Joe B. on Data Principles

Blogger: Chris Haddad

 

Burton Group is fortunate to have Joe Bugajski on board as a Senior Analyst covering Data Access Strategies. Joe is a seasoned data architecture veteran who recently was vice president of Global Standards and Interoperability at Visa. Reporting to Visa’s Global CTO, Joe was responsible for worldwide interoperability of VisaNet data and applications and global service standards for transactions processing and payment data management. 

For his first Burton Group research report, Joe is writing about .NET 3.5 Support for Data Services: LINQ and ADO.NET. To put Microsoft's data technologies in context, Joe has created a data principle evaluation framework. The framework reviews capabilities in the following areas:

• Data Assets: Increase their value
• Enterprise Architecture: Support technology standards, goals, and plans
• Software Development: Promote code quality, reliability, simplicity, and security
• Development Management: Meet business objectives

While explaining the data principles framework would require an entire research report (hopefully one Joe will write soon), I have distilled out key evaluation criteria for this blog entry:

Data Assets: Increase their value

•Assure fidelity of data typing

•Preserve (business) semantics

•Understand reliability of data semantics

•Understand the quality of the data

•Map business semantics to actual semantics

•Minimize data movement

•Understand stored form of data and query logic

•Define information preserving data format conversions

•Calculate data access volumes

•Measure instantaneous rate of change of data values

•Measure total cycle time from access to persistence

•Understand persistence needed for disaster recovery

•Meet information steward’s requirements for data access

•Maintain principle of least access

•Secure private and sensitive data during access and use

EnterpriseArchitecture: Support technology standards, goals and plans

•Minimize code and architectural complexity

•Minimize total number of suppliers and contracts

•Minimize total number of active data formats

•Promote enterprise architecture plans

•Support multi-tier maintenance services

•Achieve compliance with internal technical standards

•Maintain semantic interoperability

•Preserve and enhance value of metadata stores

•Provide for data usage traceability and auditability

•Support nonfunctional requirements; e.g. security architecture

•Maximize continuity of architectural styles

•Maximize code and services reuse

•Maximize use of existing data stores

Software Development: Promote code quality, reliability, simplicity and security

•Minimize costs and time required to deliver code

•Minimize language complexity

•Minimize code complexity

•Minimize context switching (time lost in obscurities)

•Minimize coding errors

•Achieve closest match to functional requirements

•Meet nonfunctional requirements

•Promote code portability

•Promote reliable code walk-through

•Support frequent builds

•Support regression testing

•Optimize use of working prototypes

•Maximize unit testing

•Maximize code quality

•Maximize code readability

•Maximize ease of maintenance

Development Management: Meet business objectives

•Minimize number of coding styles across projects

•Support budget and time constraints

•Improve capability to size projects

•Promote growth of developer knowledge and skills

•Minimize personnel turnover

•Minimize requirements churn

•Avoid increasing scope

•Minimize the number of surprises

•Maximize developer efficiency and effectiveness

•Maximize ability to reassign personnel

•Achieve organizational objectives

How well do these criteria match your data technology evaluation and incubation process? I look forward to reading Joe's report detailing how LINQ, ADO.NET, and the Entity Framework rate against the framework.