Rapid data audit
Within one to two weeks, our team conducts a preliminary analysis of available data sources, engages in conversations with clients to gain a full understanding of the business domain, and proceeds to design a series of possible data science projects and data governance recommendations to maximize the predictable value generation of data within an organization.
Identification of data source
Understanding and documentation of data sources, de-normalization methods, useful data project opportunities and governance recommendations around the initiative.
Data Awareness
We help our clients' teams understand the opportunities presented by data science projects and guide them to make decisions that maximize the value of their organization's engagement in data science. We introduce our clients to our rapid data audit process.
Prioritization of data opportunities
We use design thinking methodologies to combine our newly acquired knowledge of data sources, our science and engineering background, and our insights gained from conversations with our clients to create a set of data science project implementations ranked by estimated effort as well as estimated business value impact.
Data science as a service
Within 4-8 weeks, our team of domain experts, engineers, data scientists, and developers will race through a specific data business problem and deliver high-quality insights and visualizations.
Our process follows a 5 step plan
Step 1
Data Problem DefinitionStep 2
Data SourcingStep 3
Extraction, Cleaning, and TransformationStep 4
Modeling and AnalysisStep 5
DeploymentTeam Overview
Mamitiana Ignace
Manager of operations Data
Jimmy-Olivier SINNAN
Business Manager
Jacky Andriniaina
Data Scientist
Jamal Baali
Data Scientist et Consultant RPA