What is Data engineering?
Data engineering services are at the heart of our offering and aim to provide solid technological and governance foundation for your data platform to enable data-driven decision making and machine learning capabilities. Typically, those services cover 3 key stages: data collection, transformation and publishing with an aim of building and operating a data platform built around business requirements.
Illustrative list of services
- Review and assessment of current data infrastructure, recommendations for best technologies and target solution
- POC, feasibility studies, implementation roadmap for target solution
- Assembling your technologies into effective stack and avoiding inefficiencies of maintenance
- Operating model recommendations and help to deploy it into organisation
- Data platform implementation based on defined target solution (full or selected components)
- Migration from legacy to cloud based data platforms
- Data pipelines build and implementation (e.g. adding new sources), maintenance and improvement:
- Batch and Files
- Native App connections
- DB (one time and delta)
- API (REST)
- Streaming and Events
- Performance optimisation and improvement
- Data quality monitoring solutions
- Data governance, documentation and data cataloging
Benefits for stakeholders
- Management team: single source of truth, reliable performance, ROI into data platform
- Business units: timely and accurate reporting, AI and ML based insights for revenue and profit maximisation
- Product owners: data driven product enablement, deep insights into product performance data
- Data scientists: data and tools to build and run ML models
- Governance and compliance: robust and technologically enabled data management framework
Technologies
We are vendor agnostic while building solutions for our customers. Here you can find some of the technologies we worked with:
