The Experts below are selected from a list of 74850 Experts worldwide ranked by ideXlab platform
David Loshin - One of the best experts on this subject based on the ideXlab platform.
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data quality in practice
Enterprise Knowledge Management#R##N#The Data Quality Approach, 2001Co-Authors: David LoshinAbstract:This chapter examines the definition of data quality in terms of utility and highlights how understanding the measure of data quality may depend on the context and domain in which the data is scrutinized. The development of a data quality improvement program and what it takes to get the ball rolling can be summed up in seven phases—gaining senior level endorsement, training in data quality, creating and enforcing a data ownership policy, building the economic model, performing a Current State Assessment, selecting a project for improvement, and implementing and deploying the project. Different contexts for data quality—namely, data quality in an operational context, data quality in the database world, data quality and the data warehouse, data mining, electronic data interchange, and the Internet are also discussed in the chapter. While there is a distinct need for data quality in each of these contexts, the actual work that is done with respect to data quality is underStated is likely to grow in importance.
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Enterprise knowledge management: the data quality approach
2000Co-Authors: David LoshinAbstract:1. Introduction 2. Who Owns Information? 3. Data Quality in Practice 4. Economic Framework of Data Quality and the Value Proposition 5. Dimensions of Data Quality 6. Statistical Process Control and the Improvement Cycle 7. Domains, Mappings, and Enterprise Reference Data 8. Data Quality Assertions and Business Rules 9. Measurement and Current State Assessment 10. Data Quality Requirements 11. Metadata, Guidelines, and Policy 12. Rule-Based Data Quality 13. Metadata and Rule Discovery 14. Data Cleansing 15. Root Cause Analysis and Supplier Management 16. Data Enrichment/Enhancement 17. Data Quality and Business Rules in Practice 18. Building the Data Quality Practice
David Loshi - One of the best experts on this subject based on the ideXlab platform.
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enterprise knowledge management the data quality approach
2000Co-Authors: David LoshiAbstract:Preface Chapter 1 - Introduction Chapter 2 - Who Owns Information? Chapter 3 - Data Quality in Practice Chapter 4 - Economic Framework of Data Quality and the Value Proposition Chapter 5 - Dimensions of Data Quality Chapter 6 - Statistical Process Control and the Improvement Cycle Chapter 7 - Domains, Mappings, and Enterprise Reference Data Chapter 8 - Data Quality Assertions and Business Rules Chapter 9 - Measurement and Current State Assessment Chapter 10 - Data Quality Requirements Chapter 11 - Metadata, Guidelines, and Policy Chapter 12 - Rule-Based Data Quality Chapter 13 - Metadata and Rule Discovery Chapter 14 - Data Cleansing Chapter 15 - Root Cause Analysis and Supplier Management Chapter 16 - Data Enrichment/Enhancement Chapter 17 - Data Quality and Business Rules in Practice Chapter 18 - Building the Data Quality Practice
Stephen G. Haines - One of the best experts on this subject based on the ideXlab platform.
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The Systems Thinking Approach to Strategic Planning and Management
2000Co-Authors: Stephen G. HainesAbstract:Reinventing Strategic Planning: An Overview Revolutionary Change: Its Implications for Organizations Yes...There Are Right Answers The Organization: A Living, Breathing System Reinventing Strategic Management (Planning and Change) Developing a Strategic Plan: Step-by-Step The Plan-to-Plan Day (Step #1) Environmental Scanning and the Parallel Process Ideal Future Vision (Step #2) Key Success Measures (Step #3) or Goals Current State Assessment (Step #4) Strategy Development (Step #5) Business Unit Planning (Step #6) Annual Plans and Budgeting (Step #7) Mastering Strategic Change: "Where the Rubber Meets the Road" Plan-to-Implement (Step #8) Strategy Implementation and Change (Step #9) Annual Strategic Review and Update (Step #10) Getting Started: Different Options and Customized Applications Strategic Management Applications Getting Started: Options References Index
Nambisan Rohit - One of the best experts on this subject based on the ideXlab platform.
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An enterprise architecture evaluation of the Improving Massachusetts Post-Acute Care Transitions (IMPACT) Program
Massachusetts Institute of Technology, 2014Co-Authors: Nambisan RohitAbstract:Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, School of Engineering, System Design and Management Program, Engineering and Management Program, 2014.Cataloged from PDF version of thesis.Includes bibliographical references (page 87).The Post-Acute Care Transfer process is a critical area affecting the quality and safety of patient health care in the US'. While many Post-Acute Care (PAC) centers are Electronic Health Record (EHR) -enabled, a large majority of these centers, such as nursing home and home care, are not set up for exchange of electronic health information. Regardless of EHR capabilities, there are Currently no standards for health information transfer between PAC sites. The lack of standard and effective processes to collect and transfer critical patient health information during PAC transitions may be a critical component leading to issues with patient safety and quality during PAC Transitions. Additionally, issues resulting from Post- Acute care transitions (PAC transitions) are implicated as critical drivers for health care utilization in the US (2012 Medicare Chart Book). Funded by an Office of the National Coordinator Health Information Exchange challenge grant, Improving Massachusetts Post-Acute Care Transfers (IMPACT) is an innovative project managed by the Massachusetts eHealth Institute (MeHI) that will improve care transitions to and from post-acute care organizations in Massachusetts through the automation of a new Universal Transfer Form UTF for PAC transitions. Additional technical work includes creation of the Local Area Network Device (LAND) & Surrogate Electronic Environment (SEE) platforms, which together allow long-term care providers to send and receive patient information electronically through the Massachusetts HIway. MeHI is a SDE and recipient of American Recovery and Reinvestment Act (ARRA)/Health Information Technology for Economic and Clinical Health (HITECH) federal funds to create an HIE infrastructure in Massachusetts. MeHI seeks a thorough program evaluation of the IMPACT program. Due to the complex organizational, political, and technological architecture associated with the Post-Acute Care transitions and the interface between LAND & SEE and the HIway, a systems perspective is needed to accurately evaluate and provide recommendations to meet the needs of the program. The following describes the Current State Assessment for both 2012 and 2013 IMPACT program following the Enterprise Strategic Analysis for Transformation (ESAT) and Enterprise Architecting (EA) methodologies developed out of MIT's Sociotechnical Systems Research Center. Additionally, consideration is given to a future State Assessment, which is the ideal set of future State goal derived through a visioning workshop with key stakeholders.by Rohit Nambisan.S.M. in Engineering and Managemen
Pignatelli Francesco - One of the best experts on this subject based on the ideXlab platform.
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European Union Location Framework Blueprint (4.0)
'Publications Office of the European Union', 2020Co-Authors: Boguslawski Raymond, Valayer Clementine, Van Gansen Ken, Keogh Dara, Pignatelli FrancescoAbstract:Location data is fundamental to digital public services and the wider economy, delivering value in combination with other data, and supporting innovation through ‘location intelligence’. In this context, there is a need for interoperability supporting these services across Europe, and an important role for both government-authorised core location data and sector-specific location data. The European Union Location Framework (EULF) project, which was part of the Interoperability Solutions for Public Administrations (ISA) programme took action to tackle these challenges. The EULF vision is to create and promote a coherent European framework of guidance and actions to foster cross-sector and cross-border interoperability and use of location information in digital public services, building on national SDIs and INSPIRE , and resulting in more effective services, savings in time and money, and contributions to increased growth. The EULF Blueprint is a guidance framework for a wide audience to implement the EULF vision. It is based on an extensive EU survey and consultation with stakeholders and therefore embodies a wide range of views and experience. The EULF Blueprint has been updated periodically to keep pace with developments. This updated version (v4) has been produced by the European Location Interoperability Solutions for e-Government (ELISE) project, which is part of the ISA2 programme. The document has six main readers: Policy Maker; Digital Public Service Owner, Manager or Implementer; ICT Manager or Developer; Data Manager or Data Scientist; INSPIRE Data Publisher; and Private Sector Product and Service Entrepreneur / Developer. Readers can also use the Blueprint’s role-based approach to explore the document. The blueprint has five focus areas covering Policy and strategy alignment, digital government integration, standardisation and reuse, return on investment and governance, partnerships and capabilities. For each focus area, the ‘Current State’ Assessment and ‘vision’ are outlined. The key points for progressing from the Current State to the vision are then expanded into a series of 19 recommendations, each describing the rationale and expected benefits (why?), a checklist of associated actions (how?), potential problem areas in implementing the recommendation (challenges), a variety of best practices across Europe where this has been done successfully, cross-references to related recommendations in the European Interoperability Framework (EIF), and further reading related to the recommendation.JRC.B.6-Digital Econom
