What does Data Analytics Consulting cost at MaibornWolff?

Data analytics consulting starts at €4,000 for half-day strategy workshops. For more comprehensive services such as week-long proof-of-concepts, the fixed prices are around €20,000. For individual project requirements, we provide customized quotes after a non-binding consultation. This ensures you receive a solution that is precisely tailored to your technological infrastructure and specific data processing goals.

What is meant by the term data quality?

Data quality defines the degree to which information can serve as a reliable basis for decision-making. We ensure this quality through targeted processes for valid key figures. A key component is data lineage, which makes the path of data from its source to the final metric fully traceable. This allows us to identify weak points in the data flow and guarantee a high level of reliability in your analyses.

What is data ownership?

Data ownership governs the clear accountability of individuals or business units for defined data assets within an organization. This includes the establishment of binding processes for data maintenance and quality assurance. Only through clearly defined responsibilities can information be structured, prepared, and used to maximum effect. We establish these structures as part of your consulting engagement to permanently maximize the value of your data across the entire organization.

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Data analytics consulting: Unlocking potential

From data silos to decision-making: we unlock the potential of your data and reduce your costs in the long term.

Data analytics consulting for informed business decisions

Data is the foundation, but analysis is what creates the value. With targeted data analytics consulting, we transform your raw data into real competitive advantages. We go beyond classic analytics consulting: we optimize your business processes, resolve acute efficiency bottlenecks, and establish sustainable data governance including data stewardship.

Our credo: Less Technology. Better Business. We don't implement technology for technology's sake – instead, we create a data-driven decision-making culture that visualizes your information from a wide variety of sources to maximum effect. This gives you the foundation for well-informed strategies – without detours.

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Scalable implementation

We implement stable workflows for large organizations. With the power of 900 experts, we support you in implementing projects securely and with high availability—from the initial idea to the long-term operation of your applications.

Structured database

We put an end to searching in data silos. Information is prepared in such a way that it is immediately available for analysis. High data quality forms the basis for controlling your processes in a long-term, secure, and traceable manner.

Focus on users

Technology is not an end in itself. We ensure that dashboards and models are understood by the people in your company. A vibrant data culture ensures acceptance of your investments and makes results usable.

Targeted cost reduction

We only use methods that deliver measurable results. Whether machine learning or NLP, we develop solutions that simplify your processes and demonstrably reduce ongoing operating costs in your IT landscape.

Technical integration: From machine learning to SAP HANA

Our experts integrate data science workflows into complex environments such as SAP HANA, Hadoop, or SAS. We leverage machine learning, NLP, and data mining to anchor scalable solutions reliably within your existing tool landscape.

With over 850 employees, we guide you through all phases – from methodical analysis to the finished application that resolves your efficiency challenges and puts data to targeted use for your strategic goals. We focus on productive implementation, ensuring your models perform reliably even under load.

MLOps: Automation and Data Engineering

Through MLOps, we integrate automated data science workflows into the existing IT infrastructure. This optimizes collaboration between business units and IT experts.

A core aspect of our work focuses on the extraction, transformation, and preparation of data (ETL/ELT). Since these processes account for around 80 percent of the effort required for a stable data product, we ensure the quality and scalability of your analytical models through professional engineering.

Data protection and data governance

Strategic reporting and dashboarding

The goal is the visualization of relevant key figures through a high-performance data model. We support you in building dashboards that present complex data sources in a clear and comprehensible way. Our process for effective analytics consulting in reporting encompasses five core steps:

Target group analysis: Identification of end users and their specific requirements.
Requirement definition: Determination of report types and the necessary user experience.
Design concept: Selection of suitable visualization forms for the data.
Technical configuration: Implementation of the necessary report filters and logic.
Optimization: Refining the design for maximum user acceptance

Project phases: From data thinking to productive MVP

Success in data analytics consulting depends on thorough preparation. In a technical assessment, we analyze your existing data landscape, define the project scope, and capture all security requirements. If use cases are still unclear, we identify the relevant data sources and areas of application in Data Thinking workshops.

Our goal is the rapid development of a Minimum Viable Product (MVP) that forms the technological foundation for your BI solutions. We place great importance on results that go beyond mere testing phases (proof of concept) and are transferred directly into stable, production-ready applications. This ensures that your analytics consulting project delivers measurable outcomes rather than ending as a mere experiment.

1. Analysis of objectives and structures

We define the project goals and analyze organizational structures and data sources. In doing so, we identify interfaces, review provision cycles, and designate responsible data owners in order to establish the framework for implementation.

2. Inventory of the database

Our specialists examine all available data sources in detail. We evaluate the quality and check the technical suitability for analytical procedures in order to create a reliable basis for the subsequent implementation of your project.

3. Identification of potential

Using data thinking, we search for additional relevant data sources. We decide together whether to expand the project context and integrate additional use cases in order to sustainably increase the overall value of the analytical solution.

4. Ecosystem and operational activities

We define the interfaces for ongoing operations and optimize processes to improve your workflows. In doing so, we implement the necessary monitoring solutions and DevOps structures to ensure stable use of the new application.

5. Security and data governance

We configure access rights and regulate the visibility of information. This allows us to create the basis for data sharing and data products within a data domain, while maintaining the highest standards of security and governance.

6. Empowerment and project completion

In mixed teams, we transfer technical knowledge to your specialist departments. Through close cooperation, we empower your experts to take responsibility for the product and ultimately manage operations independently.

Methodology and technological foundation

Reliable data analytics consulting requires a solid technical foundation. We bridge the gap between data architecture, cloud platforms, and classic data engineering to make raw data available for analysis. A key focus lies on the establishment of standards through data cataloging, taxonomies, and structured metadata management.

These practices are the prerequisite for consistently high data quality across all operational and analytical systems. By combining data science, AI models, and collaborative methods, we ensure that the technological infrastructure is precisely aligned with the requirements of your business units.

Häufige Fragen zu Data Analytics Consulting

What does Data Analytics Consulting cost at MaibornWolff?

Data analytics consulting starts at €4,000 for half-day strategy workshops. For more comprehensive services such as week-long proof-of-concepts, the fixed prices are around €20,000. For individual project requirements, we provide customized quotes after a non-binding consultation. This ensures you receive a solution that is precisely tailored to your technological infrastructure and specific data processing goals.
What is meant by the term data quality?

Data quality defines the degree to which information can serve as a reliable basis for decision-making. We ensure this quality through targeted processes for valid key figures. A key component is data lineage, which makes the path of data from its source to the final metric fully traceable. This allows us to identify weak points in the data flow and guarantee a high level of reliability in your analyses.
What is data ownership?

Data ownership governs the clear accountability of individuals or business units for defined data assets within an organization. This includes the establishment of binding processes for data maintenance and quality assurance. Only through clearly defined responsibilities can information be structured, prepared, and used to maximum effect. We establish these structures as part of your consulting engagement to permanently maximize the value of your data across the entire organization.