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Annatech_

Data Engineering

One modeled layer, every consumer

Automation and AI are only as good as the data underneath. We build the SAP-to-warehouse backbone that feeds case management, robots and language models from the same governed views.

Reference scale

A production analytics layer

curated Snowflake views in the analytics layer
18
lines of SQL modeling the SAP domain
1,548
SAP fields mapped in the largest single view
200+
consumer classes fed by one modeled layer: BPM, RPA, AI
3

Built for a global healthcare-technology enterprise: SAP ERP extraction into Snowflake, a three-layer design from source through access to analytics, consumed simultaneously by a Pega platform, a UiPath fleet and analytical tooling.

Architecture

The backbone, end to end

ONE MODELED LAYER, EVERY CONSUMER SAP ERP finance · inventory · supply chain APIs & files REST · OData · batch drops · streams Snowflake warehouse SOURCE - raw, incremental ACCESS - typed, mapped ANALYTICS - 18 curated views 1,548 SQL lines · 200+ SAP fields mapped Pega BPM case routing & decisions RPA fleet transaction inputs LLM / RAG grounded retrieval context
As built: SAP and API sources into a three-layer Snowflake design, one governed analytics layer serving case management, robots and retrieval.

Method

Source to serving

  1. 01

    Extract

    SAP as the system of record: financial, inventory and supply-chain data extracted reliably, incrementally, without destabilizing the source.

  2. 02

    Model

    A curated analytical layer - explicit field mapping, business naming, tested SQL - instead of a swamp of raw table dumps.

  3. 03

    Serve

    Pre-computed views with predictable performance, shaped for the consumers that matter: case management, robots, dashboards.

  4. 04

    Feed AI

    The same governed layer becomes retrieval context and decision input for LLM systems - AI grounded in modeled data, not screenshots of it.

Is your automation reading screens because the data layer is missing?

Describe your source systems and who needs the data. You will get a proposed layering - and a candid view on what should not be built.

[email protected] Capability statement (PDF)