How much historical CRM data is enough for your AI initiatives?
1. Leveraging Historical Data
– Increasing importance of historical CRM data in AI applications.
– Salesforce’s Data Cloud offers transformative tools to utilize this data effectively.
2. Key Considerations
– Importance of determining the right amount of historical data for integration.
– Risks of data loss or increased costs if not managed properly.
3. Implications for Data Cloud Users
– Deletion of records from source objects affects Data Cloud storage.
– Need for careful management to utilize historical data for AI without incurring high storage costs.
4. Data Management Strategy
– Archiving as a strategic decision to balance availability and cost.
– Consider factors like data usage frequency and compliance for archiving.
5. Working with Archived Data
– Use of AppExchange solutions ensures accessibility of archived data.
– Integrate archived data with Salesforce Data Cloud and existing architecture for seamless access.
6. Actionable Steps for Salesforce Professionals
– Develop comprehensive architecture plans for immediate and long-term data management.
– Advise clients on data archiving to optimize storage costs and system performance.
Technical debt in Salesforce can hinder business growth. It often arises from quick fixes and can lead to higher costs and inefficiencies. Understanding and addressing this debt is crucial for maximizing ROI and supporting strategic objectives.
Optimize your data architecture to balance between resilience and cost. By strategically managing your data, you can drive impactful AI initiatives and enhance business growth.
You can read it here: https://sfdc.blog/QCyDI
Source from salesforceben(dot)com