Key takeaways
- ETL and ELT move data from operational systems into a warehouse for reporting and analytics.
- iPaaS connects applications to each other in near real time to automate business processes.
- Reverse ETL pushes modeled data from the warehouse back into tools such as CRM and marketing platforms.
- Many companies use more than one; the key is matching the approach to the job.
“We need to integrate our data” can mean very different things. A finance team wanting a consolidated dashboard needs something different from a sales team wanting orders to appear in the CRM instantly. Understanding the main approaches helps you choose the right tools and avoid overbuilding.
ETL and ELT
ETL stands for extract, transform, load: data is extracted from source systems, transformed into a consistent model and loaded into a data warehouse. ELT loads raw data first and transforms it inside the warehouse, which modern cloud warehouses handle well. Both are designed for analytics: combining CRM, ERP, finance and marketing data for reporting.
iPaaS
Integration platform as a service tools connect applications directly: when an order is created in one system, create it in another; when a deal closes, notify finance. They offer connectors, mapping, workflow logic and monitoring, and work in near real time. iPaaS is about operational processes, not analytics.
Reverse ETL
Reverse ETL takes data that has been modeled in the warehouse, such as customer lifetime value, product usage or health scores, and syncs it back into operational tools like Salesforce or marketing platforms, so teams can act on it.
Comparison
| ETL or ELT | iPaaS | Reverse ETL | |
|---|---|---|---|
| Purpose | Analytics and reporting | Process automation between apps | Activate warehouse data in apps |
| Direction | Apps to warehouse | App to app | Warehouse to apps |
| Timing | Scheduled batches, often hourly or daily | Near real time | Scheduled or frequent syncs |
| Typical owner | Data team | IT or operations | Data and operations together |
How to choose
- Need consolidated reporting across systems? ETL or ELT into a warehouse.
- Need systems to update each other as work happens? iPaaS or custom API integration.
- Need sales or marketing to act on analytics? Reverse ETL.
- Only two systems and simple logic? A direct integration may be enough.
Common mistakes
- Using an analytics pipeline for operational processes that need real-time updates.
- Building point-to-point integrations for everything until nobody can maintain them.
- Copying all data everywhere instead of defining systems of record.
- Ignoring monitoring, so failed syncs go unnoticed.
Our system integration and reporting teams help choose and build the right data flows.
A worked example: one company, three approaches
A subscription business uses an iPaaS to create customers in its billing system when deals close in Salesforce, and to sync invoices back. Every night, an ELT pipeline loads Salesforce, billing and product usage data into a cloud warehouse, where the data team models churn risk. A reverse ETL sync pushes the churn-risk score to each Salesforce account, so account managers know whom to call. Each tool does the job it is designed for.
Questions to ask before choosing tools
- Is the goal reporting, process automation, or acting on analytics?
- How fresh must the data be?
- Which systems own which data?
- Who will monitor and maintain the pipelines?
Frequently asked questions
Is Salesforce a good place to centralize all data?
Salesforce is excellent for customer-facing data and processes. For combined analytics across many systems, a data warehouse is usually better, with key insights synced back to Salesforce.
Can one tool do ETL and iPaaS?
Some platforms cover both, but they are designed for different jobs. Choose based on your main need.
Do small businesses need a data warehouse?
Not always. If reporting needs are met within the CRM and accounting system, a warehouse may be unnecessary until data sources multiply.
