Skip to main content

Filter by idea status

10000+ Ideas

Data Science Services to allow deployment of custom machine learning modelsNew

Description: Presently, the Data Science services section only accommodates Customer AI, primarily utilized for generating propensity scores for diverse profiles. However, it falls short in empowering customers to deploy their personalized machine learning models. This limitation necessitates a reliance on alternative tools, hindering the full utilization of data resources.Why is this feature important to you: The integration of this feature is crucial as it opens avenues for deriving tailored insights from data, aligning precisely with the unique requirements of each customer. The absence of the ability to deploy individual machine learning models constrains the potential utility of the available data, impeding the generation of valuable, customer-specific insights.How would you like the feature to work: We propose the enhancement of the RT-CDP (Real-Time Customer Data Platform) by incorporating the capability for users to deploy their personalized machine learning models within the Data Science framework. This can be facilitated by introducing a new, user-friendly interface for the data science workspace, akin to existing solutions like Treasure Data. Enabling seamless integration and deployment of custom models would empower users to extract more meaningful and targeted insights from their data.Current Behaviour: At present, the platform is limited to the out-of-the-box (OOTB) Customer AI Intelligent services. While these services provide valuable functionalities, the absence of an option to incorporate individual machine learning models into the platform confines users to the predefined capabilities. This creates a gap where users cannot fully leverage their data for more specific and nuanced analyses. The current system lacks the flexibility required to accommodate the diverse machine learning models that users may want to deploy.

Rohan_Garg
Rohan_GargNew Participant

AEM Version Updates - Automatic Updates - Handle custom code pushed to Staging but not ProductionInvestigating

Request for Feature Enhancement (RFE) Summary: Ensure AEM Maintenance Update releases respective code artifacts to Stage and Production Environments  Use-case: We currently do Stage deployments on a weekly basis and Production deployments on bi-weekly basis. However, the AEM Maintenance Update pushes back the baseline code to last successful deployment for Production to Stage as well. This then requires another Stage.Ideally as the pipeline is able to pick up the last commit id of the deployment to Production, it should also be able to pick up the Commit Id of Stage and deploy the necessary artifacts. This deviates from the usual principle of deploying same artifacts on Stage and Production but helps to keep the system in as-is state before and after Maintenance Updates. Current/Experienced Behavior: The custom code that was only available on Stage gets lost and has to be deployed again. Improved/Expected Behavior: The Production instance should have the last known production deployment artifacts while the Stage instance should similarly have its last deployed artifacts to ensure continuity. Environment Details (AEM version/service pack, any other specifics if applicable): AEMaaCS (AEM Release - 2023.12.14538.20231205T165334Z) Customer-name/Organization name: TA Digital Screenshot (if applicable): AEM Version Updates | Adobe Experience Manager Code package (if applicable): N.A

Adilos-Cantuerk
Adilos-CantuerkNew Participant

A better differenciation between AssetExpired and SubAssetExpiredInvestigating

Zusammenfassung der Funktionsverbesserungsanfrage (RFE): Better differenciation between Asset-Is-Expired and SubAsset-is-ExpiredVisual by not having a red flag for both - and for the filter. Anwendungsfall: The red flag icon on the thumbnail warns that an Asset is expired. This red flag indicates that a file can not be downloaded. BUT this warning is used by the system for two different occasions.AssetExpired and SubAssetExpired.An InDesign file might contain an expired picture.Now that InDesign file will be displayed with a red flag.But the InDesign file itself is not expired and can be downloaded.Therefore i suggest that there needs to be a better differenciation.Visualy as well as for the expiry search filter. Aktuelles/erlebtes Verhalten: If a picture expires that is built into 1000 documents, the expiry filter now lists 1001 expired assets - even there is only a single expired asset and a 1000 assets in which this picture is a dependency.There is no visual differenciation between an expired InDesign and an InDesign that simply contains an expired asset. Users see the red flag and get the impression that the file can not even be downloaded.  Verbessertes/erwartetes Verhalten: For the Thumbnails, this can easily be done by having a small change in /libs//dam/gui/coral/components/admin/contentrenderer/card/asset/propertyList.jspThis already checks between the two states:if ((isContextCollection || properties.contains(VIEW_PN_IS_ASSETEXPIRED)) && (isAssetExpired || isSubAssetExpired)) { %>    <coral-card-property class="expirystatus" icon="flag" data-is-asset-expired="<%= isAssetExpired %>"                         data-is-sub-asset-expired="<%= isSubAssetExpired %>"                         title="<%= xssAPI.encodeForHTMLAttr(i18n.get("Expired")) %>"></coral-card-property>    <% } I changed this for my organisation, but i think it would be a great improvement for everybody OOTB. Umgebungsdetails (AEM-Version/Service Pack, ggf. weitere Angaben):   Name des Kunden/der Organisation: medi GmbH & Co. KG Screenshot (sofern zutreffend): Code-Paket (sofern zutreffend):