Technologies — Agrolytica

SQL Server

Microsoft’s relational database management system, the historical reference for enterprise decision-support environments.

When we recommend it: For companies with existing on-premise infrastructure, controlled volumes (up to several TB), and an IT team already trained on the Microsoft ecosystem.
Typical use case: A data warehouse consolidating production and sales data for a single industrial site or a handful of sites.

Power BI

Microsoft’s Business Intelligence tool, for building interactive dashboards and self-service analytics.

When we recommend it: When you’re already on Microsoft 365, business teams need to build some reports themselves, and license costs need to stay under control.
Typical use case: An OTIF/Fill Rate dashboard checked daily by supply chain teams, with different views per role.

IBM Cognos

An enterprise BI platform, historically strong on centralized governance and large user bases.

When we recommend it: For large organizations with strict governance requirements, a dedicated central BI team, and an existing Cognos footprint to evolve rather than replace.
Typical use case: Consolidated multi-site reporting distributed to several hundred users with fine-grained access control.

Oracle Essbase

A multidimensional OLAP engine, a historical pillar of financial performance management (EPM/CPM).

When we recommend it: When your budget and forecast processes are already structured around multidimensional cubes, or finance needs fast what-if analysis on large volumes.
Typical use case: An annual budget cycle with scenario simulations by production site.

Databricks

A data & AI platform built on Apache Spark, designed for large volumes and real-time workloads.

When we recommend it: For IoT sensor data, real-time traceability, or when your volumes outgrow what a classic SQL architecture can efficiently handle.
Typical use case: Continuous ingestion of production sensor data for predictive maintenance.