What leaders see
Promising pilots that do not change daily work.
Teams test tools, get useful output, and still copy results into spreadsheets, tickets, emails, or ERP screens by hand.
Services
Business Decisions · Data
Data Analytics & Business Intelligence
Turn scattered data into decisions people can trust. The business already has information about customers, orders, inventory, finance, fulfillment, and service. We connect and govern it so people can see what is happening, understand why, and act without rebuilding the answer by hand.
01
The Problem
Leaders cannot manage what teams cannot see clearly.
The problem is rarely that the model cannot generate an answer. The real problem is that the data, permissions, exception rules, and action boundaries are not governed well enough for AI to affect production work.
What is actually happening
The automation cannot reach the operating record.
Source data, permissions, business rules, exception handling, and audit trails are not clean enough for the system to take action.
What gets worse
Automation scales uncertainty.
Bad inputs move faster, decisions become harder to trace, and teams lose confidence before AI becomes operationally useful.
02
What Changes
What Data Analytics & Business Intelligence includes.
The business already has information about customers, orders, inventory, finance, fulfillment, and service. We connect and govern it so people can see what is happening, understand why, and act without rebuilding the answer by hand.
01
Data Warehouse & Integration
Centralize data from ERP, WMS, CRM, finance, commerce, service, and other business systems into a cloud data warehouse. Automated pipelines keep data fresh and consistent.
Related service02
Executive Dashboards
Real-time dashboards for revenue, margin, inventory turns, on-time delivery, and production throughput. Accessible on any device, updated automatically.
Related service03
Operations Analytics
Connect order, inventory, fulfillment, service, finance, exception, and customer-workflow data so leaders can identify delays, leakage, and capacity constraints.
Related service04
Demand Forecasting
Machine learning models trained on your historical data to forecast demand by product, customer, and channel. Reduce stockouts and overstock simultaneously.
Related service05
Inventory Optimization
Analytics-driven safety stock calculations, reorder points, and ABC classification. Reduce carrying costs while maintaining service levels.
Related service06
Self-Service Reporting
Empower your team to build their own reports and explore data without IT involvement. Governed data models ensure consistency across all reports.
Related service03
How It Fits Your Operations
How Data Analytics & Business Intelligence fits your operation.
Intelligence layerWhich decisions can be automated, which need review, and which should stay human-owned.
Governance dependencyThe agent needs governed inputs, clear action boundaries, and audit logging before it can touch production workflows.
Data the model must trust
ERP history
exception queues
pricing rules
quality records
fulfillment events
What Launchpad defines before engineering begins
- What the business needs to change and why.
- Which systems, records, risks, and readiness gaps shape the work.
- What should be built, how it fits the architecture, and in what order.
Related Foundations
What to evaluate next.
Follow the dependencies behind this service instead of treating it as an isolated project.
01
Data engineering and integration
Build the governed records, pipelines, and definitions AI needs to produce reliable results.
Explore next step02
Cloud architecture and operations
Prepare secure infrastructure, access controls, monitoring, and recovery for production AI workloads.
Explore next step03
AI on Your Data readiness
Evaluate the use case, owned data, permissions, review model, and workflow outcome before implementation.
Explore next step04
Launchpad readiness and Roadmap
Assess readiness, dependencies, risk, architecture, and implementation order before engineering begins.
Explore next stepLaunchpad Before Engineering
Decide what to build and in what order.
Launchpad assesses the business and turns discovery into priorities, risks, readiness, architecture, and an implementation Roadmap. Metrotechs then engineers and supports the approved solution.
Metrotechs designs, builds, integrates, and supports the approved solution.
Launchpad keeps priorities, risks, owners, decisions, and delivery governance connected.
04
Delivery sequence
How Metrotechs delivers Data Analytics & Business Intelligence.
The business already has information about customers, orders, inventory, finance, fulfillment, and service. We connect and govern it so people can see what is happening,.
01
Data Audit
Inventory all data sources, assess quality, and map relationships. Identify gaps and define the metrics that matter most to your operation.
02
Architecture & ETL
Design the data warehouse schema and build automated data pipelines. Cloud-based with incremental refresh for near-real-time analytics.
03
Dashboard Development
Build executive and operational dashboards in Power BI, Tableau, or Looker. Iterative design with stakeholder feedback at every round.
04
Advanced Analytics
Deploy forecasting models, anomaly detection, and optimization algorithms. Validate predictions against historical data before production use.
05
Training & Handoff
Train your team on dashboards, self-service reporting, and data interpretation. Full documentation and ongoing support.
05
FAQ
Questions that usually decide the scope.
Straight answers to what operators ask before committing budget to this work.
Power BI, Tableau, Looker, and custom-built dashboards. We recommend based on your existing Microsoft/Google ecosystem, team size, and budget. Power BI is the most common choice for operators already on Microsoft.