Capabilities
Six specialties for getting data in order.
Scattered forms, personal Excel files, master data full of inconsistencies. As a team dedicated to data readiness, we cover six areas — from inventory to pipeline building. Combine only what you need and roll out in phases.
Data Inventory & Assessment
Before
We catalog internal and external data sources and evaluate their quality, freshness, and usability.
Structuring Forms & Spreadsheets
Before
Paper delivery slip
+ handwritten note: "batch next time"
We convert paper forms and local Excel files into structured data using OCR and parsers.
Deduplication & Entity Resolution
Before
We consolidate customer, product, and people master data, resolving naming inconsistencies and duplicates.
Missing & Anomalous Value Detection
Before
We combine rules, statistics, and machine learning to detect anomalies — and design the imputation logic to fix them.
Master Data Integration
Before
We unify master data scattered across systems so records can be referenced with a single shared ID.
ETL/ELT Pipelines
Before
We build reproducible pipelines that keep clean data flowing, day after day.
How we deliver
A phased rollout, from Phase 0 to 5.
Rather than fixing everything at once, we work in the order data gets clean — starting with an inventory. Every phase leaves results your team can use, building toward operations that keep data in order continuously.
Phase 0
Data Inventory & Assessment
We map out what data exists where — across teams and systems — and how clean (or messy) it really is. Every engagement starts with this clear-eyed assessment.
Phase 1
Structuring Forms & Spreadsheets
Paper forms, local Excel files, email attachments. We convert unstructured information into formats a database can work with.
Phase 2
Deduplication & Entity Resolution
We consolidate master records for customers, products, and people so that "ACME Corp." and "ACME Corporation" are treated as one, eliminating naming inconsistencies.
Phase 3
Data Quality Rule Design
Required fields, data types, value ranges, imputation of missing values — we design quality rules that fit your operations and turn them into automated checks.
Phase 4
Data Platform & Pipelines
We design ETL/ELT pipelines and a data warehouse that keep clean data flowing continuously, with reproducible, dependable operations.
Phase 5
Connecting to Value
We connect your clean data to BI dashboards, automated reports, and business systems — and, where needed, bridge into AI use cases such as predictive models and RAG/LLM applications.
Start by understanding where your data stands.
In most cases we recommend starting from Phase 0, Data Inventory & Assessment. "We have the data, but don't know where to start" is a perfectly good place to begin — get in touch.