Catalina: DevOps & DataOps on Azure Cloud

CASE STUDY · RETAIL & DISTRIBUTION

Industrialised CI/CD pipelines and automated DataOps flows into Snowflake and BigQuery.

Catalina, a pioneer of data-driven relationship marketing, called on Adservio to industrialise its pipelines as part of its Azure Cloud migration.

Catalina : Adservio case study
Client
Catalina (relationship marketing)
Expertise
DevOps & DataOps · Azure Cloud Migration · Security By Design
Tech Stack
Azure · Snowflake · BigQuery · dbt · Soda · Airflow
Engagement
8 experts · 30 months
CONTEXT

Project Context

Catalina operates a critical data-driven relationship marketing platform for its retail partners. The legacy on-premise IS could no longer absorb the growth in volumes or the release frequency the market expected.

Deployments were still done manually, with risks of production incidents and an uncompetitive time-to-market. The marketing data flows were orchestrated by ad hoc scripts, without observability or monitored quality.

The challenge: migrating to Azure, industrialising the CI/CD pipelines and the DataOps stack, embedding GDPR security by design, and freeing the Catalina teams to focus on business value.

Strategic Objectives

(01)

End-to-end CI/CD

Industrialise the application and data delivery pipelines: 230 active pipelines, automated build/test/deploy, time-to-market divided by 3 on new releases.

(02)

Automated DataOps

Automate the marketing DataOps flows (POS, CRM, web tags) into Snowflake and BigQuery, with dbt + soda orchestration and reverse-ETL activation for activation segments.

(03)

Security By Design

Embed security directly in the pipelines: blocking SAST + DAST + GDPR compliance tests, and an audit log of every deployment and every data flow.

Solutions Delivered by Adservio

Adservio deployed a Cloud + DataOps team (Cloud Architects, DevOps Engineers, Data Engineers, Security Champion) over 30 months.

(01)

Azure Cloud Migration

Complete migration of Catalina workloads to Azure with a blue-green strategy, zero downtime and a rollback plan tested on every migration batch.

(02)

CI/CD pipelines

Deployment of 230 GitHub Actions / Azure DevOps pipelines with blocking quality gates (coverage >80%, SAST, DAST), reusable templates and auto-rollback on failure.

(03)

DataOps stack

Complete DataOps architecture: ingestion via Airflow, dbt transformation, soda data tests, reverse-ETL activation into the marketing systems: the whole chain steered and observed.

(04)

Snowflake + BigQuery

Dual-cloud setup of Snowflake (Azure) + BigQuery (GCP) for analytical workloads, with a data mesh per domain and granular RBAC by default.

(05)

Native GDPR security

GDPR by design integration: pseudonymisation, automated DPIA, retention policies as code, an immutable audit log of every access to customer data.

230 pipelines. Snowflake and BigQuery.
Security By Design.

Industrialised CI/CD, automated marketing DataOps flows, data quality continuously monitored: industrialisation as a competitiveness lever.

Results

230
Industrialised pipelines

CI/CD pipelines covering the full SDLC, automated build/test/deploy.

÷3
Time-to-market

Release time-to-market divided by 3.

< 15 min
Data freshness

Automated marketing flows into Snowflake and BigQuery.

0
Critical vulnerability

Zero critical vulnerabilities in production, security by design.

−18%
Cloud bill

Continuous FinOps optimisation of Snowflake and BigQuery costs.

0
Migration incident

Azure migration executed with no blocking incident, blue-green strategy.

Impact

End-to-end CI/CD

230 industrialised pipelines covering the full SDLC, release time-to-market divided by 3, multiple deployments per day without manual intervention.

Automated DataOps

Fully automated marketing flows into Snowflake and BigQuery, data freshness under 15 min, data quality continuously monitored via soda checks.

Security By Design

Security natively embedded in every pipeline: 0 critical vulnerabilities in production, GDPR by default, internal audits passed without reservation.

Incident-free migration

Complete Azure Cloud migration carried out without a blocking incident or interruption to the marketing service, with a proven blue-green strategy.

Controlled costs

Continuous FinOps optimisation of Snowflake and BigQuery costs (rightsizing, autoscaling, query optimisation), −18% on the annual cloud bill.

Team autonomy

The Catalina teams now run the entire DataOps stack autonomously, with reusable templates and living documentation.

TALK TO AN EXPERT

Industrialise your DevOps and DataOps pipelines

Cloud migration, CI/CD, Snowflake/BigQuery, security by design: let us discuss your transformation. An Adservio expert gets back to you within 24h.

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