Data & Analytics
Data & Dashboarding foundation
Drive decisions with reliable data
- GA4
- Piano
- Mixpanel
- and 3 other tools
Data & Analytics
Data Engineering
Build a solid, sovereign data foundation
Build a modern, sovereign and automated cloud data infrastructure: streamline your data flows and remove your legacy dependencies.
The need
What you tell us
« I want to industrialize my data: reliable pipelines, a well-managed cloud platform and automated flows, without depending on fragile legacy systems or a historical provider. »
- « I want to migrate to the cloud (GCP/BigQuery) »
- « I want reliable pipelines (dbt) »
- « I want to move away from my legacy system »
- « I want to industrialize my data »
Our response
- Audit of the existing setup and target architecture
- Cloud migration and dbt pipelines
- Industrialization and documentation
The principle
A solid and sovereign data foundation
01Sources
- Web analytics
- CRM
- Media networks
- E-commerce
Your current tools
02Ingestion
- API connectors
- Scheduled exports
- Orchestration
Operated by the provider
03Warehouse
ClickHouse
- Raw data
- Modeled tables
Operated by the provider
04Transformation
dbt
- Versioned SQL models
- Tests and documentation
Operated by your teams
05Reporting
- Cross-referenced dashboards
- Shared KPIs
Operated by the provider
Tool examples: the stack is chosen based on your context, constraints and licenses.
Operating mode
Almost no operations, you keep the dbt models
Your sources feed an open source warehouse, modeled with dbt, for dashboards that cross-reference your data. The foundation remains the same regardless of the operating mode chosen.
- Brique opérée par vos équipes
- Brique opérée par le fournisseur
- Socle commun : entrepôt et modèles dbt
Method
Our method in 5 steps
Our stance
Sovereignty & robustness
A controlled and documented infrastructure, giving you control over your data and costs.
- Cloud
- dbt
- CI/CD
Step 01 : Audit
Conducting a complete assessment of your existing legacy, data volumes and technical constraints.
- Legacy system assessment
- Technical constraints and volume
- Mapping of existing flows
- Technical debt and identified risks
Step 02 : Architecture
Definition of the validated target schema and selection of your sovereign stack (Google Cloud Platform, dbt).
- Validated target schema
- Choice of stack (Google Cloud Platform, dbt)
- Target data model
- Security and access defined
Step 03 : Migration
Secure migration of historical data and modeling of your dbt pipelines.
- Historical data recovery
- Modeled dbt pipelines
- Like-for-like results
- Seamless switchover
Step 04 : Industrialization
Setup of automated testing, continuous deployment (CI/CD) and orchestration of your data flows.
- Tests and CI/CD in place
- Flow orchestration
- Error handling and recovery
- Cost optimization
Step 05 : Handover
Comprehensive documentation, data lineage and training for your teams to guarantee full autonomy.
- Documentation and lineage
- Team training
- Runbook
- Gradual handover
Deliverables
What you get
Target architecture
Documented and validated.
dbt pipelines
Tested, versioned models.
Migrated platform
Operational on the cloud.
Documentation & lineage
Handover to the teams.
Who is it for?
Who is this offer for?
Tools used
- GCP
- BigQuery
- dbt
- Airflow
- ClickHouse
- Snowflake
- Company with fragile legacy data or cloud migration
- Context: departure of a long-standing provider, sovereignty
- Sponsor: Head of Data, CIO, Data Engineer lead
To go further
Articles by our experts related to this offer.
Opinion: Predictive analytics, reality or witchcraft?
Last month we talked about personalization. We got great feedback and decided to focus today on predictive analy
Why and how to improve your 1st party collection strategy?
In this webinar, we explore the crucial role of 1st party data in an approach to improving the experience
Bayesian vs Frequentist: which method for your A/B tests?
Finally understand the difference between Bayesian and frequentist statistics to optimize your A/B tests.
Qualitative and quantitative analysis, how to choose?
Quanti or quali? Leverage both types of analysis to improve UX and boost your CRO strategy!
DMA (Digital Markets Act): everything you need to know!
After the rollout of GDPR in 2018, it's time to prepare for the arrival of the Digital Markets Act in spring 2024
To go further
Often associated with
Data & Analytics
Sanity Check Tracking
Make your tracking reliable before deciding
- GA4
- GTM
- Piano
- and 2 other tools
Data & Analytics
Privacy & Consent
Stay compliant and keep usable data
- Didomi
- OneTrust
- Axeptio
- and 2 other tools
Other Data & Analytics offers
View the Data & Analytics pillar