1、AI-Ready Data EssentialsRoadmapHow to govern,qualify and align data to deliver value with AI2Roadmap:AI-Ready Data E Follow Us on LinkedIn Become a Client AI-readySource:GartnerWhat is AI-ready data?Why is it important now?Organizations that fail to realize the vast differences between AI-ready data

2、 requirements and traditional data management will endanger the success of their AI efforts.Without AI-ready data,the promise of AI will fail to materialize.Robust data management and governance are essential for success and can themselves be enhanced through AI-driven approaches.Learn the critical

3、steps and strategies for preparing data to harness the power of AI.Through 2025,of generative AI(GenAI)projects will be abandoned after proof of concept due to poor data quality,inadequate risk controls,escalating costs or unclear business value.30%Traditional data managementMake your data ready for

4、 AI.Make your AI ready for data.AI-ready dataGovernmentpoliciesData catalogingVisualizationAI data bias mitigation Chunking vector embeddingLineageData qualityAI data labelingSemanticsPrompt engineeringAI synthetic dataAI data enrichmentData productScalability performanceData engineeringBusiness-dri

5、ven workflow3Roadmap:AI-Ready Data E Follow Us on LinkedIn Become a Client What makes data AI-ready?AI-ready data means that your data must be representative of the use case,of every pattern,errors,outliers and unexpected emergence that is needed to train or run the AI model for the specific use.Dat

6、a readiness for AI is not something you can build once and for all,nor that you can build ahead of time for all your data.It is a process and a practice based on availability of metadata to align,qualify and govern the data.AI-ready dataSource:GartnerGoverncontextuallyQualifycontinuouslyAlign dataAI