Trusted Analytics - 10 weeks - Assessment

We help you to ensure the risks that arise from the development, implementation and deployment of machine learning & AI solutions are controlled properly. We assess the way of working of your AI and analytics development teams with the Microsoft Azure platform, and recommend development of best practices & guidelines for the proper and controlled use of Microsoft Azure. You use a Microsoft Azure-based infrastructure and way of working in place for your analytics & AI development activities or intend to migrate towards it. You already have - or want to put in place - Company Ethics, Risks and Controls framework, & QA processes for Big Data and AI. This may cover development and deployment of infrastructure requirements, use of Azure services for meeting development process and deployment audit trail requirements, use of Azure services for data preparation and modeling reperformance capability, use of Azure services for access control on data and predictive models, best practices for merging, testing and building, explainability, fairness, and reliability of predictive models using Azure ML and Cognitive services.

Phase 1 – Review of existing Risks and Controls framework,& Quality Assurance processes

• Desk research & documentation analysis
• Interviews with business owners, internal QA and auditors Output: overview of QA controls that impact the development process and infrastructure with prioritization based on business value.

Phase 2 – Gap Analysis on way of working of your development teams with Azure services

• Desk research & documentation analysis
• Interviews/workshop with developers to review way of working Output: gap analysis between QA controls and Microsoft Azure platform usage.

Phase 3 – Recommend strategy for closing gaps

• Prioritize gaps & investigate Azure best practices. Potential use of guidelines for closing gaps
• Finalize recommendations & report
• Output: report of gaps, prio's & recommendations

Investment based on size of landscape