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Partial Seminar List:
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Data Modeling
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ABSTRACT: Traditional entity-relationship modeling and normalization techniques capture only the structural and static relationships of data. This seminar addresses modeling the behavioral aspects of data to provide robust, high-integrity, value-centric application development and database design.
You learn how to apply object-oriented concepts to data modeling including inheritance and life cycle state, as well as how to model business rules and integrity policies. How to model time-dependent data and distributed data are addressed. Data models must support not just applications, but business process re-engineering, TQM processes, as well as rapid application development (RAD) projects. In this seminar you learn how to model generic data types to support flexible design. Accelerated data modeling workshops are required to support RAD projects while increasing consensus definition and stable enterprise data models. Critical to the success of data modeling workshops are techniques for managing group dynamics and team-building.
The real value of data models is when they are translated into flexible and stable databases with value-centric applications that implement effectively re-designed business processes. This seminar shows you how.
ADVANCED DATA MODELING AND VALUE-CENTRIC APPLICATION DEVELOPMENT
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ABSTRACT: The emergence of data warehouse, object technology, multi-media, document, rule-based and other complex data type technology has created a challenge to traditional data modeling methods. Furthermore, the World Wide Web has altered shape of both business work and information management.
Basic entity-relationship modeling and normalization techniques capture only the structural and static relationships of structured data. This seminar addresses semantic modeling of complex information types along with the behavioral aspects of data. This provides robust, high-integrity, value-centric application development and database design and exploitation of today's emerging technologies.
You learn how to apply object-oriented concepts to data modeling including inheritance and life cycle state, as well as how to model business rules and integrity policies. How to model time-dependent data and distributed data are addressed. Data models must support more than application development. They support business communication, business reengineering, TQM, Total Information Quality Management (TIQMTM ), and rapid application development (RAD) projects. You learn how to model generic data types to create flexible design that supports rapid business change.
Informational applications such as data warehouse, decision support and executive information systems require models that are inherently different from operational data models. You learn rules and guidelines for effective data warehouse modeling and design to support the strategic and tactical processes of the enterprise.
ADVANCED DATA MODELING:
Objects, Business Rules, and Other Important Things
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ABSTRACT: In the information age, the success of an organization will be driven by its effective use of its information resource. Characteristics of an effective information resource include flexibility to allow changes to the business processes, stability to allow new applications, and sharability to maximize the value of the information and reduce information float.
This seminar provides an integrated approach to data modeling that leads to flexible, stable and sharable database designs. This balanced and pragmatic approach enables you to maximize data sharing, minimize data redundancy, and make a positive impact on the effectiveness and bottom line of your organization.
CONCEPTUAL DATA MODELING:
Designing the Information Resource From the Business Perspective
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ABSTRACT: This seminar describes the trends in the evolution of application development in the information age.
It describes how one can-- and must-- exploit today's information technology for competitive advantage applications.
You learn the emerging directions in information management and data modeling along with their ramification on application engineering and information resource development.
You learn characteristics of a value-centric application architecture and approach that can reduce the cost of application development while increasing the quality of applications.
DATA MODELING FOR THE APPLICATION DEVELOPER
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ABSTRACT: In the information age, the success of an organization will be driven by its effective use of its information resource. This seminar does not just describe the mechanics of data modeling, it describes how to design quality in to data models. This seminar applies the quality principles of Kaizen, Quality Function Deployment (QFD) and Deming's 14 Points of Quality to the process of data and information modeling. Quality characteristics of an effective information architecture (both conceptual and physical) include:
- Stability to allow new applications without changing the existing architecture-- only adding
- Flexibility to allow changes to the business processes with minimal architecture change
- Reusability to maximize the value of the information and reduce information float
- "Consistently meet knowledge workers' expectations" to represent and house the information they must know to perform their work and accomplish enterprise objectives
DEVELOPING HIGH QUALITY DATA MODELS:
Applying Quality Principles to Information Architecture
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ABSTRACT: Reducing time to market is no longer an optional objective for all business activities. The challenge is how to meet ever decreasing time windows without compromising quality of data models. The answer is to apply workable techniques as applied in eXtreme Programming without acquiescing to its weaknesses.
RApid Data Development (RADD2TM ) approach to developing data models is a major tool for Information resource management in the Data Analysis and Modeling process. It applies the principles of Quality Function Deployment (QFD) to data model development. QFD is the active involvement of the customer in product design. Here knowledge workers, as information customers actively "design" the enterprise information products.
Benefits include reducing the time required for the modeling process; increasing communications among information systems and business professionals, and enhancing the value and shareability of the resulting data models.
This seminar presents the Who, What, When, Where, and How of conducting effective Rapid Data Development modeling workshops. You learn techniques for rapid development of conceptual data models. Highlights include tips on how to avoid pitfalls, how to minimize the risk of an incomplete model, how to validate the data model, and how to incorporate modeling tools and other support tools.
You learn how to resolve conflicts over data definition, and how to bridge communication gaps among cross-business area knowledge workers, systems development staff and information resource management to achieve consensus in data model definition.
You learn how to incorporate RADD workshops along with JAD (Joint Application Development) and RAD (Rapid Application Development) workshops to expedite the Information Systems development process.
In this seminar you learn the deliverables of the RADD data modeling workshop and how to manage the documentation process. You learn what skills are required of the workshop facilitator. Seminar participants will receive a self-assessment instrument to assist in understanding facilitator profiles.
You learn the techniques, group dynamics and the process of conducting a workshop approach to developing data models. This seminar includes a role-playing case study in which seminar attendees will participate in and evaluate the data modeling workshop process.
RAPID DATA DEVELOPMENT (RADD):
Conducting Rapid Data Modeling Workshops for Quality Data Models
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Data Warehouse
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ABSTRACT: The data warehouse can be a competitive advantage dream or a costly nightmare. Critical success factors include a well-defined and intuitive data architecture and quality data that supports the organization's strategic and decision support processes. This seminar addresses how to design the data warehouse to support competitive advantage uses even for potential uses not thought of today. You learn how to increase the value of operational data resources coupled with data from external resources.
Addressed are the differences in modeling data for strategic business processes and decision support as compared with modeling data for operational use.
DATA MODELING FOR DATA WAREHOUSE AND DECISION SUPPORT DATABASES
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ABSTRACT: A manufacturing firm wasted $1 million on its data warehouse before it recognized the need for quality data architecture and for data quality control in its data warehousing processes. A major bank scrapped a $29 million data warehouse to start over from scratch. The reason? Failing to understand and avoid the pitfalls described here. This tutorial details the essential ingredients of an effective information quality environment for the data warehouse.
Mr. English describes how to assess information quality (IQ) at the data sources and in the warehouse. You learn processes for correcting defective data and for preventing recurrence of data defects. Mr. English defines how to control data movement from source to warehouse. You learn both the technical and management requirements for a sustainable information quality environment for data warehousing.
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"This course has been the top-rated course in two [Data
Warehousing Institute] Implementation Conferences." - Data Warehousing Institute Leadership Conference brochure |
INFORMATION QUALITY IN THE DATA WAREHOUSE
Principles and Practice
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ABSTRACT: The advance of technologies, such as client/server, data warehouse, and data distribution are reshaping the roles of both application development and data management. Data management is taking on increasing importance to enable competitive advantage business process re-engineering and value-adding to the information resource through the data warehouse.
In this seminar you learn how to implement effective data management processes to manage data in client/server, distributed, and data warehouse environments as an enterprise resource. Management, technical, and organizational issues required to implement data resource management (DRM) effectively in the distributed and decentralized computing environment are addressed. Potential pitfalls facing DRM in the client/server environment are identified along with guidance on how to avoid them.
The key to successful exploitation of any new technology is understanding the underlying paradigm and re-thinking the rules and regulations of that paradigm. This seminar illustrates guidelines and techniques for modeling client/server applications and data.
The term "data warehouse" is an unfortunate term. This seminar focuses on the fact that the data warehouse is a "distribution center" used to "informate" knowledge workers.
IRM IN CLIENT/SERVER, DISTRIBUTED, AND DATA WAREHOUSE ENVIRONMENTS
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ABSTRACT: The data warehouse can be a competitive advantage dream or a costly nightmare. This seminar addresses how to plan and design the data warehouse to support competitive advantage uses--even for potential uses not thought of today. You learn how to increase value of operational data resources coupled with data from external resources. A key focus is how to manage the quality and consistency of the data within source databases and the data warehouse. You learn guidelines for how to avoid pitfalls to data warehouse to assure a quality strategic knowledge tool.
Addressed are the critical success factors of planning, organizing, directing and controlling the data warehouse for maximum value.
MANAGING THE DATA WAREHOUSE
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Information Quality
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ABSTRACT: As organizations jump into the e-Commerce and e-Business arena, failure to address information quality issues can produce Garbage-In-Garbage-Out @ the Speed of Internet. In this seminar you learn how to avoid the significant pitfalls so you can provide a quality experience for your Internet customers.
Mr. English describes how to measure, control and improve the quality of information in the Internet and at the data sources. Mr. English describes how to apply Total Quality data Processes to information in web pages, business data integrated with HTML data and information gathered though Internet transactions. He also addresses how to analyze causes of non-quality data and how toe improve the processes that cause the defects.
eQUALITY:
Quality in Internet and e-Business Information
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ABSTRACT: Do you know how much money and lost business your enterprise is wasting in process failure and "information scrap and rework" caused by poor quality information?
Information technology that is supposed to propel organizations into the Knowledge Age is often misused, forcing organizations into a state of primitive information "hunter-gatherers." Most managers and employees alike spend an inordinate amount of time in hunting for information, verifying, reconciling and correcting it, or creating their own "private databases" when they cannot trust the "corporate" data.
Mr. English defines the mandate and the "how-to" for executive management if they desire to be effective in the Information Age, eliminating the waste due to poor quality information. He describes important management principles applied to information that have not yet made it into the traditional management education programs, including:
- Sound business management applied to information as a strategic business resource, like those applied to financial, people, and other resources
- Quality improvement applied to information as a "product" of business processes, like those applied to manufacturing processes
All the business "restructuring" and "cost-reduction" efforts in the world will not save an organization that is failing because of squandered information resources. Mr. English describes what Executive Management must know and do to eliminate the process failure and costs of "information scrap and rework" caused by poor quality information.
INFORMATION QUALITY and BUSINESS EFFECTIVENESS:
Executive Management Mandate for Success in the Information Age
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ABSTRACT: This seminar describes the quality principles that must be applied to both business processes and information systems processes to achieve world class performance.
It outlines how to measure and improve information quality to reclaim the lost profits of poor quality information. This course provides guidelines for implementing the TIQM® Quality System environment to sustain an effective information quality environment for business effectiveness.
W. Edwards Deming's fourteen points of quality provide the basis for defining an information quality management environment. You learn management techniques for implementing sustainable information quality improvement. Illustrations show leading-edge best practices that result in business effectiveness and competitive advantage.
INFORMATION QUALITY IMPROVEMENT:
Processes and Best Practices for Business Performance Excellence
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ABSTRACT: A manufacturing firm wasted $1 million on its data warehouse before it recognized the need for quality data architecture and for data quality control in its data warehousing processes. A major bank scrapped a $29 million data warehouse to start over from scratch. The reason? Failing to understand and avoid the pitfalls described here. This tutorial details the essential ingredients of an effective information quality environment for the data warehouse.
Mr. English describes how to assess information quality (IQ) at the data sources and in the warehouse. You learn processes for correcting defective data and for preventing recurrence of data defects. Mr. English defines how to control data movement from source to warehouse. You learn both the technical and management requirements for a sustainable information quality environment for data warehousing.
"This course has been the top-rated course in two [Data Warehousing Institute] Implementation Conferences." - Data Warehousing Institute Leadership Conference brochure
INFORMATION QUALITY IN THE DATA WAREHOUSE
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ABSTRACT: The important principles of information management have not yet made it into the traditional management education programs. Those principles of managing information as a strategic business resource and applying quality management principles to information as a product-- not a byproduct-- are for an organization to survive and thrive in the "realized" Information Age.
Managers cannot provide effective leadership without quality information. Organizations cannot operate successfully without quality information from other units. Organizations cannot successfully contribute to enterprise goals without producing quality information. Yet most employees and managers spend an inordinate amount of time in hunting for information, verifying and correcting it, or creating alternative data resources when they cannot trust the "corporate" data. Mr. English addresses what managers must know about information quality management and what they must do to improve their business processes and effectiveness through quality information.
INFORMATION QUALITY MANAGEMENT:
What Every Manager Must Know and Do
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ABSTRACT: Information management is not solely an information systems responsibility. Information management is a responsibility of anyone and everyone in the enterprise who creates, updates, deletes, or uses information in some way.
The transition to the Information Age applies the same principles to the information resource as are applied to capital and human resources. Among those principles is accountability for the use of the business resources. In order to optimize the effectiveness of information management accountability must be applied to the definition of data and to the quality of data created, both in source databases and in migration to strategic databases (data warehouses).
This seminar addresses the several roles of information stewardship in the effective Information-Age enterprise. You learn how leading edge organizations have organized and implemented information accountability for information as a business-- not just a technical-- resource.
INFORMATION STEWARDSHIP:
Implementing Accountability for Information Quality
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Information Resource Management / Data Resource Management
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ABSTRACT: The decade of the 90s is redefining the role of data as the enterprise's second most valuable resource. Data resource management is enabling organizations to achieve competitive advantage, business re-engineering and enhancement of the business value chain.
In this seminar you learn the principles of information management and how to apply them in the business areas. You learn the goals and objectives information management must achieve to enable the information age. Addressed are the management and organizational issues required to implement information management effectively. Potential pitfalls facing information management are identified along with guidance on how to avoid them.
While organizations have recognized the requirement for quality improvement to be competitive in the 90s, and I/S functions have recognized the need to improve the software quality process, very little has taken place to measure and improve the quality of data. This seminar describes metrics for measuring the quality of data and management techniques for implementing a total quality program for information management. You learn how organizations have implemented steps to measure and improve the quality and effectiveness of their information management.
In order to optimize the effectiveness of information management as a resource, there must be accountability for that resource in a way similar to accountability for financial and human resources. This seminar addresses the role of information stewardship in information management in the business areas.
INFORMATION MANAGEMENT PRINCIPLES FOR KNOWLEDGE WORKERS
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ABSTRACT: The explosion of information technology moves relentlessly ahead; far faster than the typical organization's ability to assimilate and effectively manage and exploit it. Internet and Intranet technologies have redefined the information environments. This demands a redefinition of information management (IM) and data resource management (IRM).
This seminar is about two things: (1) Survival, and (2) "Thrival" (1) Survival-- not of individual information professionals-- but of the enterprise itself. (2) "Thrival" means not only do those organizations who practice the principles outlined here survive, but they will also thrive: increasing market share and profits while reducing costs and time-to-market. This seminar describes the core competencies for information management (IM) to make the Knowledge-Age transition.
INFORMATION MANAGMENT IN THE VIRTUAL ENTERPRISE:
Managing the Convergence of Internet and Enterprise Data
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INFORMATION RESOURCE MANAGEMENT IN THE KNOWLEDGE AGE:
The Evolution of Data Administration
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Information Visioning and Strategy
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ABSTRACT: The organization that is not managing its information cannot manage its business. Without managed, quality information, the enterprise cannot "know" what it needs to know to understand its customers and customer needs, manage operations, analyze its performance and make the strategic decisions for the future of the enterprise. This is even more crucial for service sector organizations, such as banks, insurance and government organizations whose products are, in fact, information.
This executive discussion describes how the principles used to manage other business resources, such as human and financial resources, apply to managing information and knowledge as strategic resources. Implementation of these principles is required to transform the "data processing" function into true "Information Management" (IM), and transform the enterprise from an industrial-age to an information-age organization. This presentation discusses how the organization can harness the power of today's information technology to exploit its information resources for competitive advantage.
CREATING THE INFORMATION-AGE ORGANIZATION:
for Business and Systems Effectiveness in the Information Age
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ABSTRACT: In this new economy, organizations that fail to exploit today's and tomorrow's information technology to re-engineer their business processes may not be around to see the 21st century. Companies that do not engineer their computer applications from an information and integrated systems architecture based on their company's strategic business plans may fall significantly behind their competition.
This seminar shows you how your organization can more fully exploit today's information technology for strategic advantage by applying the same management principles as are used to manage other corporate assets. This begins with strategic information planning as an integral part of strategic business planning.
Strategic information plans that are based on strategic business objectives are three times more likely to be successful than long range systems development plans which are not. This workshop will focus on how your organization can develop more successful long range systems development plans through a planning process which integrates the business plans and information systems development.
STRATEGIC INFORMATION ARCHITECTURE:
Integrating Business Plans and Information Systems Development
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