Data Engineering
Our data engineering service covers the entire value chain of your data: from extraction from various sources to modeling to efficient orchestration. We ensure that your data is always available and can be used for analysis.
Our process
Data extraction and integration
- Translating technical requirements into technical concepts
- Identify required data sources and data connection options
- Providing the automated data integration via python pipelines or using leading SaaS providers
Data Modelling
- Modelling of integrated raw data along defined use cases and business processes
- Design and implementation of a general and scalable data model (e.g. Kimball or Data Vault)
- Enables efficient access to central and validated data for evaluations within the company
Orchestration
- Establishing a comprehensive Orchestrate the entire data infrastructure
- Transparent monitoring of all processes for providing data within the company
- Trigger or scheduled orchestration of data pipelines makes the data available when it is needed
Data Engineering
Business value
Data engineering is the key to generating real business value from your raw data. By systematically collecting, transforming and providing your data, you create the basis for well-founded decisions, innovative products and optimized processes. With data engineering, you can identify market potential, minimize risks and strengthen your competitive advantage.
Efficiency & automation
Imagine that your data is working for you. Data engineering makes it possible to automate many data-related tasks. This saves you time and resources, reduces manual errors and allows you to focus on strategic projects. An efficient data pipeline ensures that the right information gets to the right place at the right time.
Innovation & competitive advantage
In today's data-driven world, innovation is inextricably linked to the ability to use data effectively. Data engineering enables you to develop new products and services and to test innovative business models. With a solid foundation in data engineering, you can react faster to market changes and expand your competitive advantage.
Data quality & trust
Data is only as good as its quality. Data engineering ensures that your data is accurate, complete, and consistent. By implementing quality controls and data validations, you can gain confidence in your data and make informed decisions. High data quality is the basis for reliable analyses and successful business results.
This is how we go about data engineering services
From raw data extraction to providing valuable insights, I'll guide you step by step through our proven data engineering process. We transform your complex data into clear and meaningful information that helps you make informed decisions and move your business forward.
Requirements analysis & design
At the beginning, we work intensively on your individual requirements. Together, we define your goals and develop a tailor-made solution. We analyse your existing data structures, identify potential and develop a clear roadmap for your data engineering project.
Data Extraction & Integration
We extract your data from various sources, such as databases, APIs, or CSV files. This data is then brought together in a central storage unit. We attach great importance to data quality and consistency in order to create a solid basis for your analyses.
Data cleansing and transformation
Raw data is often incomplete, inconsistent, or contains errors. In this phase, we clean and transform your data to prepare it for analysis. We fill in missing values, correct errors, and normalize data to ensure a consistent structure.
Data modelling & data infrastructure construction
We build a robust data model that meets your specific requirements. This model serves as a basis for organizing and storing your data in an appropriate database or data warehouse. In parallel, we are setting up the entire data infrastructure, including the necessary ETL processes.
Implementation and monitoring
After successful development, we implement the solution in your IT environment. We ensure a smooth transition and train your employees as needed. We also use monitoring tools to continuously monitor the performance of the data pipeline and ensure that your data is always up to date and available.
Data engineering in our framework
We work with the framework organization, culture and architecture.
Because in our opinion, these three areas are the most important factors for successfully anchoring data in the company in the long term.
Data engineering focuses on architecture. As a company, you can opt for a focus that best supports the company's goals in the short term. But it is important to always keep an eye on all areas and not to neglect any of the three pillars in order to generate long-term impact.
The Data Institute — the strong partner for data engineering services
We understand that your data is a valuable asset. That is why we treat them with the utmost care. With our data engineering solutions, you can enable your company to react faster to market changes, identify new business opportunities and increase customer satisfaction.
What is the Data Engineering Service anyway
Data engineering is the process of turning raw data into a usable form. We extract, transform, and load your data into specialized systems so you can use it for analytics and machine learning. It is the basis for data-driven decisions.
Who needs data engineering services?
In fact, every company that collects data can benefit from data engineering. Whether you work in e-commerce, manufacturing, or finance — with well-structured data, you can optimize processes, develop new products, and make better decisions.
Who is involved in Data Engineering Services?
A data engineering project usually involves various roles:
- Data Engineer: The architect of your data landscape who builds the data structures and processes.
- Data Scientist: The expert in statistical methods and machine learning who draws valuable insights from the data.
- Data Analyst: The translator of data who transforms complex relationships into understandable reports.
What services can be combined withData Engineering?
Case studies on the subjectData Engineering
You can find suitable examples of our work on this topic in the following case studies:
Knowledge around Data Engineering
In addition to case studies, we also have various blog articles on the topic:
Glossary aboutData Engineering
Find all the important terms explained in detail and clearly here.
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