Welcome to the DA&AI wiki, here you will find all the information you need to interact with DA&AI, order New Projects and Small Enhancements (change requests) and see what we're currently working on.
Empower people to generate value by creating insight based on trusted data.
Committed to being a trusted advisor and delivering the best data solutions via our hubs, using:
Thought leadership
Cutting edge technology
High performing teams
What we do
The Data, Analytics and AI Platform is part of Digital Technologies (DT) and has a clear mandate to scale the data capabilities of Solvay.
The purpose of the DA&AI Platform is to:
- Build and scale new digital capabilities;
- Simplify and modernise our technology landscape;
- Protect and secure technology assets; and
- Establish data as an enterprise asset.
Data will become an enterprise asset through the group Data & Analytics strategy which sets the tune to accelerate value creation while enabling the foundations. This includes:
- Integrated tool chains for data science, from acquisition, organisation, analysis and delivery.
- The model and artefact libraries as well, the data science labs and the AI hub of a modern integrated data and analytics capability.
- A contracts and expertise centre for data science as a service for both the Product Groups and enterprise overall, enabling data science as a core business capability within the business
- Supporting AI as an expertise centre out of D&A while the user cases are maturing
The DA&AI Operating Model (OM) supports and builds on the DT ATOM.
DA&AI Operating Model
Our Operating Model ensures:
- A single point of contact for Data & Analytics;
- Proactive management of a well defined portfolio of projects (current and future);
- Solution design is developed according to a common platform architecture;
- We build a community of practices and expertise which enables best practice sharing, knowledge transfer and standardisation;
- A dedicated team responsible for the moves to production and monitoring of apps;
- Advisory capabilities in place to work with the product managers and business; and
- DA&AI objectives defined, cascaded down and regularly monitored.
DA&AI Leadership Team
