Ambassador
James Knapp
VP, Strategy & Architecture
United KingdomVerified Community AmbassadorContent James is Following
There is no structured methods but do it adhoc depending on business needs
There is no check & balances
Mature processes, having dedicated Data Governance & steward and Data QA practices handles Data Quality
Business manages it on their own way
Strongly Agree
Agree
Disagree
Strongly Disagree
What experiences have you had with AI Guardrails across Google Gemini (for Workspaces). We’re concerned about amplifying access to sensitive files (I.e. access already exists but Gemini now surfaces insights from these files so much more readily). We'll tighten up access controls and likely implement Google Workspace AI Classification, but we’re also considering selecting and implementing an AI Guardrails vendor. Which vendors do people have experiences with? Aporia, Arize, Bedrock, Databricks, Guardrails AI, IBM, Nvidia, Whylabs Which features were most relevant and useable? Bias Mitigation, Explainability, Data Privacy, Security, Regulatory Compliance Is a vendor needed? Could a homespun collection of Gems suffice?
1.7k views2 Upvotes
SAP continues to drive 'Clean the Core' or more recently 'Cleaner Core'. Besides removal of unnecessary or unused WRICEF code (a waste of time effort in my eyes), looking for any real clean you have done and found beneficial. One thought we have had is to move off some of the SAP capability and move to SaaS solutions integrated via an orchestration layer. Thus reducing our SAP footprint and moving us towards a viable S/4 upgrade. Any thoughts on this 'cleaning' approach?
James KnappVP, Strategy & Architecture in Media3 months ago
Thanks. Likewise I would like to know how we can DIY clean core rather than engage PS
1 Reply
1.8k views1 Upvote2 Comments
Land a pilot/POC that people care about and are willing to advocate for as the stepping stone to your broader rollout.