Make (formerly Integromat) is a visual automation platform specialized in complex data processing workflows. Its visual scenario builder maps out data flow between apps with conditional routing, iteration over arrays, error handling, and data transformation that surpasses Zapier...
ZTABS builds data processing automation with Make — delivering production-grade solutions backed by 500+ projects and 10+ years of experience. Make (formerly Integromat) is a visual automation platform specialized in complex data processing workflows. Its visual scenario builder maps out data flow between apps with conditional routing, iteration over arrays, error handling, and data transformation that surpasses Zapier for complex data operations. Get a free consultation →
500+
Projects Delivered
4.9/5
Client Rating
10+
Years Experience
Make is a proven choice for data processing automation. Our team has delivered hundreds of data processing automation projects with Make, and the results speak for themselves.
Make (formerly Integromat) is a visual automation platform specialized in complex data processing workflows. Its visual scenario builder maps out data flow between apps with conditional routing, iteration over arrays, error handling, and data transformation that surpasses Zapier for complex data operations. Make handles scenarios where data needs parsing, splitting, merging, and restructuring between systems. For businesses that need to process CSV files, sync databases, transform API data, and manage complex multi-step data workflows, Make provides the visual power that code-based solutions offer with no-code accessibility.
See exactly how data transforms between steps. The visual canvas shows connections, data flow, and conditional branches — easier to debug than linear automation tools.
Iterate over arrays, merge data from multiple sources, parse CSV/JSON/XML, and transform data structures. Handle complex data processing without code.
Each module has error handling options — retry, ignore, break, or route to an alternative path. Build resilient automations that handle failures gracefully.
Make pricing is based on operations, not number of scenarios. Process high volumes at lower cost than Zapier for data-heavy workflows.
Building data processing automation with Make?
Our team has delivered hundreds of Make projects. Talk to a senior engineer today.
Schedule a CallUse Make data stores to track processed records and prevent duplicates. Without deduplication, re-running scenarios after errors can create duplicate entries in your target systems.
Make has become the go-to choice for data processing automation because it balances developer productivity with production performance. The ecosystem maturity means fewer custom solutions and faster time-to-market.
| Layer | Tool |
|---|---|
| Platform | Make (Integromat) |
| Data | Built-in data stores |
| Triggers | Webhooks / schedules / app events |
| Processing | Iterators / aggregators / routers |
| Custom | HTTP modules / custom functions |
| Monitoring | Execution history and logging |
A Make data processing scenario starts with a trigger — file upload, webhook, schedule, or app event. The visual canvas shows each processing step as a module. For CSV data sync: a schedule trigger fetches a CSV file from SFTP, the CSV parser extracts rows, an iterator processes each row individually, conditional routers send new records to the CRM and updated records to the ERP, and an aggregator compiles results for a summary email.
Error handling modules catch API failures, retry with backoff, and route persistent errors to a Slack notification. Make's built-in data stores act as lightweight databases for tracking processed records, deduplication, and maintaining state between scenario runs. The visual execution history shows exactly which modules processed which data, making debugging straightforward.
Our senior Make engineers have delivered 500+ projects. Get a free consultation with a technical architect.