Business Central records operational activity; it was not designed to produce cross-functional analysis. Moving from raw ERP data to questions such as yield variance by SKU, ingredient cost impact, or gross margin shift has typically required manual extraction or custom work in the data warehouse.

inectaETL handles that extraction layer. It pulls data from Business Central via a curated API collection, transforms it for analytical use, and loads it into the customer’s platform. The pipeline ships pre-configured for food-specific data structures such as catch weights, lot traceability, yield calculations, and posted production journals and runs on a continuous orchestration server with flexible scheduling.

inectaETL was not part of a product roadmap initiative. inecta’s own CFO and COO built it because they faced the same problem their clients face: operational data locked in a transactional system, unavailable for management reporting. inecta now runs its own management reporting—revenue, utilization, project profitability, and resource cost—directly off the ETL pipeline. The product was proven on inecta’s own data before it was offered to customers.

“We developed inectaETL to solve a challenge we faced ourselves. Our leadership team encountered the same obstacle as our customers: operational data in Business Central, with no practical way to generate management reports. After creating the pipeline and using it for our own reporting, only then did we introduce it to the market," said Ruth Lestina, chief operating officer of inecta. "inectaETL serves as a bridge between a customer’s food ERP data and their existing analytics tools, managing the food-specific complexities. This simplifies their process: no custom data warehouse, no data engineering team, and no need to switch BI platforms. We know it works because we use it ourselves."

Source: inecta