Product ideas | Community
Skip to main content

Ideas

Filter by idea status

10000+ Ideas

RobertDo1Level 2

Separate expenses between what was budgeted and what was plannedNew

Description / Why is this feature important to you / Current Behaviour - Workfront has the ability to separate labor costs between what was budgeted, what is planned, and what are actual labor costs. While there is an ability to separate expenses between what expenses are planned and what are the actual expense results, Workfront does not have the ability to separate expenses between what was budgeted and what was planned.  A project's baseline / approved budget in terms of expenses must be stored outside of Workfront.   Planned expenses entered on the Expenses dashboard tab and/or on Tasks get automatically updated on the Business Case. If a project manager adds planned expenses that weren't budgeted, how would we report a variance between budgeted and planned expenses?  Answer:  Workfront users are not able to report a variance between budgeted and planned expenses. How would you like the feature to work -Similar to how a budget is entered on the business case for labor, allow the expenses entered there to be the baseline budget separate from planned expenses.  Planned expenses would be separate and change to reflect what is expected to happen, whereas the budgeted expenses would remain equal to the baseline approved budgeted expenses.   Users would then be able to report between budgeted expenses, planned expenses, and actual expenses, similar to how users are able to report between budgeted labor, planned labor, and actual labor.  

Purge lookup dataset before new data load via Data DistillerNew

For audience composition, enrichment with a lookup dataset is a useful feature. However to generate the lookup dataset, either an external data load or a scheduled query in Data Distiller is needed to populate the dataset.Quite often this data is of a "refresh" nature, i.e. the best way to handle is to purge the dataset, and reload the fresh data - as record links may also be deleted in the new load.Dropping the dataset, and creating a new one with CTAS is not an option, since the reference link for enrichment in the Audience Composition would need to be restored. Why is this feature important to you - we have multiple use-case scenarios where we have to enrich a certain segment with extra data for personalization in AJO.- we have also use-cases where the rule segment builder is insufficient to design the query - a designated more complex query (via query service) is needed to prepare extra data which can be used in to filter on. Adding this extra data to the profile could bloat the profile at the end (if multiple of these scenario's are needed). How would you like the feature to work- the ability to run a CTAS "replace" query, where the previous inserted batch is deleted before the new batch is inserted Current Behaviour- batch deletion is only possible via API, and needs an external process to manage. We would like to have an option which is part of Data Distiller and does not require an external process.

aanchal-sikka
Community Advisor
aanchal-sikkaCommunity Advisor

Data Validation and Compliance ReportingInvestigating

Request for Feature Enhancement (RFE) Summary: This feature will enable organizations to define metadata validation rules based on compliance or guideline requirements and extract detailed reports for discrepancies. This will facilitate better data governance and streamlined updates to metadata across the organization. Use-case: Organizations often face challenges ensuring metadata adheres to evolving compliance regulations or organizational guidelines. Manual validation processes are time-intensive and error-prone, leading to non-compliance risks and inconsistencies in metadata quality. This feature addresses the need for automated validation and actionable reporting. Current/Experienced Behavior: Metadata validation is performed manually or using scripts, leading to inefficiencies. There is no unified interface or reporting mechanism to validate metadata against dynamically defined compliance rules. Discrepancies or outdated metadata are identified late, causing delays in remediation and compliance violations. Improved/Expected Behavior: Provide an intuitive interface for users to define validation rules for metadata (e.g., required fields, formatting, values adhering to controlled vocabularies). Automate metadata validation against these rules and generate detailed discrepancy reports. Offer configurable outputs (e.g., exportable reports in CSV/Excel formats) for review and remediation. Integrate with workflows for updating and re-validating metadata. Include support for recurring or scheduled validation processes. Ensure compatibility with diverse metadata structures and schemas. Environment Details (AEM version/service pack, any other specifics if applicable): AEM 6.5 Customer-name/Organization name:   Screenshot (if applicable):   Code package (if applicable):