Data lake & BI consulting for numbers you can trust. And dashboards your team actually uses.
We bring your ERP, CRM, spreadsheets and apps into a data lake or warehouse in your cloud, with monitored pipelines, quality tests and dashboards in Power BI, Looker or Tableau. Every team decides from the same number.
When data slows down decisions
The situations that most often bring companies to us.
Reports built in spreadsheets
Someone spends days merging ERP, CRM and spreadsheet exports to close the month, and every version shows a different number.
Every team has its own number
Sales, finance and operations show up with different metrics, and the meeting turns into a debate about which one is right.
Slow or breaking Power BI
Dashboards take forever to load, break when a source changes, and nobody knows where each metric comes from.
Loads fail and nobody notices
Scripts and scheduled jobs with no monitoring. The error only shows up when leadership sees the wrong number.
Personal data out of control
Customer IDs, emails and personal data scattered across databases, with no access control or clear privacy rules.
You want AI, but the data isn't ready
The AI project is stuck because data is scattered, low quality and has no clear owner.
From raw sources to trusted dashboards
We build the whole platform or just the missing piece, using the tools you already have.
Data lake, warehouse or lakehouse
Architecture in your cloud on BigQuery, Redshift, Snowflake or Databricks, organized into raw, clean and analytics layers, sized to your volume and budget.
ETL/ELT pipelines
Ingestion from ERP, CRM, databases, APIs and spreadsheets with dbt, Airflow or Spark, batch or near real time, with reprocessing and history.
Modeling and semantic layer
Dimensional modeling, standardized metrics and a data catalog: every metric has a documented definition, owner and origin.
BI dashboards
Power BI, Looker or Tableau dashboards designed around each team's decisions, with solid performance, role-based access and business validation.
Data quality and monitoring
Data tests on every load, alerts for failures and delays, and lineage to see what's affected when a source changes.
Governance, privacy, AI-ready
Access control, masking and anonymization of personal data, plus an organized foundation ready for AI projects.
From assessment to trusted data
Short releases: priority sources and dashboards come first, the rest follow in cycles.
Sources and decisions
We map sources, volumes, current reports and the decisions your data needs to support.
Architecture and plan
Platform, data model and delivery sequence, sent within 48h of the first call.
Pipelines and layers
Pipelines for priority sources and raw, clean and analytics layers, with quality tests from day one.
Metrics and semantic layer
Metrics defined with each team, dimensional modeling and a catalog showing where every number comes from.
Dashboards and validation
First dashboards published, with every metric checked by the business teams before it becomes official.
Operations and new sources
Load and cost monitoring, documentation and team training. New sources and dashboards are added in cycles.
Know whether the number on the dashboard is right
Trusted data isn't just a nice dashboard. It's knowing the load ran, the tests passed and where every metric came from. All of it stays visible, in your cloud and on the tools that make sense for you.
- Status of every pipeline, with failure or delay alerts before people start using the data
- Quality tests on every load: nulls, duplicates, keys and business rules
- Lineage from source to dashboard, so you see the impact of any change
- Dashboard usage tracked, so you improve what your team actually opens
- Platform cost per load and per team, right next to performance
Tell us about your data in 1 minute
Pick the options, leave your contact and the brief goes by email straight to a specialist. More context means a sharper first conversation.