Your Data is a Mess. And Every Report You Pull is Wrong.
The same customer has 3 different records with 3 different spellings. Reports from different systems never match. Nobody trusts the numbers because nobody knows where they came from.
Bad Data is Quietly Expensive
Every decision you make is only as good as the data it's based on. What is bad data costing you?
What You're Dealing With Now
- Split customer records — same person exists as "J Smith", "John Smith", and "john.smith@company" and you have no idea they're the same
- Conflicting reports — sales says one number, operations says another, accounting says something else
- AI tools don't work — you want to use AI but your data isn't structured enough for it to be useful
- Nobody trusts the numbers — every report starts with an argument about which data source is right
What Good Data Architecture Delivers
- Golden records — every customer, product, and entity has one definitive record that all systems reference
- Reconciled reporting — all systems agree because they all pull from the same source of truth
- AI-ready structures — your data is organized and clean enough to power machine learning and analytics
- Decisions you can trust — when the data says X, you can act on X without second-guessing
Data Architecture Services That Fix the Root Problem
Not quick patches. We design and build data structures that scale with your business and keep your data clean forever.
Data Architecture Design
A blueprint for how your data should be structured. We map every entity, relationship, and data flow so your systems work together instead of against each other.
- Entity relationship mapping
- Schema design and normalization
- Scalability planning
Typical result: A data model that supports 10x growth without restructuring
Master Data Management
Single source of truth for customers, products, suppliers, and every critical entity. No more duplicates, no more conflicts, no more guessing which record is right.
- Duplicate detection and merging
- Golden record creation
- Cross-system synchronization
Typical result: 30-50% reduction in duplicate records immediately
ETL Pipeline Development
Move data reliably between systems. Extract, transform, and load pipelines that run automatically, handle errors gracefully, and keep everything in sync.
- Automated data synchronization
- Error handling and retry logic
- Transformation and validation rules
Typical result: 99.9% data sync reliability with automated monitoring
Data Quality & Cleansing
Fix what's broken. We identify duplicates, standardize formats, fill gaps, and establish rules that keep bad data from entering your systems in the first place.
- Profile and assess current quality
- Standardization and normalization
- Ongoing quality monitoring
Typical result: Data accuracy improvement from 70% to 95%+
AI-Ready Data Structures
Prepare your data for machine learning and analytics. Proper feature engineering, clean training sets, and structures that make AI tools actually useful.
- Feature engineering support
- Training data preparation
- Analytics-friendly schemas
Typical result: AI model accuracy improved by 2-3x through better data
Data Governance
Rules and processes that keep data clean over time. Access controls, change tracking, validation rules, and ownership so your data stays reliable forever.
- Data ownership and stewardship
- Change audit trails
- Validation and quality rules
Typical result: Data quality maintained at 95%+ without manual intervention
How Phoenix Businesses Fixed Their Data
Real examples from industries we've helped across the Valley.
Multi-Location Retail
Chandler (4 locations)
Same customer shopping at different stores was creating 3-4 duplicate records. Inventory counts never matched between POS and warehouse. Customer service couldn't see purchase history across locations.
Result: Unified customer view across all stores, 15% increase in repeat business
E-Commerce + Wholesale
Gilbert
Shopify online store, wholesale orders, and Amazon marketplace all had different product catalogs. Same SKU had different names and prices everywhere. Inventory reconciliation was a weekly nightmare.
Result: Single product catalog feeds all channels, 40 hours saved monthly
Manufacturing
Tempe
Production data lived in one system, quality metrics in another, supply chain in a third. Couldn't correlate defects with suppliers or production runs because data wasn't connected.
Result: Trace every defect to source, 25% reduction in quality issues
Healthcare Network
Phoenix (3 locations)
Patient records scattered across locations with no unified view. Same patient had different medical histories at each location. Billing was constant mess of duplicate claims.
Result: Complete patient history in one place, 60% fewer billing errors
The Cost of Bad Data Adds Up Fast
Bad data isn't just annoying—it's expensive. Here's what fixing it actually saves you.
20%
Average Revenue Lost to Bad Data
12 hrs
Per Week Spent Reconciling Data
3-6 mo
Typical Payback Period
Real Math from a Gilbert Client
Annual Cost of Bad Data (Before):
- • 15 hours/week reconciling reports @ $65/hr
- • = $50,700/year in wasted time
- • ~$35,000 in lost orders from duplicate records
- • $12,000 in marketing sent to bad contacts
- • = ~$98,000/year total cost
After Data Architecture Fix:
- • Reconciliation time: 1 hour/week
- • Duplicate records eliminated
- • Marketing data cleaned and validated
- • Project cost: $7,500 one-time
One-time investment: $7,500. Saves ~$97,000/year. 13x first-year ROI.
How We Fix Your Data
From mess to mastery in 3-6 weeks
Data Audit
We assess every system, catalog every data source, and identify every duplication, inconsistency, and gap.
Architecture Design
We design a data model that solves your specific problems and create a roadmap for getting there.
Clean & Build
We clean existing data, build the master records, create ETL pipelines, and establish governance rules.
Validate & Handoff
We verify accuracy, train your team on maintaining data quality, and provide tools to keep it clean.
Which Data Problem is Costing You the Most?
Book a free data architecture audit. We'll identify your specific data quality issues and show you exactly what it would take to fix them.
Free data audit | $3,000-$9,500 | 3-6 week delivery | Data you can trust