How Data Modeling Fits Into an Overall Enterprise Architecture Donna Burbank Global Data Strategy Ltd
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Ewsolutions Enterprise Architecture, Data Architecture, Data
EWSolutions Enterprise Architecture, Data Architecture, Data Governance, Metadata Management Case Study Leveraging Existing Investments in Systems, Data and Personnel to Improve Logistics and Supply Chain Management for Defense Operations Enterprise architecture planning and development, data architecture, metadata management, data governance, and enterprise data integration combined to ensure the success of the world's largest defense logistics and supply chain. EWSolutions, Inc. 1/25/2017 Developing and Implementing a New Defense Logistics Supply Chain: A Case Study in How EWSolutions Enabled Success for the US Department of Defense The Department of Defense (DoD) is America's oldest and largest government agency. It employs a civilian force of 742,000, along with over 1.3 million men and women on active duty; it is the United State's largest employer. Another 826,000 people serve in the National Guard and Reserve forces. The national security depends on defense installations, people, and facilities being in the right place, at the right time, with the right qualities and capacities to protect the security of the United States and allies. These military service members and civilians operate in every time zone and in every climate. More than 450,000 employees are overseas, both afloat and ashore. This complexity extends to the logistics, communication, and supply chain needed to connect and furnish these employees and dependents with all the required resources (food, clothing, weapons, etc.) The mission of the US Department of Defense is to provide the military forces needed to deter war and to protect the security of the United States. Fulfilling this mission requires a large variety of resources; securing and delivering those resources to the right place at the right time in the right quantities requires accurate information that comes from complete and valid data. -
Enterprise Architecture
Enterprise Architecture Dr. Adnan Albar Faculty of Computing & Information Technology King AbdulAziz University - Jeddah 1 Enterprise Architecture Methods Lecture 5 Week 5 Slides King AbdulAziz University - FCIT 2 Overview . Description Languages for Business & IT Domains . IDEF . BPMN . Testbed . ARIS . Unified Modeling Language . Service-Oriented Architecture (SOA) Slide 3 Description Languages . In domains such as business process design and software development, we find established description languages for modeling these domains. For software modeling, UML is of course, the single dominant language. In organization and process modeling, on the other hand, a multitude of languages are in use: there is no standard for models in this domain. We will focus on languages that either find widespread use or have properties that are interesting from the perspective of our goals in developing an enterprise architecture language. Slide 4 IDEF – Integrated DEFinition Methods .IDEF is a family of languages .Used to perform enterprise modeling and analysis .Currently, there are 16 IDEF methods. Of these methods, IDEF0, IDEF3, and IDEF1X (‘the core’) are the most commonly used. Slide 5 IDEF – The Scope it Covers .Functional modeling, IDEF0: The idea behind IDEF0 is to model the elements controlling the execution of a function, the actors performing the function, the objects or data consumed and produced by the function, and the relationships between business functions (shared resources and dependencies). .Process modeling, IDEF3: IDEF3 captures the workflow of a business process via process flow diagrams. These show the task sequence for processes performed by the organization, the decision logic, describe different scenarios for performing the same business functions, and enable the analysis and improvement of the workflow. -
Powerdesigner 16.6 Data Modeling
SAP® PowerDesigner® Document Version: 16.6 – 2016-02-22 Data Modeling Content 1 Building Data Models ...........................................................8 1.1 Getting Started with Data Modeling...................................................8 Conceptual Data Models........................................................8 Logical Data Models...........................................................9 Physical Data Models..........................................................9 Creating a Data Model.........................................................10 Customizing your Modeling Environment........................................... 15 1.2 Conceptual and Logical Diagrams...................................................26 Supported CDM/LDM Notations.................................................27 Conceptual Diagrams.........................................................31 Logical Diagrams............................................................43 Data Items (CDM)............................................................47 Entities (CDM/LDM)..........................................................49 Attributes (CDM/LDM)........................................................55 Identifiers (CDM/LDM)........................................................58 Relationships (CDM/LDM)..................................................... 59 Associations and Association Links (CDM)..........................................70 Inheritances (CDM/LDM)......................................................77 1.3 Physical Diagrams..............................................................82 -
Integrating IT Portfolio Management with Enterprise Architecture Management 79
Enterprise Modelling and Information Systems Architectures Vol. 8, No. 2, December 2013 Integrating IT Portfolio Management with Enterprise Architecture Management 79 Daniel Simon, Kai Fischbach, Detlef Schoder Integrating IT Portfolio Management with Enterprise Architecture Management The management of information technology (IT) as a business has become a crucial factor in today’s complex and dynamic environments. Many firms thus have implemented IT portfolio and enterprise architecture (EA) management practices, and academic research has paid increasing attention to these concepts. However, their integration seems poorly substantiated; this article therefore seeks to answer two main questions: (1) What are differences and common characteristics of IT portfolio and EA management, and in what way can they be integrated? and (2) what factors and types might describe an integrated process design of EA management and project portfolio management in particular? To answer these questions, this study synthesises previous research and surveys EA practitioners to propose an EA management process map, as well as three descriptive factors and four clusters, which provide an integrated process design with project portfolio management. The interrelations with organisational aspects and software tool support are also explored. This article thereby clarifies and systematises the subject area while also offering advice for researchers and practitioners. 1 Introduction structured, business-like approach to IT manage- ment that comprises application, infrastructure, The notion of managing information technology service, and project portfolio management (Ben- (IT) as a business (Lientz and Larssen 2004) has son et al. 2004; Kaplan 2005). attracted significant attention, particularly as IT environments grow steadily more complex and Integration is equally critical to EA management, thus more difficult to manage. -
Data Model Standards and Guidelines, Registration Policies And
Data Model Standards and Guidelines, Registration Policies and Procedures Version 3.2 ● 6/02/2017 Data Model Standards and Guidelines, Registration Policies and Procedures Document Version Control Document Version Control VERSION D ATE AUTHOR DESCRIPTION DRAFT 03/28/07 Venkatesh Kadadasu Baseline Draft Document 0.1 05/04/2007 Venkatesh Kadadasu Sections 1.1, 1.2, 1.3, 1.4 revised 0.2 05/07/2007 Venkatesh Kadadasu Sections 1.4, 2.0, 2.2, 2.2.1, 3.1, 3.2, 3.2.1, 3.2.2 revised 0.3 05/24/07 Venkatesh Kadadasu Incorporated feedback from Uli 0.4 5/31/2007 Venkatesh Kadadasu Incorporated Steve’s feedback: Section 1.5 Issues -Change Decide to Decision Section 2.2.5 Coordinate with Kumar and Lisa to determine the class words used by XML community, and identify them in the document. (This was discussed previously.) Data Standardization - We have discussed on several occasions the cross-walk table between tabular naming standards and XML. When did it get dropped? Section 2.3.2 Conceptual data model level of detail: changed (S) No foreign key attributes may be entered in the conceptual data model. To (S) No attributes may be entered in the conceptual data model. 0.5 6/4/2007 Steve Horn Move last paragraph of Section 2.0 to section 2.1.4 Data Standardization Added definitions of key terms 0.6 6/5/2007 Ulrike Nasshan Section 2.2.5 Coordinate with Kumar and Lisa to determine the class words used by XML community, and identify them in the document. -
Integration Definition for Function Modeling (IDEF0)
NIST U.S. DEPARTMENT OF COMMERCE PUBLICATIONS £ Technology Administration National Institute of Standards and Technology FIPS PUB 183 FEDERAL INFORMATION PROCESSING STANDARDS PUBLICATION INTEGRATION DEFINITION FOR FUNCTION MODELING (IDEFO) » Category: Software Standard SUBCATEGORY: MODELING TECHNIQUES 1993 December 21 183 PUB FIPS JK- 45C .AS A3 //I S3 IS 93 FIPS PUB 183 FEDERAL INFORMATION PROCESSING STANDARDS PUBLICATION INTEGRATION DEFINITION FOR FUNCTION MODELING (IDEFO) Category: Software Standard Subcategory: Modeling Techniques Computer Systems Laboratory National Institute of Standards and Technology Gaithersburg, MD 20899 Issued December 21, 1993 U.S. Department of Commerce Ronald H. Brown, Secretary Technology Administration Mary L. Good, Under Secretary for Technology National Institute of Standards and Technology Arati Prabhakar, Director Foreword The Federal Information Processing Standards Publication Series of the National Institute of Standards and Technology (NIST) is the official publication relating to standards and guidelines adopted and promulgated under the provisions of Section 111 (d) of the Federal Property and Administrative Services Act of 1949 as amended by the Computer Security Act of 1987, Public Law 100-235. These mandates have given the Secretary of Commerce and NIST important responsibilities for improving the utilization and management of computer and related telecommunications systems in the Federal Government. The NIST, through its Computer Systems Laboratory, provides leadership, technical guidance, -
Data Analytics EMEA Insurance Data Analytics Study Contents
A little less conversation, a lot more action – tactics to get satisfaction from data analytics EMEA Insurance data analytics study Contents Foreword 01 Introduction from the authors 04 Vision and strategy 05 A disconnect between analytics and business strategies 05 Articulating a clear business case can be tricky 07 Tactical projects are trumping long haul strategic wins 09 The ever evolving world of the CDO 10 Assets and capability 12 Purple People are hard to find 12 Data is not always accessible or trustworthy 14 Agility and traditional insurance are not natural bedfellows 18 Operationalisation and change management 23 Operating models have no clear winner 23 The message is not always loud and clear 24 Hearts and minds do not change overnight 25 Are you ready to become an IDO? 28 Appendix A – The survey 30 Appendix B – Links to publications 31 Appendix C – Key contacts 32 A little less conversation, a lot more action – tactics to get satisfaction from data analytics | EMEA Insurance data analytics study Foreword The world is experiencing the fastest pace of data expansion and technological change in history. Our work with the World Economic Forum in 2015 identified that, within financial services, insurance is the industry which is most ripe for disruption from innovation owing to the significant pressure across the value chain. To build on this work, our report ‘Turbulence ahead – The future of general insurance’, set out various innovations transforming the industry and subsequent scenarios for The time is now the future. It identified that innovation within the insurance industry is no longer led by insurers themselves. -
Metamodeling and Method Engineering with Conceptbase”
This is a pre-print of the book chapter M. Jeusfeld: “Metamodeling and method engineering with ConceptBase” . In Jeusfeld, M.A., Jarke, M., Mylopoulos, J. (eds): Metamodeling for Method Engineering, pp. 89-168. The MIT Press., 2009; the original book is available from MIT Press http://mitpress.mit.edu/node/192290 This pre-print may only be used for scholar, non-commercial purposes. Most of the sources for the examples in this chapter are available via http://merkur.informatik.rwth-aachen.de/pub/bscw.cgi/3782591 for download. They require ConceptBase 7.0 or later available from http://conceptbase.cc. Metamodeling and Method Engineering with ConceptBase Manfred Jeusfeld Abstract. This chapter provides a practical guide on how to use the meta data repository ConceptBase to design information modeling methods by using meta- modeling. After motivating the abstraction principles behind meta-modeling, the language Telos as realized in ConceptBase is presented. First, a standard factual representation of statements at any IRDS abstraction level is defined. Then, the foundation of Telos as a logical theory is elaborated yielding simple fixpoint semantics. The principles for object naming, instantiation, attribution, and specialization are reflected by roughly 30 logical axioms. After the language axiomatization, user-defined rules, constraints and queries are introduced. The first part is concluded by a description of active rules that allows the specification of reactions of ConceptBase to external events. The second part applies the language features of the first part to a full-fledged information modeling method: The Yourdan method for Modern Structured Analysis. The notations of the Yourdan method are designed along the IRDS framework. -
Constructing a Meta Data Architecture
0-471-35523-2.int.07 6/16/00 12:29 AM Page 181 CHAPTER 7 Constructing a Meta Data Architecture This chapter describes the key elements of a meta data repository architec- ture and explains how to tie data warehouse architecture into the architec- ture of the meta data repository. After reviewing these essential elements, I examine the three basic architectural approaches for building a meta data repository and discuss the advantages and disadvantages of each. Last, I discuss advanced meta data architecture techniques such as closed-loop and bidirectional meta data, which are gaining popularity as our industry evolves. What Makes a Good Architecture A sound meta data architecture incorporates five general characteristics: ■ Integrated ■ Scalable ■ Robust ■ Customizable ■ Open 181 0-471-35523-2.int.07 6/16/00 12:29 AM Page 182 182 Chapter 7 It is important to understand that if a company purchases meta data access and/or integration tools, those tools define a significant portion of the meta data architecture. Companies should, therefore, consider these essential characteristics when evaluating tools and their implementation of the technology. Integrated Anyone who has worked on a decision support project understands that the biggest challenge in building a data warehouse is integrating all of the dis- parate sources of data and transforming the data into meaningful informa- tion. The same is true for a meta data repository. A meta data repository typically needs to be able to integrate a variety of types and sources of meta data and turn the resulting stew into meaningful, accessible business and technical meta data. -
Enterprise Architecture for Project Managers
Enterprise Architecture for Project Managers JK Corporate Services (JKCS) Authored by: Stan Ketchum, PMP Enterprise Architecture for Project Managers by Stan Ketchum is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License Enterprise Architecture for Project Managers Table of Contents Introduction .................................................................................................................................... 1 Purpose ........................................................................................................................................... 2 What Is Enterprise Architecture? ................................................................................................... 2 Why Is EA Needed? ..................................................................................................................... 2 What are the benefits of EA? ...................................................................................................... 3 EA vs Projects .............................................................................................................................. 3 What Does EA Consist of? ............................................................................................................... 4 EA Domains ................................................................................................................................. 4 Business Architecture ............................................................................................................ -
Architecting Software the SEI Way Twitter #Seiarchitecture © 2012 Carnegie Mellon University Outline Essential Problems for Architects
Analyzing and Evaluating Enterprise Architectures John Klein Senior Technical Staff John has over 20 years experience developing systems and software. He joined SEI in 2008. Before joining SEI, John was a chief architect at Avaya, Inc. There his responsibilities included development of multimodal agents, architectures for communication analytics, and the creation and enhancement of the Customer Interaction Software Product Line architecture. Prior to that, John was a software architect at Quintus, where he designed the first commercially successful multi- channel integrated contact center product and led the technology integration of the product portfolio as Quintus acquired several other companies. See his full bio at: www.sei.cmu.edu/go/architecting-software-the-sei-way Architecting Software the SEI Way Twitter #SEIArchitecture © 2012 Carnegie Mellon University Outline Essential problems for architects - • How do we efficiently translate business goals into quality attribute requirements? • How do we ensure that these quality attribute requirements are reflected in the tradeoffs and decisions that shaped the architecture? Agenda • Review of the SEI perspective on architecture-centric engineering • Scaling from software context to systems of systems and enterprise architectures • An approach to developing quality attribute requirements for enterprise architectures • An approach to first-pass evaluation of enterprise architectures • Tying together EA and system/software analysis and evaluation Architecting Software the SEI Way 1 Twitter #SEIArchitecture © 2012 Carnegie Mellon University Architecture-centric Engineering – Software and Systems IMPLEMENT AND EVOLVE DESIGN IMPLEMENT BUSINESS AND MISSION GOALS ARCHITECTURE SYSTEM SATISFY CONFORM SATISFY Architecting Software the SEI Way Twitter #SEIArchitecture © 2012 Carnegie Mellon University Principles of Architecture-Centric Engineering Every system has an architecture, regardless of scale. -
4.3 NWS ENTERPRISE ARCHITECTURE Bobby Jones
4.3 NWS ENTERPRISE ARCHITECTURE Bobby Jones*, Chief IT Architect Barry West, Chief Information Officer NOAA’s National Weather Service 1 INTRODUCTION An Enterprise Architecture (EA) is a comprehensive blueprint that aligns an organization’s business In 1996, Congress required Federal Agency Chief processes with its Information Technology (IT) Information Officers (CIO) to develop, maintain, and strategy. It is documented using multiple facilitate integrated systems architectures with the architectural models or views that show how the passage of the Clinger-Cohen Act. Additionally, current and future needs of an organization will be Office of Management and Budget (OMB) issued met. The key components of the EA are: guidance that requires agency information systems investments to be consistent with Federal, Agency, • Accurate representation of the and bureau architectures. Enterprise Architectures business environment, strategy and (EA) are “blueprints” for systematically and critical success factors completely defining an organization’s current • Comprehensive documentation of (baseline) or desired (target) environment. EAs are business units and key processes essential for evolving information systems and • Views of the systems and data that developing new systems that optimize their mission support these processes value. This is accomplished in logical or business • A set of technology standards that terms (e.g., mission, business functions, information define what technologies and flows, and systems environments) and technical products are approved to be used terms (e.g., software, hardware, communications), within an organization, and includes a sequencing plan for transitioning complemented by prescriptive from the baseline environment to the target enterprise-wide guidelines on how environment. to best apply these technology standards in creating business If defined, maintained, and implemented effectively, applications.