Data Pipelines


We support you all around
Do you need a data pipeline to transfer data from multiple heterogeneous sources to one or even more target systems? Do you need to consolidate, filter, and process multiple data sources, possibly in real time? evoila can help you!
Our offer
Processing of structured, unstructured and semi-structured data
A data pipeline is a process, which handles data in multiple steps. There is a wide range of specific applications for data pipelines. They are used to pre-process data before storing them in one or more target systems for analytics.
True to the motto “garbage in—garbage out”, the quality and performance of a data pipeline is crucial for the success of data analytics processes. Our consultants offer the required expertise to help you as our customer in designing data pipelines to process structured, unstructured, and semi-structured data.


Data pipelines for large data volumes
When designing data pipelines, the handling of large data volumes is a significant challenge. Our consultants help you as our customer to implement highly available, scalable, and fully parallelized processes, which allow the processing and storge of data volumes in the petabyte range.
We offer a considerable number of certified consultants for different technologies. This enables us to select the right tool for your application and to support your enterprise in all phases.


Data Understanding
- Evaluation: (semi) structured Data, Unstructured Data
- Data Processing: Cleaning, Transformation
- Data Analysis: Aggregation, Machine Learning

Solution Design/Review
- Data Sources Stream
- Batch Processing Environment

Deployment
- Cluster Sizing Performance Tuning Monitoring
Our consultants get the best out of your data
The evoila group offers specialists in areas like cloud, hyperscaler, data engineering, data analytics & machine learning, security, and software development and is therefore able to comprehensively take care of your project. We operate independently from cloud providers and technologies.