Data Pipelines & ETL

The term ETL – extract, transform, load – is classically understood to mean accessing data from a data source, processing it and then storing the data in a data target. Solutions covering these requirements have been available on the market for several years. Our services in this environment include:

The classic ETL tools extend their range of functions, especially in the area of modeling data, in order to integrate artificial intelligence/machine learning algorithms. This extension creates the prerequisite to analyze the data already in the loading process (ETL) and to update the results into the data sources.

Data pipelines enable you to keep your data up-to-date in real time and continuously by integrating new processes and workflows in the loading process.

A data pipeline typically includes various elements of data processing. Examples include extracting data from the source system, harmonizing data from different data sources, deriving new insights from the data via AI/Machine Learning, and storing the data in the data target or visualizing the data for the user. In sum, you have a wide variety of options for "manipulating" your data.

Application examples for Data Pipelines are:

• Preparation of financial data for financial forecasting
• Integration of OCR solutions with algorithms for automated capture of master data from documents
• Processing of data from different data sources with transformation by AI algorithms into a unified schema

We support you in designing data pipelines with our expertise in data source connectivity and data targets. In addition, we bring in our know-how in the AI/Machine Learning environment based on various projects.

We create added value for your company together with you, not only by loading and transforming data, but also by drawing new insights from the data in the same step.