Data Framework

Our approach to DataFramework

Data Tracking
- Planning and implementation of a consistent tracking strategy (e.g. for websites, apps or CRM systems)
- Collection of relevant user, transaction and process data at every touchpoint
Customer Data Platform
- Design and construction of a central platform on which customer data flows together
- Integration of all systems (e.g. shop, CRM, marketing automation) and implementation of data guidelines
Data Warehouse (DWH)
- Creation of a structured database for reporting and analysis
- Optimized data models and ETL processes that ensure high data quality and consistency‍
Data Lake
- Setting up flexible storage structures for unstructured or semi-structure ddata
- Enables exploratory analysis and machine learning applications
Real-time & near-time architecture‍
- Implementation of powerful streaming platforms (e.g. Apache Kafka)
- Use of frameworks such as Apache Flink to Process data streams in real time and make automated decisions
Omnichannel Data Integration
- Planning and implementation of complex ETL or ELT processes
- Harmonization of various data sources and formats to create a holistic customer picture

Our tools and methods

Cloud platforms (Google Cloud, AWS, Azure)
We choose the right cloud infrastructure for your requirements and rely on scalable services such as BigQuery, Redshift or Synapse.
Opensource technologies (Kafka, Flink, Airflow, Spark)
Flexible tools allow you to retain control over data flows, streaming applications and workflows at all times.
Database technologies (SQL, NoSQL)
Depending on the application, we combine relational and non-relational databases to achieve the best possible performance and structure.
MLOps frameworks (Vertex AI, MLflow)
We rely on proven platforms to automate machine learning pipelines and deploy models in production.
Agile development & DevOps
Our interdisciplinary teams work according to agile methods (Scrum, Kanban) and integrate continuous improvement processes (CI/CD).

What results (deliverables) do you get after /during /through a data framework?

Comprehensive data tracking plan
A clear guide on where and how to collect relevant data and how to feed it consistently into your systems.

Customer data platform
A central location where all customer data is brought together, segmented and made available for other applications.

Structured data warehouse
‍With defined data models, ETL processes and documentation so that your reporting and BI tools are reliably supplied.

Data lake for unstructured data
‍Flexible storage and analysis capacities for large amounts of data, including scaling options and interfaces to machine learning applications.

Real-time and near-time infrastructure
‍Technical implementation of streaming tools (Kafka, Flink) that enable automated decision-making processes and live dashboards.

Omnichannel data integration
‍Uniform ETL processes for all channels – online shop, marketplaces, CRM, ERP, POS systems – for a 360-degree customer picture.

Matthias Dietrich

CEO & Founder

As the founder and managing director of foobar Agency, Matthias brings over 20 years of experience in implementing and strategizing eCommerce projects. His expertise helps companies effectively translate technological innovation into business success.

Fritz has 10 years of experience in strategic consulting for medium-sized businesses and previously served as Head of eCommerce at Burda Digital, where he successfully guided brands like cyberport. His strategic expertise combines practical implementation with visionary approaches.

Fritz Schildt de Baey

Associate Partner

Fritz has 10 years of experience in strategic consulting for medium-sized businesses and previously served as Head of eCommerce at Burda Digital, where he successfully guided brands like cyberport. His strategic expertise combines practical implementation with visionary approaches.

Max Lüling

Advisor

Max brings more than 20 years of experience in consulting and building digital business models. His focus lies on digitizing and transforming traditional business structures to prepare companies for future challenges.

Scalable data architecture for future-proof innovations

Data Framework

Let's talk!