Bulk Object Field Creator
BOFC (Bulk Object Field Creator) is a 100% native Force.com app built to simplify bulk Salesforce metadata operations. It helps Admins and Developers easily manage, compare, and move metadata with just a few clicks. It saves time, reduces mistakes, and boosts productivity by supporting tasks like cloning, exporting, updating, and comparing across one or multiple Salesforce orgs. Major Features: ⚡ Perform bulk Create, Update, Delete (CRUD) operations on Objects and Fields 🔄 Clone metadata like Flows, Profiles, Picklists, Permission Sets, and Reports across the same or external orgs 📊 Compare & Export multiple Profiles, Permission Sets, and Process Builders 📂 Export Objects, Fields, Validations, Record Types, Page Layouts, and Rules (Assignment, Validation, Workflow) ✅ Export & Update Field Permissions at scale 🛠 Import, Update, Delete, and Export Validation Rules 🎯 Bulk update Picklist values for multiple Record Types 🧩 Manage Process Builders, Permission Set Assignments, Flows, Apex & Visualforce Code (using Code Comparator) NOTE: - 24×7 dedicated support with quick response times. - 100% Native Salesforce App—does not transfer data or send emails from Salesforce
Top keywords
- bulk4×2.40%
- export4×2.40%
- salesforce4×2.40%
- update4×2.40%
- metadata3×1.80%
- multiple3×1.80%
- permission3×1.80%
- 1002×1.20%
- 100 native2×1.20%
- builders2×1.20%
- code2×1.20%
- compare2×1.20%
Einstein Discovery Writeback
READ BEFORE INSTALLING. Einstein Discovery is best used out of the box. We encourage you to use native, no code write-back functionality. Use this managed package only if the native write-back functionality does not meet your business needs. A story includes what happened, why it happened, predictions and recommendations for a given outcome variable. A model is the portion of a story that includes: explanations (why it happened) predictions (what could happen) recommendations (what to do to improve a predicted outcome) Every story includes a desired goal to maximize or minimize the outcome. For example, if you want to predict time to close on an opportunity, you can have separate models for small and large opportunities. You can use this approach if the behavior of your opportunities changes depending on their size. You could create a model on your large opportunities dataset and deploy that to Salesforce. Then you could create a model on your small opportunities dataset and append your small model to the same prediction and recommendation settings. In this context, the model is the segment.
Top keywords
- model5×2.81%
- opportunities4×2.25%
- happened3×1.69%
- includes3×1.69%
- outcome3×1.69%
- small3×1.69%
- story3×1.69%
- dataset2×1.12%