In the era of big data and advanced analytics, leveraging historical CRM data for AI applications is becoming increasingly significant. Salesforce, a leader in this domain, offers robust tools like Data Cloud that can transform the way businesses utilize their data.
However, there’s an important question that is often skipped: “How much historical data should we use, and what’s the best way to set up our data integration architecture?”. Failure to consider this may lead to unexpected data loss or increased operational costs. Intrigued?
When Data Deletion Becomes a Double-Edged Sword
If you are familiar with the Salesforce Data Cloud connectors, such as the out-of-the-box CRM connector, you know that if you delete a record from the source object, it is automatically removed from Data Cloud. On the surface, this could look like a good thing. After all, it simplifies removing bad records or records due to a privacy request, right? Not so fast.
Storage in transactional systems, or systems of record, is expensive. For this reason, high-availability solutions routinely remove and archive historical transactions. However, that same data set may be incredibly impactful for predictive or generative AI solutions or analytics.
Our system of reference solution architecture decisions, and Data Cloud is a system of reference, must consider the utility of historical data for AI and analytics and how to manage that data.
Storing Data in Transactional Systems Can Be Pricey
Transactional systems often require high availability, supporting multiple simultaneous business transactions, and the cost of storage is expensive. It’s why many organizations archive old transactions that aren’t needed day-to-day but might be gold mines for AI.
Take emails or activities in your CRM, for instance. We hardly look back at communications older than a few months, yet this historical data can be crucial for understanding trends and making predictions.
Organizations that implement data archiving strategies often see significant reductions in storage costs, with some reporting up to a 50% decrease. This substantial cost saving is primarily due to moving rarely accessed yet compliance-necessary data out of primary storage systems. This strategic data management not only optimizes storage expenses but also enhances overall CRM system performance, facilitating faster and more efficient daily operations.
Archiving Is Part of Your Data Management Strategy
Incorporating data archiving into the solution architecture is a strategic decision.
It allows for historical data to be stored cost-effectively while still being accessible for business transactional use case exceptions, as well as for AI and analytics. This approach ensures data availability without the prohibitive costs associated with high-availability storage solutions.
As Salesforce Consultants and Architects, it is our responsibility to guide customers through the complexities of data management. This involves making informed decisions about which data to retain actively in the systems of record and which to archive. The decision-making process should consider factors like data usage frequency, compliance requirements, and the potential impact on AI applications.
Working with Archived Data
Archiving your Salesforce CRM data using AppExchange solutions like Capstorm or Own Company doesn’t mean it’s out of reach for your end users. With the right security settings and application configurations, you can ensure that select users have access to historical records within the CRM itself, streamlining compliance-related processes without needing to switch applications.
Integrating this historical data into Salesforce Data Cloud also aligns with your existing integration architecture strategy. Whether leveraging zero-copy integration for seamless data access or employing specific connectors that match your archival solution’s storage technology, the process is designed to be straightforward and efficient.
Your Call to Action: Comprehensive Architecture Planning
Consultants are urged to develop thorough architecture plans that address both immediate and long-term needs. Advising clients on archiving unused data can free up valuable resources and optimize system performance.
By balancing resilience, time-to-value, and cost considerations, businesses can enhance their data-driven strategies and maximize the benefits of Salesforce Data Cloud and AI.
Summary
Optimizing the use of historical CRM data in Salesforce Data Cloud is not just about technology implementation – it’s about strategic data management. By understanding the nuances of data synchronization, archiving, and utilization, consultants can help businesses unlock powerful insights and drive meaningful AI initiatives.
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