Data Ingestion
The process of collecting data from source systems — ERPs, databases, APIs, file uploads, email — and loading it into a pipeline or platform where it can be processed. Ingestion is the first step in any data workflow: nothing gets analyzed, enriched, or acted on until it has been ingested.
What is Data Ingestion?
Data ingestion is the process of moving data from where it originates — an ERP, a supplier portal, an email inbox, a file system, an external API — into a system where it can be processed, analyzed, or acted on. Before any AI model can extract fields from an invoice, classify a document, or run a matching algorithm, that data needs to be collected and made available in a consistent format. Ingestion handles that collection step.
Ingestion can be batch-based (pulling a day's worth of transactions every night), stream-based (processing each document as it arrives in real time), or event-driven (triggered by a specific action, like a new order being placed). The right pattern depends on how time-sensitive the downstream process is and how the source system delivers data.
What Makes Ingestion Difficult
Data arrives in different formats — PDFs, CSVs, EDI messages, API responses, email attachments. Source systems have different authentication methods, rate limits, and availability windows. Data quality is inconsistent: missing fields, encoding errors, duplicate records, and schema changes break pipelines that were not built to handle them.
Format normalization — converting varied input formats into a consistent internal schema
Error handling — routing malformed or incomplete records to a review queue instead of silently failing
Deduplication — detecting and handling records that arrive more than once
Data Ingestion in Operations
For a manufacturer or distributor, reliable ingestion is what keeps automated workflows running without gaps. If supplier invoices arrive via three channels — email attachment, supplier portal export, EDI feed — and ingestion is not robust across all three, some invoices fall through. The AP team discovers the gap when a supplier calls about an overdue payment, not when it was first missed. Well-designed ingestion captures everything, logs what it received, and surfaces exceptions immediately.