Your presenter: Dr. Peter Aiken
Dr. Peter Aiken is widely acclaimed as one of the top ten data management authorities in the world. In addition to examining the data management practices of more than 500 organizations, he has spent multi-year immersions with organizations as diverse as the U.S. Department of Defense, Deutsche Bank, Nokia, Wells Fargo, the Commonwealth of Virginia, and numerous other high profile clients. As President of DAMA International, his expertise in the practice is unquestioned. He has been an Associate Professor at Virginia Commonwealth University's School of Business Information Systems Department since 1993 and owns Data Blueprint, an award-winning data management and IT consulting firm.
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March Webinar: Practical Data Modeling
Tuesday, March 13, 2012; 2:00 PM - 3:30 PM ET (11:00 AM- 12:30 PM PT)
This presentation provides you with an understanding of the data modeling and data development components of data management. Participants will understand how the analysis, design, implementation, deployment, and maintenance of data solutions should be approached in order to maximize the full value of the enterprise data resources and activities. Architecting in quality is imperative at this level and complements a subset of project activities within the system development lifecycle (SDLC) focused on defining data requirements, designing data solution components, and implementing these components. Participants will understand the difficulties organizations experience when interacting with data development efforts and how to best incorporate these efforts into specific data projects.
Learning Objectives:
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What is data modeling? What is data development?
- Why are they important and how do they compare?
- Where do they fit in as data management components?
- Data modeling/development frameworks
- Considerations for improving data modeling and data development within your organization
- Guiding principles & best practices
April Webinar: Data Operations Management: Turning your Challenges into Success
Tuesday, April 10, 2012; 2:00 PM - 3:30 PM ET (11:00 AM- 12:30 PM PT)
While database operations comprise the majority of the organizational data operations management focus, other data delivery options, e.g. portals and virtualization, are interacting with increasingly complex regulatory environments. This presents organizations with dense analysis challenges in order to understand reporting obligations. Using the Zachman Framework as a guide, you will learn how to understand and approach data operations challenges from tuning to real-time reconfiguration. This presentation provides you with an understanding of data operations management, including the initiation, operation, tuning, maintenance, backup/recovery, archiving and disposal of data assets in support of organizational strategies and other activities.
Learning Objectives:
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What is data operations management?
- Why is data operations management important?
- Considerations for improving data operations management within your organization
- Guiding principles & best practices
May Webinar: How Safe is Your Data? Data Security Webinar
Tuesday, May 15, 2012; 2:00 PM - 3:30 PM ET (11:00 AM- 12:30 PM PT)
If you have ever used passwords such as “123456” or simply “password” then you need to attend this webinar! Our presentation provides you with an overview of the organizational data security management requirements that are necessary to meet industry benchmarks. Participants will understand the requirements for planning, developing, and executing security policies and procedures to provide proper authentication, authorization, access, and auditing of data and information assets. By the end of our session, you will understand how effective data security policies and procedures ensure that the right people can use and update data in the right way, as well as the importance of restricting inappropriate access.
Learning Objectives:
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Top data security concerns & requirements
- The cost of not having accurate security
- Data security statistics & examples of security breaches
- Passwords & policy examples
- Data security management framework
- Guiding principles & best practices
June Webinar: MDM and Data Quality: Not an Option but a Requirement
Tuesday, June 12, 2012; 2:00 PM - 3:30 PM ET (11:00 AM- 12:30 PM PT)
This presentation provides you with an understanding of the goals of reference and master data management (MDM), including establishing and implementing authoritative data sources, establishing and implementing more effective means of delivery data to various business processes, as well as increasing the quality of information used in organizational analytical functions (such as BI). You will understand the parallel importance of incorporating data quality engineering into the planning of reference and MDM.
Learning Objectives:
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What is reference and MDM?
- Why are reference and MDM important?
- Reference and MDM Frameworks
- Guiding principles & best practices
July Webinar: Practical Applications for Data Warehousing, Analytics, BI, and Meta-
Integration Technologies
Tuesday, July 10, 2012; 2:00 PM - 3:30 PM ET (11:00 AM- 12:30 PM PT)
Meta-integration is considered data warehousing by some, while others describe it as data virtualization. This presentation provides an overview of meta-integration starting with organizational requirements. We will discuss how meta-models can be used to jump-start organizational efforts. Participants will understand the strengths and weaknesses of various technological capabilities, and the key role of data quality in all of them.
Learning Objectives:
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What are data warehousing, analytics, BI and meta-integration technologies and why are they important?
- Organizational requirements
- Strengths and weaknesses of technological capabilities
- Top 10 data warehouse failures
- They key role of data quality
- The use of Meta models
- Frameworks
- Guiding principles & best practices
August Webinar: Structuring Your Unstructured Data: Document & Content Management
Tuesday, August 14, 2012; 2:00 PM - 3:30 PM ET (11:00 AM- 12:30 PM PT)
Non-tabular data plays an increasing role in organizations. While we are still far away from automated content comprehension, increasingly sophisticated technologies are extending our data management capabilities into more critical and more regulated areas. This presentation provides you with an understanding of the dimensions of this vast new area, including electronic and physical document monitoring, storage systems, content analysis and archive, retrieve and purge cycling.
Learning Objectives:
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What is Document & Content Management?
- Why is Document & Content Management Important?
- Planning and Implementing Document & Content Management
- Levels of Control
- Backup & Recovery
- Retention & Disposition
- Audits
- Frameworks for Document & Content Management
- Guiding principles & best practices
September Webinar: Let’s talk Metadata: Strategies and Successes
Tuesday, September 11, 2012; 2:00 PM - 3:30 PM ET (11:00 AM- 12:30 PM PT)
Commonly described as metadata management, properly implemented metadata practices incorporate data structures into more abstract processing. By using data about the data to enhance its value, its understandability, ease of use and many other options, organizations have developed sophisticated ways to enhance their data management and especially their data quality engineering efforts. Join us to learn more about specific metadata benefits and how to leverage it to achieve success within your organization.
Learning Objectives:
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What is Metadata? Why is Metadata important?
- Major metadata types & subject areas
- Important metadata benefits
- Metadata strategies & implementation
- Frameworks
- How to leverage metadata to your success
- Guiding principles & best practices
October Webinar: Engineering Solutions to Data Quality Challenges
Tuesday, October 9, 2012; 2:00 PM - 3:30 PM ET (11:00 AM- 12:30 PM PT)
This presentation provides guidance to organizations considering or preparing for data quality initiatives. We will illustrate how organizations with chronic business challenges often can trace the root of the problem to poor data quality. Showing how data quality can be engineered provides a useful framework in which to develop an organizational approach. This in turn will allow organizations to more quickly identify data problems caused by structural issues versus practice-oriented defects. Participants will also learn the importance of practicing data quality engineering quantification.
Learning Objectives:
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What is data quality and why is it important?
- Data quality concepts & activities
- Data Quality Management (DQM) cycle
- Data quality awareness & requirements
- Data quality dimensions
- Case Study: Data Quality Golden Rules
- Data quality tools & frameworks
- Guiding principles & best practices
November Webinar: Get the Most Out of Your Tools: Data Management Technologies
Tuesday, November 13, 2012; 2:00 PM - 3:30 PM ET (11:00 AM- 12:30 PM PT)
This presentation provides an overview of the many types and classes of useful technology available to data managers. These include: computer aided software/systems engineering (CASE) tools, repositories, profiling/discovery tools, data quality engineering technologies, and data integration servers.
Learning Objectives:
- Understanding data technology requirements
- Defining data technology architecture
- A closer look at tools and how to leverage them to your success
December Webinar: Show Me the Money: The Business Value of Data and ROI
Tuesday, December 11, 2012; 2:00 PM - 3:30 PM ET (11:00 AM- 12:30 PM PT)
Failure to successfully monetize data management investments sets up an unfortunate loop of fixing symptoms without addressing the underlying problems. As organizations begin to understand poor data management practices as the root causes of many of their problems, they become more willing to make the required investments in our profession. This presentation uses specific examples to illustrate the costs of poor data management. Join us and learn how you can apply similar tactics at your organization to justify funding and gain management approval.
Learning Objectives:
- The general ineffectiveness of data management investments
- Root case analysis of data-related IT systems failures
- Several success stories/monetization examples
Partnership
Our webinars are brought to you in collaboration with:
The Online Education Portal for Data Management Professionals
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