmap for Implementation
      • Meta Data Management Inputs/Outputs
      • Data Governance & Stewardship Structure
    • Enterprise Data Warehousing
      • Common Objectives
      • Value to the Organization
      • Roadmap for Implementation
      • Meta Data Management Inputs/Outputs
      • Data Governance & Stewardship Structure
  5. Enterprise Data Architecture Best Practices
  6. Enterprise Data Architecture Real-World Case Studies
In 1999, Peter Drucker wrote that, so far, the focus of the IT revolution has not been on information at all, but on technology. Now, the next information revolution is under way and information is a company’s most important business asset. This includes business processes and architectures required to best leverage information within and across multiple enterprises. As a result, IT has now evolved to a place where the CIO can’t handle it alone. To make sure that IT is always aligned with business you need an Enterprise Architect, people and firms whose focus is no longer on the "T" in IT but on the “I.” Today, Enterprise Architecture is maturing into a true profession, and the role of the architect is constantly evolving.

In this presentation, Allen Brown, CEO of The Open Group, a vendor- and technology-neutral consortium focused on open standards and global interoperability, will address the following:
  • The evolution of the enterprise architect
  • New demands on enterprise architecture professionals, including when barriers are broken down within and between enterprises, a city planner perspective of enterprise architecture must be taken;
  • The role of industry certification programs in helping both architects and companies meet these challenges and find the right talent.

Allen Brown is the President and CEO of The Open Group, a vendor- and technology-neutral consortium that works towards enabling access to integrated information within and between enterprises based on open standards and global interoperability. He has been with the company since 1993, when he joined the then X/Open Company Limited with the dual responsibility of Chief Financial Officer and Vice President of Business Development. In this position he played a significant role in the development of the certification of conformance to the Single UNIX Specification and the licensing of the UNIX® trademark. Prior to joining The Open Group, Mr. Brown managed a consulting firm in London, which he founded in 1987. He enjoyed a mix of financial management and general management assignments, which included advising venture capitalists on investment decisions, and consulting on IT systems design and implementation. Mr. Brown holds an MBA from London Business School.

Business users are demanding more data, better analytics, and faster delivery times from their I/T organizations. And the tools to support these needs—BI, ETL, warehousing, mining, cheap storage—are readily available and no longer key differentiating factors. In fact, they may be driving behaviors that are inhibiting I/T’s ability to deliver what the business needs to compete. For example, when an application is built for a particular business function, it will typically manage its data within that function’s limited view of the enterprise data model. Over time, different applications will fragment the data model, as the needs of each business area evolve and time-to-market pressures make it easier to create loosely-coupled data stores for each application. Subsequently, one or more data warehouses will be built to collect and homogenize the data silos, leading to further inconsistency between the warehouse meta model and the source data models, and requiring heavy ETL transactions, redundant storage, and more data cleansing…not to mention higher development and maintenance costs. But if “the business is the business”, i.e., the business model is the same regardless of how its systems are structured, then why should each application need its own data model, and why should the data warehouse need a different meta model than the operational data stores? ESB (and more broadly, SOA) provides a framework and tools to help enforce better alignment of the enterprise data architecture across business applications and warehouses. In this presentation, we will discuss how ESB can be used to bring together multiple application data stores and data warehousing platforms under a common data access umbrella.
Three specific implementations will be discussed:
  1. Simplified data access services to replace localized (app-specific) services and eliminate cumulative calls and transformations;
  2. A common inquiry gateway for applications to navigate both operational data stores and a data warehouse;
  3. Right-sized access services that better fit specific data requirements and reduce the need for an application to “crawl the data model”.
Federal information is a national asset needed by the public to understand the activities of their government and it is an internal asset to be leveraged across the single, federated government enterprise to:
  • improve performance
  • support decision-making
  • document agency activities
  • fight the global war on terrorism
  • enable accurate reporting.
The Federal Data Reference Model (DRM) supports the emergence of repeatable processes that enable agencies to discover, share and seamlessly exchange data and information relevant to meet business and mission objectives. The key to the DRM\'s successful implementation is the establishment of governance, guidance and processes to solve the real information sharing problems of government.

The Federal Community recognizes that government organizations must be accountable and their performance must be measured. This is best done through identifying Lines of Business (LOBs) and Communities of Interest (COIs), each taking responsibility for managing the data that support their business (or mission) and applying appropriate governance, standards, and services.

Dr. Suzanne Acar (DOI) and Mr. Bryan Aucoin (DNI) are co-chairs of the Federal Data Architecture Subcommittee and will share their work and findings to enhance agency collaboration for improved information sharing. Points of emphasis will include:
  • The mission of the Federal Data Architecture Subcommittee
  • The Federal DRM Management Strategy
  • Engaging Communities of Interests and Stakeholders
  • The Three Pillar Data Strategy Framework
  • Future directions.
In the wake of 9/11, and with the growing threat of terrorism, the need to "connect the dots" places greater requirements on our intelligence agencies to be able to interrelate and share data. Our response is to develop an EDA engaged in all facets of data integration, exploitation, sharing and our emerging SOA. Our need to apply the EDA is immediate, and cannot wait for its completion. Therefore, we are taking an approach that is simultaneously both strategic and tactical. We employ 3-pronged outreach to development organization “Referents”, a “Project Guidance” service, and ongoing education. Referents are active, engaged representatives who review and contribute to the emerging EDA and serve as emissaries to our diverse development activities. The voluntary “Project Guidance Service” engages interactively with projects to develop phased data models and recommendations to enable downstream convergence with the maturing EDA and Data Services Architecture without disrupting schedules. Our CTO Seminar Series features internal and external experts, educating and engaging advocates throughout the enterprise. By the time the EDA is completed and formally adopted, it will already have been largely implemented and will be delivering significant benefits to the Nation.
Intel, like many large enterprises, faces significant integration challenges. Integration of architectures for business, information, technology and solutions traverse skills, business strategies, and organization boundaries. As a priority, we are initially focusing on business process and information. Our experience tells us that business process should lead architecture. This presentation will describe the challenges, plans, methodology and processes that must be addressed to successfully navigate the integration challenges. In 2005, the Business and Data analysts from the Supply Network business area initiated a discussion to explore the benefits of increased collaboration. Together we established a methodology to align standards, methods, tools, roles, responsibilities. The methodology also identifies key opportunities to align business, information, technologies, and solutions that have improved end-to-end integration.

Intel has made some key changes to better align our organization and our process to drive business, information, technology, and solution integration. Governance is just one of the areas where we developed a set of a “building codes” (architecture principles, policies, standards, and prescriptive guidance), to ensure compliance to the architectural direction.
  • The BITS Rule: Integrated architecture supports business, information, technology and solutions.
  • Architecture crosses skill, business strategies, and organizational boundaries
  • Methodology must meet the integration challenges to go across different disciplines.
  • End-to-end methodology aligns standards, methods, tools, roles, and responsibilities
  • The implementations required a governance policy that could be uniformly self-enforced which resulted in 'building codes.'
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