Data Architecture
Data becomes decision.
We structure Data Lakes, ETL/ELT Pipelines and analytics layers. We transform scattered raw data into actionable business intelligence and executive dashboards.
When this solution is for you
Do you recognize any of these situations in your operation?
Reports don't match between areas
Each area has its own 'truth' spreadsheet
Difficulty answering simple questions ('how many active customers do we have?')
Data in multiple systems without consolidation
Decisions based on 'guesswork' due to lack of reliable data
What we deliver in practice
Clear service components, without complex technical terms
Data and source map
Complete ecosystem inventory
- Cataloging: where they are, what format
- Current quality analysis
- Gap and redundancy identification
Data architecture
Design in business terms
- Sized Data Lake/Warehouse
- Bronze/silver/gold layers
- Governance and security
Automated pipelines
Reliable data loading
- ETL/ELT for each source
- Real-time or batch updates
- Quality validations
Analytics layer
Data ready for consumption
- Executive dashboards
- Self-service BI for areas
- APIs for applications
How the project works with Codee
Clear and predictable process, with aligned expectations at each stage
Inventory
1-2 weeksWe map all data sources: where they are, what format, who owns them, what quality. We understand business questions that need to be answered.
Architecture
2-3 weeksWe design target structure: Data Lake, Data Warehouse or both. We define technologies, dimensional modeling and governance strategy. Everything explained in business terms.
Pipelines
4-8 weeksWe implement loading pipelines starting with priority sources. Data flows automatically from source to destination with quality validations.
Analytics
2-4 weeksWe create dashboards, reports and APIs. We train areas for self-service. We iterate based on feedback until information is truly useful.
Examples of scenarios and results
Real cases where we successfully applied this solution
Context
Sales data scattered across 3 regional ERPs, no consolidated view, impossible to make national inventory decisions
What was done
Unified Data Lake with pipelines from each ERP. Analytics layer with single view of sales, inventory and margin in real time. Regional and national dashboards.
Result
Inventory decisions 3x faster, unified view, -30% stockouts
Context
Manual attendance reports, took 1 week to consolidate data from multiple clinics, impossible to track indicators
What was done
Data Warehouse with daily ETL from each clinic. Automatic dashboards with quality, occupancy and financial indicators.
Result
Reports from 1 week → 5 minutes, daily visibility, guaranteed compliance
Frequently asked questions
Common questions about Data
Let's talk about Data?
We structure Data Lakes, ETL/ELT Pipelines and analytics layers. We transform scattered raw data into actionable business intelligence and executive dashboards.
Talk to an expert in DataNo commitment. First conversation is diagnosis.
Other solutions that may interest you
Explore other ways to transform your operation
Let's talk about
your technical challenge?
We don't have salespeople. You talk directly with senior engineers who understand your problem.