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
The Business Impact of Your Data Engineering: Transforming Raw Data into Value
Our Mission: Business Value over Data Pipelines
Data Engineering is the art of transforming raw data into usable, reliable insights. We design efficient, automated processes that supply your analysts and data scientists with quality-assured data.
The Measurable Impact
Data Quality: 60% less inconsistencies through automated ETL/ELT processes.
Efficiency: 80% less manual effort in data preparation (Case Study MediaPrint).
Time-to-Insight: Insights are available in minutes, not days.
Facts based on our work for E-Commerce and media companies
Your Path to a Clean Data Foundation
We start with a Requirements Analysis and develop the ETL/ELT pipeline architecture that creates your Golden Record. We ensure your data is quality-assured and usable.
Take Action: Schedule a Data Engineering Consultation
You still need the basics: The Ultimate Guide: All the Basics of Data Governance
Do you still need the basics, definitions, and background information on data architecture?
All information that does not directly relate to your 5-phase process can be found centrally in our expert guide.
Start with a deep dive: 3 key principles for Data Engineers, eliminate the complexity and vendor lock-in
or Ultimate Guide: Basics on Data Governance
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 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:
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