Tom Haughey is currently President of InfoModel, Inc., a training and consulting company specializing in practical and rapid development methods. His courses on data management, data warehousing, and software development have been delivered to Fortune 1000 companies around the world. He has worked on the development of seven different CASE tools, over 40,000 copies of which have been sold to date. He was formerly Chief Technology Officer for the Pepsi Bottling Group and Enterprise Director of Data Warehousing for Pepsico. He wrote his own CASE tool in 1984.He formerly worked for IBM for 17 years as a Senior project manager. He is the author of many articles on Data Management, Information Engineering and Data Warehousing.
 

The Transition from Logical to Physical
The process of moving from a Logical Data Model to an initial Relational Database Design is the same regardless of the specific database product.  This presentation will cover the essential steps to kick starting a basic relational database design starting with a fully attributed logical data model.

Special Topics in Data Warehouse Design
This presentation will cover selected advanced topics in Data Warehouse Design.
 

Eric Offenberg, CIPP and Product Marketing Manager at Princeton Softech, an IBM Company, has established himself as a data privacy thought leader. With nearly 10 years of technology marketing experience across industries, Offenberg speaks on data privacy compliance issues in live Webinars, industry events and with media and analysts on behalf of Princeton Softech. He holds an MBA with a concentration in marketing from Rider University and a BA degree in communications with a concentration in public relations from Rutgers University.

Essentials of Test Data Management

Creating realistic and consistent test databases is the first step in delivering reliable database and/or application enhancements and upgrades.  But with multiple database clones to configure and manage, your costs can quickly spiral out of control.  Testing cycles are extended, and releases are delayed.  So, how can you support rapid database and application deployment while controlling costs?   Join us for a discussion of proven test data management techniques. 

Learn how organizations have reduced storage costs and sped iterative testing cycles by creating “right-sized” test environments which accurately represent the structure of relevant data models.  Hear how sites can automate the comparison of baseline data against successive test run results to quickly identify application errors.  Learn about application-aware data masking techniques that sites can leverage to de‑identify and protect confidential information in test databases. 

Learning points:

·        Streamline test data management, speed delivery of application enhancements and reduce costs

·        Effectively protect confidential test data by masking personally identifying information like credit card and national identification numbers

·        Find errors early in the application lifecycle, where they are cheaper and easier to fix

·        Improve operational efficiencies by shortening iterative testing cycles, improving test coverage and ensuring accuracy