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Glossary
Data Management

Data Engineering

Data engineers design, build, and operate the systems and processes required to transform raw data into usable information.

Meaning in detailContact us now

Data engineering is a central part of modern companies. Data engineers play a crucial role in turning raw data into valuable insights. Through their work, they enable companies to make data-driven decisions and strengthen their competitive advantage.

Tasks in data engineering

Why is data engineering important?

  • Data-driven decisions: Data engineers provide the basis for data-based decisions by providing high-quality data.
  • Scalability: They build systems that can handle growing amounts of data.
  • Efficiency: By automating processes, they increase the efficiency of data processing.
  • Innovation: Data engineers make it possible to use new technologies such as Machine learning and artificial intelligence.

Key technologies in data engineering

  • SQL: The standard language for working with relational databases.
  • Python: A versatile programming language for data analysis and Machine learning.
  • Cloud platforms: Cloud-based services such as AWS, Azure, and GCP provide scalable and cost-effective solutions for data engineering.
  • Big data technologies: Hadoop, Spark, and other technologies for processing large amounts of data.

Here are a few more topics that you can find out more about:

Note: Our team benefited from the support of AI technologies while creating and maintaining this glossary.

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Passende Case Studies

Zu diesem Thema gibt es passende Case Studies

Alle Case Studies entdecken
Babymarkt is data-driven
eCommerce
5
Minuten Lesedauer

From data audit to individual architecture sketch

eCommerce thrives on data — babymarkt wanted to make even better use of it.
Couple reading a newspaper
Medien
5
Minuten Lesedauer

MediaPrint reinvents itself in terms of data technology

The publisher wanted a clear structure and the development of a data culture.
A modern data stack for in-depth customer analysis
eCommerce
4
Minuten Lesedauer

A modern data stack for in-depth customer analysis

Modern Data Stack is used for data integration to analyze customer behavior and product data
Hub & Spoke Model and Data Roll Out
Medien
4
Minuten Lesedauer

Hub & Spoke Model and Data Roll Out

Program developed for organization, architecture, culture; mission & vision for data organization

Which services fit to
Data Engineering
?

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Data Architecture

The right tools in the right place. Update the existing infrastructure or renew most of it.

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Data Strategy

When what happens how and why — that explains the data strategy.

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Reporting & Business Intelligence

Not just beautiful dashboards, but information at a glance.

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