Data pipelines: Provide data and transform it at scale

Large amounts of data can be extracted from their original environment via data pipelines and made available for further processing. This includes various transformations and processes such as copying data, transferring it to the cloud, combining different data sets and operations such as structuring and formatting. Data pipelines form an important basis to ensure that information is continuously available.

With data pipelines you can

  • Better achieve analytical and business purposes
  • Process data quickly, efficiently and without errors
  • Automate processes
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Technologies in the field of data pipelines

As experts and confluent partners for Apache Kafka, we advise companies on finding the right technologies that fit their specific requirements.

Kafka Connect

Kafka Connect is an open source framework that allows data sources and sinks to be seamlessly integrated and managed in Apache Kafka.


Prefect is a Python-based, open-source platform for automating data pipelines and workflows.

Apache Airflow

Apache Airflow is an open source tool for creating, scheduling, and monitoring workflow orchestrations.

Our services in the field of data pipelines

In order to make sensible use of large data flows and the potential associated with them, we support companies with advice and implementation.

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Kafka workshop

With the popular open source software, data streams can be scaled, stored and processed via a distributed streaming platform.

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IT support

Our IT support ensures that the systems operate securely by monitoring them and rectifying faults immediately.

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In order to use data pipelines and the associated technologies effectively, we take care of the implementation in the existing IT environment

With advice from Acosom on stable IT infrastructures

IT consulting is often the first step when companies want to introduce new technologies. In our advice, we rely on our many years of know-how and our knowledge in the field of modern software architectures. Our approach includes:

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Initial consultation

In an initial discussion, goals and wishes are defined and questions about costs are clarified. We then adapt our consulting services transparently.

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Analysis and concept

After a precise analysis of the IT landscape and the technologies used, all the points discussed are incorporated into the concept creation.

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Quality is our top priority. That is why our IT consulting also includes the implementation of the selected products - even with demanding IT system landscapes. IT consulting aims at sustainable results with real added value.

Data pipelines in the company

The use of data pipelines requires thorough planning and implementation. The information fed in should be as complete and error-free as possible so that a high quality can be achieved. It is also important that the technologies used function without problems, even with growing volumes and increased transmission speeds, without performance suffering. We are the experts to ensure that companies receive secure IT systems in which data is reliably protected against access in the development of robust IT architectures for advice and implementation.

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Flexible and scalable: the advantages of data pipelines

Data pipelines can be used in various application areas because they offer a powerful and flexible way to process and analyze large amounts of data. Other benefits include:

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Greater efficiency

With data pipelines, data collection and processing can be automated, reducing manual effort and increasing accuracy.

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Higher data quality

Data pipelines can perform real-time data validation and cleaning, improving data quality and reliability.

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Better decisions

With real-time data, faster, information-based decisions can be made and agile reactions to changing conditions can be made.

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Customer journey

Businesses can personalize their offerings and provide their customers with more relevant and timely information.

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Optimal teamwork

Collaboration and cross-cutting decisions are streamlined by providing real-time data to the different teams.

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Competitive advantage

Companies using modern technologies such as data pipelines are one step ahead of competitors using traditional methods.

Frequently Asked Questions

How do data pipelines help the business?

Companies usually accumulate large amounts of data. The larger the volume of data, the slower and more inefficient it is to process. Data pipelines ensure that data processing is clearly structured and implemented effectively. Acosom helps to better exploit the potential of data by using data pipelines.

What types of data pipelines are there?

With data pipelines, a distinction is made between ETL and ELT. With the classic ETL (Extract, Transform, Load) method, the data is extracted, transformed and then loaded or transferred. However, data is lost during the transformation. That’s why ELT first loads the data, saves it and only then transforms it.

Data pipelines processes: ETL vs. ELT

Data pipelines differ in their process steps and processing types. Extract, Transform, Load (ETL) is the classic method: data is first extracted, then prepared and then loaded into another system. “Transform” involves consolidating data and cleaning the data from low-quality data. “Load” means the provision of the data via container or API. However, these intermediate steps can be built on top of one another in different ways. In the ELT process (Extract, Load, Transfer), the data is first loaded and only then processed - i.e. exactly the other way around than is the case with ETL. Due to the reverse order with ELT, no data is lost in this way. This is useful, for example, to train machine learning models as precisely as possible. The ELT approach is also suitable for big data and data lakes.

What role does data engineering play in data pipelines?

In addition to data warehouses and data engineers, data pipelines are the main components of data engineering. Data engineering summarizes a series of measures that create interfaces and mechanisms for a continuous and reliable flow of information and access. Data engineers are responsible for setting up and operating the data infrastructure in companies. In data warehouses, companies collect, store and format extracted data from certain systems. This data is moved – for example from applications to a data warehouse or database – via data pipelines.