Business outcome
Use this capability when the framework shows that people cannot trust the records, measures, or exceptions needed to make decisions across demand, supply, production, inventory, fulfillment, delivery, or service.
Services
Data & Analytics · Data Analytics · Data Warehouse
Data Warehouse & Integration
One warehouse for all your data, not one spreadsheet per department.
Manufacturing records are often divided across ERP, MES, WMS, QMS, CRM, portals, files, and spreadsheets. We build governed pipelines and reconciled models so operational analytics use defined ownership and consistent measures instead of manual departmental extracts.
A strong fit when
- Monthly reports require manual data exports from ERP, WMS, and CRM -- then hours of reconciliation in Excel
- Finance, operations, and sales each have their own version of "revenue" and "inventory" because they pull from different sources
- No historical data in a queryable format -- trend analysis means digging through archived spreadsheets
- Data freshness measured in days or weeks because ETL processes are manual or broken
Why this service exists
Connect the technology decision to the work the manufacturing business must control.
System responsibility
Data engineering turns records from ERP and connected systems into governed information for shared visibility, reporting, reconciliation, automation, and accountable action.
Ownership and control
The manufacturer must own the definitions, source authority, access, lineage, quality rules, reconciliations, and decision context behind every important measure.
01
The Problem
Manufacturing reports disagree because records, ownership, timing, and definitions are fragmented.
Analytics problems begin when a dashboard is built before records, definitions, timing, lineage, and accountability have been reconciled across the operation.
What leaders see
Reports disagree about current conditions.
Teams debate demand, workload, capacity, inventory, service, delivery, and margin instead of acting on them.
What is actually happening
Measures inherit unresolved record conflicts.
Sources, identifiers, definitions, refresh timing, adjustments, and ownership differ across systems and teams.
What gets worse
Faster reporting accelerates the wrong answer.
More dashboards spread inconsistent measures and make exception ownership harder to establish.
02
What changes
Make the operating responsibility visible and governable.
Manufacturing records are often divided across ERP, MES, WMS, QMS, CRM, portals, files, and spreadsheets. We build governed pipelines and reconciled models so operational analytics use.
01
Operating outcome
One warehouse for all your data, not one spreadsheet per department.
02
Operating records to reconcile
demand and orders, products, services, and inventory, work and capacity
03
Decision and exception path
Which decision the view supports, which records establish it, and how disagreement or missing data becomes visible.
04
Ownership and continuity
Measures need defined ownership, timing, lineage, reconciliation, and access before dashboards can become a basis for operating decisions.
03
Architecture
Build the service around the business record and decision.
Which decision the view supports, which records establish it, and how disagreement or missing data becomes visible.
01Source record
02Governed connection
03Validation
04Business system
05Accountable owner
Operating records to reconcile
demand and ordersproducts, services, and inventorywork and capacityquality and customer servicedelivery and financial results
04
Engineering scope
What Metrotechs engineers for Data Warehouse & Integration.
The exact scope follows the approved business objective, source records, dependencies, controls, and delivery sequence.
01
Cloud Data Warehouse
Deploy Snowflake, BigQuery, or Azure Synapse as your central analytics warehouse. Schema designed for complex operating data models -- orders, inventory, production, quality, and financials.
02
ERP Data Integration
Monitored extraction from current and legacy ERP systems using an integration pattern suited to the source. Transaction, master, and configuration data move on an agreed cadence with validation and recovery controls.
03
WMS & MES Integration
Warehouse transactions, production completions, quality records, and shop-floor data integrated alongside ERP data. The warehouse sees the full operational picture.
04
Automated ETL Pipelines
Scheduled or event-driven pipelines extract, transform, and load data from source systems with explicit quality checks, deduplication, standardization, monitoring, and exception handling.
05
Data Quality Layer
Validation rules, anomaly detection, and data quality scoring applied during ingestion. Bad data is flagged and quarantined -- not loaded into the warehouse to corrupt downstream reports.
06
Semantic Layer & Data Models
Business-friendly models define measures such as revenue, inventory, and on-time delivery with accountable owners. Approved dashboards and reports use those governed definitions and expose any intentional variation.
05
Delivery sequence
From operating reality to a solution the business can own.
Source System Inventory
Catalog the data sources in scope, document volumes, update frequencies, ownership, and access methods, and map the flows that need to converge in the warehouse.
Schema & Model Design
Design the warehouse schema and semantic models based on your analytics requirements. Define dimensions, facts, and business metric calculations with stakeholder sign-off.
Pipeline Development
Build ETL/ELT pipelines for each source system. Implement data quality checks, transformation logic, and incremental refresh strategies.
Validation & Go-Live
Validate warehouse data against source systems. Reconcile counts, totals, and key metrics. Go live when data accuracy meets defined thresholds.
Monitoring & Maintenance
Deploy pipeline monitoring, data freshness alerts, and quality dashboards. Ongoing maintenance as source systems change or new data sources are added.
Related services and systems
Continue through the connected operating environment.
Use these connected services and references to understand the records, workflows, and systems surrounding this work.
Systems explained
ERPUnderstand the operating records, workflows, and system-of-record boundaries an ERP should own.CRMUnderstand how customer, account, opportunity, activity, and relationship context should connect to the operating flow.WMSUnderstand how warehouse execution owns receiving, movement, picking, packing, and inventory control.
06
FAQ
Questions to answer before implementation begins.
Clear answers for manufacturing leaders evaluating the work, operating responsibility, and delivery path.
We choose the platform from your cloud environment, source systems, analytical workloads, security obligations, existing skills, cost model, and reporting tools. BigQuery, Snowflake, and other managed warehouses are options, not automatic defaults.