Tailored data solutions for life sciences & pharmaceuticals
We help life science and pharmaceutical companies use their data strategically. With industry-specific know-how, scalable platforms and powerful BI solutions, we create the basis for faster decisions, assured compliance and sustainable innovation.
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Data integration for
Life Sciences & Pharma
The life science and pharmaceutical industries are facing major, data-driven challenges. Research, studies, production, and supply chains generate huge amounts of data, but data silos and fragmented systems slow down analytics and innovation. Strict regulation requires excellent data management and complete traceability. Patent expires, competition from generic drugs, and pressure to deliver innovations faster are increasing costs.
We know these challenges from numerous projects in the life science and pharmaceutical sectors and know how to solve them pragmatically and sustainably. We help you build sustainable data platforms, develop scalable reporting and analytics structures, and establish data governance models that meet both regulatory requirements and professional needs.
Typical questions
Typical questions
- How do we identify, evaluate and prioritize use cases with the highest strategic impact (e.g. churn prevention vs. network data analysis)?
- How do we anchor regulatory requirements (unbundling, EnWG, GDPR) in a uniform data governance concept?
- Which platform architecture allows us long-term flexibility while maintaining security and investment protection?
- How do we establish a central understanding of data across various IT systems, market roles and specialist areas?
Our services
- Development of a holistic data strategy with a top-down and bottom-up approach
- Use case portfolio analysis including profitability assessment
- Development of a role model for data ownership & governance
- Change enablement & organizational development for data-driven work
success stories
For RheinEnergie, we developed a central data strategy that is closely linked to corporate strategy and divisional strategies and supports their implementation in a targeted manner. The strategy addresses decentralized data landscapes and promotes a company-wide self-service culture for data-driven value creation. It provides clarity about roles and responsibilities and defines a common understanding of governance as the basis for scalable, future-oriented use of data.
Typical questions
Typical questions
- How do we identify, evaluate and prioritize use cases with the highest strategic impact (e.g. churn prevention vs. network data analysis)?
- How do we anchor regulatory requirements (unbundling, EnWG, GDPR) in a uniform data governance concept?
- Which platform architecture allows us long-term flexibility while maintaining security and investment protection?
- How do we establish a central understanding of data across various IT systems, market roles and specialist areas?
Our services
- Development of a holistic data strategy with a top-down and bottom-up approach
- Use case portfolio analysis including profitability assessment
- Development of a role model for data ownership & governance
- Change enablement & organizational development for data-driven work
success stories
For RheinEnergie, we developed a central data strategy that is closely linked to corporate strategy and divisional strategies and supports their implementation in a targeted manner. The strategy addresses decentralized data landscapes and promotes a company-wide self-service culture for data-driven value creation. It provides clarity about roles and responsibilities and defines a common understanding of governance as the basis for scalable, future-oriented use of data.
Typical questions
Typical questions
- How do we identify, evaluate and prioritize use cases with the highest strategic impact (e.g. churn prevention vs. network data analysis)?
- How do we anchor regulatory requirements (unbundling, EnWG, GDPR) in a uniform data governance concept?
- Which platform architecture allows us long-term flexibility while maintaining security and investment protection?
- How do we establish a central understanding of data across various IT systems, market roles and specialist areas?
Our services
- Development of a holistic data strategy with a top-down and bottom-up approach
- Use case portfolio analysis including profitability assessment
- Development of a role model for data ownership & governance
- Change enablement & organizational development for data-driven work
success stories
For RheinEnergie, we developed a central data strategy that is closely linked to corporate strategy and divisional strategies and supports their implementation in a targeted manner. The strategy addresses decentralized data landscapes and promotes a company-wide self-service culture for data-driven value creation. It provides clarity about roles and responsibilities and defines a common understanding of governance as the basis for scalable, future-oriented use of data.
Our established solutions for life science & pharmaceutical companies
Questions our customers ask
- Which use cases have the biggest strategic impact?
- How can we set up agile data governance that complies with GxP standards and takes into account regulatory requirements such as EMA, BfArM and PEI?
- How do we avoid delays in approvals and market entry due to poor data integrity and data fragmentation?
How we support your life science or pharmaceutical company
- Conducting data thinking workshops and maturity assessments to identify use cases with the highest added value
- Development of a holistic data strategy with a top-down and bottom-up approach
- Establishment of role and authorization concepts for data ownership & governance
success stories
For RheinEnergie, we have developed a central data strategy that is interlinked with corporate and divisional strategies. The strategy promotes a decentralized data culture and strengthens self-service and governance — as a basis for scalable, future-proof data use.
Questions our customers ask
- How do we integrate data from heterogeneous sources (ERP, CRM, laboratory, IoT, market data) centrally and fail-safe?
- Which platform architecture supports international approval processes and cross-site research?
- Which data architecture enables complete data lineage, audit trails, and GxP-compliant logging?
How we support your life science or pharmaceutical company
- Build scalable, cloud-based data platforms
- Development of robust data pipelines for automated data integration of LIMS, production systems, ERP, CRM & EHR
- Automatic monitoring, logging and audit trails to ensure data quality in a regulatory context
success stories
For EVM (Energieversorgung Mittelrein), we have brought together, harmonized and enriched data from historically developed systems with external data. The modular data modeling approach enables future expansions, and the modern lakehouse structure provides a stable basis for AI initiatives.
Our customers were concerned with these questions
- How do we automate our reporting to save time in controlling?
- How do we identify market trends or security risks at an early stage?
- How do we create a uniform reporting structure for all departments without losing precision?
- How do we support our departments with self-service analytics and role-based access?
How we support your life science or pharmaceutical company
- Development of interactive dashboards for research, production, quality assurance and sales
- Development of self-service BI including governance and training concept
- Setting up automated alerts for critical changes (market access, supply chain and clinical studies)
success stories
For RheinEnergie, we have laid the central basis for data-driven analyses. Data thinking workshops and structured use case development resulted in a clear roadmap for BI applications and self-service analytics. For evm, we created a 360° customer view by building a customer data platform.
How we have already successfully supported other life science & pharmaceutical companies
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taod helped us to store our data in our area in an orderly manner and to create good Power BI reports. We now have a clear and user-friendly overview that creates transparency about the data situation. It enables a better understanding of the interrelationships, supports well-founded decisions and makes it easier to coordinate common goals.
The business was provided with profound transparency and further analyses in order to address identifiable improvement opportunities in the respective specialist departments and then implement them together. Overall, the project is a complete success from Dexcom Germany's point of view.
Dexcom
Our solutions for network providers
Transparency about network investments & maintenance measures
We provide an overview of investment planning and maintenance — from medium voltage to local network level. With comprehensible data and visualizations for technology, controlling and regulatory reporting.
Securing grid stability through intelligent processes
We support you in implementing legal requirements such as Redispatch 2.0 — with sophisticated data processes that reliably combine generation, network operation and planning.
Integration of geodata & spatial reference into BI landscapes
We integrate geodata into existing BI systems — e.g. for network expansion planning, capacity assessment or location decisions. This makes spatial reference an integral part of data-based decisions.
Reliable automation of market communication
We make market processes such as supplier changes, MaKo2024 or format changes robust and maintainable — through clean data structures, automated test tracks and clearly defined workflows.
Data-based control of network connections
We help structure and accelerate grid connection processes for PV systems, charging infrastructure or heat pumps based on data — with automated preliminary checks, bottleneck checks and transparent monitoring.
Cross-project reporting governance
We help build a consistent reporting landscape across projects and specialist areas — with coordinated key figures, clear processes and sustainable data management.
From strategy to self-service: This is how we support life science & pharmaceutical companies on their data journey.
Define status quo & use case
Together, we develop a target image, define roles, use cases and a roadmap — tailored to your existing systems and strategic goals.
Modernize infrastructure
We create the technical basis with a scalable, maintainable data infrastructure.
Automate processes
Data pipelines, reporting routes and quality checks are automated — for stable data flows and consistent evaluations.
Empower teams
We make your departments fit for data — with targeted enablement in Power BI, Tableau & Co., so that you can work independently in the long term.
FAQ
Decisions are accelerated when relevant data is provided consistently, up-to-date and comprehensible. This requires clear data responsibility, coordinated key figures and processes that enable analyses without lengthy coordination.
Isolated solutions make regulatory traceability difficult and increase the risk of inconsistent decisions. In a regulated environment, such breaks can lead to delays, audit findings, or limited scalability.
Heterogeneous data sources such as LIMS, ERP, CRM or production systems are connected through standardized pipelines and a common data model so that data is consistent and usable across business areas and locations.
