Open-source, Python-based frameworks are an attractive alternative to large tool vendors and are increasingly used in specialized areas such as risk management. They offer strengths like modularity and comprehensive documentation, replacing standard frameworks such as SAS. Large tool vendors are natively implementing Python and Jupyter Notebooks in their cloud environments and benefiting from interoperability across all technical areas within the company. With high-performance connectors and lower costs, comprehensive open-source ETL/ELT and warehousing solutions are possible.
Our experts will support you in developing alternative, tailor-made and modular solutions that meet your business needs and can be seamlessly integrated into your CI/CD pipelines.
Python-based ETL/ELT and data analytics frameworks in conjunction with PostgreSQL as the database: Quick to deploy, customizable, portable, flexibly scalable, cost-effective
We work with a deployment-driven approach based on DevOps principles, using Jenkins, Docker, and Maven. We build CI/CD pipelines and integrate applications into them. Data and its rapid availability are our top priorities, which is why we utilize DataOps approaches
Production-ready scripts for setting up ETL/ELT infrastructures within migration scenarios save time and resources
Data integration, transformations and analysis in a homogeneous environment in Azure with DataBricks or Azure Data Factory
Keywords
- Process modeling
- Open Source Frameworks
- python
- R
- Deployment
- Pipelines
- DevOps
- Data Science
- Machine Learning
- Jupyter Notebook
