Figures that don’t match
Every department has its own spreadsheet, and none of them agree.
EXPERTISE · DATA & PERFORMANCE
Reliable data.
Informed decisions.
Data engineering, dashboards, automated reports and predictive models: data that drives management decisions.
WHY IT’S CRITICAL
Every transaction, every connection generates data. Today, it lies dormant. Tomorrow, it steers.
We build the data pipelines that turn scattered files and databases into reliable indicators: collection, quality, warehouse, dashboards, automated reports. Then the models that anticipate: scoring, prediction, segmentation.
That is what OMER does for Orange’s Mobile Money and Airtime distribution in Côte d’Ivoire and Burkina Faso.
THE CHALLENGES
What we
often hear.
Decisions at D+7
Reports arrive when it’s too late to act.
Untapped data
Logs, files and business databases that are never used.
WHAT WE DO
What we
take on.
Services that combine to fit your context, from scoping to operations.
Data engineering
Collection, ETL, data warehouse and data lake.
- Spark, Airflow, dbt
- ODS, warehouse, data marts
Dashboards and BI
Management KPIs and automated reports.
- Power BI, Superset, Kibana
- Hourly email reports
Scoring and prediction
Machine learning models to anticipate.
- Stock-outs, inactivity
- Segmentation
Quality and reconciliation
Quality rules, database reconciliation, revenue assurance.
- Automated controls
- Discrepancies detected
Regulatory reporting
Automated reports for supervisory authorities.
- BCEAO, Banking Commission
- Traceability
Geolocation
Spatial analysis of activity and the field.
- Point-of-sale mapping
- Geographic data
OUR APPROACH
How we
work.
Map the sources
Where the data is, who produces it, and at what quality.
Source mapMake reliable and consolidate
Quality rules, warehouse, history.
Data foundationDeliver insight
Dashboards and reports for every use.
Shared KPIsAnticipate
Predictive models, evaluated and monitored.
Models in productionWHAT YOU GET
Deliverables
you can verify.
Scope, responsibilities and acceptance criteria are defined during scoping.
Source mapAnd quality rules.
Documented warehouse and data flowsWith monitoring.
Dashboards and reportsAutomated and shared.
Evaluated predictive modelsAnd monitored over time.
REFERENCES
On the ground,
in production.
ORANGE · CÔTE D’IVOIRE & BURKINA FASO
OMER: steering distribution in near real time
Point-of-sale scoring, stock-out prediction and hourly reports for sales teams.
Read the case study →DataTelecom operator
SUNSHINE: revenue assurance
Automated database reconciliation and revenue control.
InstitutionsAfrican Union
Animal resources: an IT system for 55 states
From data collection to data sharing, to anticipate health alerts across the continent.
Case study →TECHNICAL ENVIRONMENT
Technologies
we master.
Around thirty open-source and vendor solutions, chosen to fit your context. Technologies are confirmed during scoping.
Processing
- Apache Spark
- Airflow
- dbt
- ClickHouse
- Elasticsearch
Visualisation
- Power BI
- Apache Superset
- Kibana
- Grafana
Learning
- MLflow
- scikit-learn
- TensorFlow
- PyTorch
FREQUENTLY ASKED QUESTIONS
What we’re
often asked.
Do we need a data lake to start?
No. We start with the indicators that matter for your decisions, then build the foundation as use cases are confirmed.
Our data quality is poor. Is that a blocker?
That’s the case for almost every project. Quality is handled within the pipeline: rules, controls, reconciliation and correction at the source.
Where is the data hosted?
Wherever your constraints require: in your data centres or with a hosting provider chosen with you, in line with applicable regulations.
GO FURTHER
Expertise
to explore.
GETTING STARTED
A clearly defined
first step.
WHEN TO CALL US
Scattered data, manual dashboards, decisions made without reliable indicators.
FIRST ENGAGEMENT
A data scoping: sources, priority indicators and a first dashboard in production.
INDICATIVE DURATION
4 to 6 weeks
WHAT WE NEED FROM YOU
Access to data sources and a business owner for the indicators.