Data Governance Consulting Security, quality, and AI readiness for your data

Data governance is far more than just compliance. It is the foundation for transforming your data from a mere storage medium into a strategic competitive advantage.

With Woodmark, you establish a data governance framework that combines organisational policies with technical excellence. This creates the basis for trusted reporting, AI-driven innovation, and compliant operations. We support you in managing data as your organisation’s most valuable asset — securely, transparently, and efficiently.

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Our services in data governance

Analysis & Strategy

Framework & Organisation

Technical Enablement & Tools

From current state to a clear data strategy

Comprehensive assessment: We provide you with a clear overview of your data landscape and the underlying architecture.
Strategy development: Together, we develop a data governance strategy that is perfectly aligned with your objectives.
Foundation for success: We lay the groundwork for sustainable business success through reliable and validated data.

Structure and security in data management

Framework design: We design a framework that clearly defines structures, roles, and responsibilities.
Compliance & security: We establish sustainable processes to ensure data quality, data protection, and regulatory compliance.
Efficiency: Clear rules enable more efficient workflows in handling data.

Technical implementation and long-term integration

Policies & standards: We introduce standards to ensure long-term data protection and data security.
Tool integration: We advise you on selecting and implementing the right governance tools.
Building trust: Organisational measures strengthen trust in your data across the entire organisation.

Architecture review

We analyse your technical components and the logical structure of your data and BI architecture, creating a robust basis for informed decision-making.

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Assessment & Roadmap

We identify key areas for action and develop a tailored roadmap that sets clear priorities and provides rapid direction.

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Framework & Mentoring

We support you in solution design and tool selection, and guide your team through targeted mentoring. This fosters transparency and helps establish a truly data-driven culture.

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Architecture Review: The Foundation for Modern Data Management

Transparency and structure for your data landscape

Many organisations face the challenge that their data architecture has evolved over the years, becoming increasingly complex and difficult to manage. An architecture review provides clarity on how well your current data and BI landscape is positioned — and where action is needed.

We analyse your technical components as well as the logical structure of your systems, from cloud platforms and on-premises environments to relevant data sources. Throughout the process, we assess everything in the context of your strategic objectives and identify concrete optimisation opportunities. This gives you a well-founded basis for decision-making and ensures that your tools and processes are sustainably embedded within a modern data management framework.

Technical Assessment

Many data landscapes have evolved over time and are insufficiently documented. We analyse your existing data sources, interfaces, and data flows in detail, identifying areas where a lack of transparency, redundancies, or complex dependencies hinder effective data governance and day-to-day operations.

Tool Evaluation

In many cases, existing BI and analytics tools provide only limited support for data governance or are not properly integrated. We assess your current software landscape in terms of governance capabilities, data quality, security, and scalability, and identify where tools may be slowing down processes rather than supporting them.

Risk Analysis

Unclear responsibilities, technical debt, or inadequate access management concepts pose significant risks to data governance, compliance, and data security. We identify critical vulnerabilities and assess how well your data architecture can withstand current and future requirements.

Outcome

You receive a structured technical status report that provides a robust basis for informed decision-making — enabling the targeted expansion of your data governance and the sustainable evolution of your data architecture.

Assessment & Roadmap – Clarity and Direction

Strategic planning for your data journey

As data landscapes grow, parallel initiatives, unclear responsibilities, and a lack of prioritisation often emerge. Visibility is lost, and data governance remains difficult to grasp — even though clear decisions and concrete actions are urgently needed.

Through a comprehensive assessment, we identify the key areas for action within your data landscape and evaluate its current level of maturity. We take both organisational and technical aspects into account, engage relevant stakeholders, and develop a tailored roadmap with clear priorities and next steps for your data governance.

Assessment & Roadmap – Clarity and Direction

Stakeholder Interviews

Data governance often fails due to differing expectations between business units and IT. Through structured interviews, we capture the requirements, objectives, and pain points of relevant stakeholders, creating a shared understanding of data, responsibilities, and priorities.

Maturity Assessment

Many organisations recognise the need to take action on data governance but are unsure of their current position. We assess the maturity of your data governance across organisational, process, and technical dimensions and develop a realistic target state for your data strategy.

Prioritisation and identification of quick wins

Based on the assessment, we prioritise key initiatives, identify quick wins that deliver immediate value, and develop long-term strategic initiatives to establish sustainable data management.

Roadmap Development

Based on the prioritised initiatives, we develop a tailored data governance roadmap with clearly defined phases, assigned responsibilities, and concrete next steps for implementation.

Outcome

An implementation-focused data governance roadmap with clear priorities that brings together strategy, organisation, and technology — driving effective and future-ready data governance in a targeted way.

Data Governance Framework & Mentoring

Creating structure and embedding it sustainably

When responsibilities are unclear, data quality fluctuates, and rules exist only on paper, data governance quickly becomes a risk rather than a success factor. A data governance framework provides the necessary structure by defining how data is owned, managed, and used securely within your organisation.

Woodmark supports you in designing and implementing a tailored framework that clearly establishes roles, standards, and decision-making processes. Through targeted mentoring, we guide your team during implementation and ensure that data governance is firmly embedded in day-to-day operations.

Organisational Design

Unclear responsibilities are among the most common causes of data governance failure. We define clear roles such as Data Owners and Data Stewards, establish decision-making processes, and firmly embed governance responsibilities within your organisation.

Policy Development

Missing or inconsistent rules lead to poor data quality and increased risk. We develop practical policies and standards for data quality, access management, security, and compliance — designed to be reliably implemented in day-to-day operations.

Tool Selection and Implementation

Many organisations use tools that provide only limited support for data governance. We guide you through the selection and implementation of suitable data governance technologies — for example in areas such as data cataloguing, metadata management, or data quality — and ensure seamless integration into your existing data architecture.

Team Enablement

Data governance only works when knowledge is firmly embedded within the organisation. Through targeted coaching and mentoring, we empower your teams to independently apply roles, processes, and tools — ensuring that governance is sustainably embedded in your data management practices.

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Please leave your name and your preferred contact method — either your phone number or email address. We will get back to you as soon as possible and look forward to speaking with you.

Why choose Woodmark?

With 25 years of experience in data management, data quality, and analytics, Woodmark’s experts help you develop your data governance strategy and ensure security — even in complex cloud environments.

Based on your specific requirements, we work with you to create tailored solutions for your data landscape.

And most importantly, by involving stakeholders and business units at an early stage, we ensure that objectives are achieved and foster the acceptance needed to establish a truly data-driven culture across your organisation.

FAQs about Data Governance

What is meant by Data Governance?

Data Governance refers to the organisational and technical framework that enables companies to manage and control how data is handled. It defines roles, processes, standards and rules to ensure long-term data quality, security, transparency and compliance.

What are the benefits of Data Governance?

Effective Data Governance builds trust in data, improves decision-making and reduces risks. It enables legally compliant operations, more efficient processes, consistent reporting, and provides the foundation for analytics and AI initiatives.

Who is responsible for Data Governance and what roles are involved?

Data Governance is a shared responsibility between business departments and IT. Typical roles include Data Owners, Data Stewards and governance committees, who oversee data quality, standards, access rights and data usage.

Use cases for data governance

Customer success stories

Use Case

How Data Analytics Is Revolutionising Training and Health in Sport

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At the Olympic Training Center in Cologne, sports scientists face a key challenge: gaining deeper insights into Paralympic long jump performance. Together with Woodmark and AWS, biomechanics data and AI are used to analyse movement, speed, and take-off in near real time, enabling faster feedback, smarter diagnostics, and new perspectives for athletes and coaches.

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Use Case

How AI is accelerating the fresh start of Düsseldorfer Eislauf-Gemeinschaft (DEG)

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After their sporting restart, Düsseldorfer EG faced an extraordinary challenge: building a squad from scratch – under intense time pressure. Together with Woodmark, the traditional club turned to AI-driven analysis to identify player profiles with precision, assess market opportunities more quickly, and make well-founded decisions.

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Use Case

GDPR- & NIS2-Compliant Data Platform

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A leading company in the airline catering industry is laying the foundation for tomorrow’s inflight services with a modern data platform on AWS and Databricks. Scalable, secure and future-focused, it enables data-driven innovation, greater transparency and noticeably more efficient processes across the entire value chain.

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Enhanced Customer Service with an AI Chatbot

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With a GenAI bot for automated responses, Quirion speeds up support, eases the burden on teams, and boosts customer satisfaction. Fast. Scalable. Future-proof.

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AI-powered analysis of legal documents with AWS

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Imagine being able to analyse legal documents like NDAs in seconds – completely free from manual errors and endless hours of work. By leveraging AI and AWS Bedrock, we have developed a solution that automates the extraction of key contract information.

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AI & Amazon Q: The intelligent platform for data-driven ice hockey scouting

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With an AI-powered platform based on Amazon Q, IceHawk UG optimises its scouting and controlling: relevant data is centralised, player and opponent analyses are automated, and decisions are made based on solid foundations. A step towards data-driven, future-proof club development.

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SV Darmstadt 98 improves player analysis with AI technology

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Experience the future of sports data analysis with an AI-powered solution from AWS. The coaching staff and scouts can now easily ask questions like "Who is the best substitute for an injured player?" via voice query.

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Use Case

Development of a Data Governance Framework for an MS Purview-based data platform

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Through the new Data Governance Framework, including the Data Marketplace, a systematic improvement in data and metadata quality in the Data Lakehouse was achieved.

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Use Case

AI-supported tender optimization for construction companies

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Currently, reviewing tender documents takes several days. AWS's Gen-AI solution offers significant time savings and enables faster decisions through clear executive summaries

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Use Case

Introduction of Databricks platform at municipal utilities

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The introduction of the Databricks platform at the municipal utilities enables the IT department to address all use cases from the specialist departments, break down existing silos, and strengthen the reputation of IT.

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Use Case

GenAI route generation with AWS and the D2E program

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SilverRail Technologies aims to redefine the travel experience for its customers and has laid the foundation for a data-driven, AI-powered travel assistant.

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Use Case

Higher efficiency through process automation in AWS

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Woodmark has supported NHD Beteiligungs GmbH in reducing operational effort through the use of automation in AWS. This resulted in improved operational processes, reduced downtime, and lower costs in the AWS environment.

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Use Case

Migration and modernisation of the Redshift data warehouse

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Our client Tom Tailor was able to create a 'single point of truth' for business logic and KPIs with the migration and modernization of the Redshift data warehouse. This now enables more accurate data-driven decision-making.

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Use Case

Introduction of Amazon QuickSight for better comparability of staff and branches

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A butcher shop lacks established branch and personnel reporting, and the branch managers are using an outdated analysis system. With the implementation of Amazon QuickSight, fast evaluations are now possible.

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Use Case

Insurance group migrates from heterogeneous BI landscape to Amazon QuickSight

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An internationally operating insurance group saves license costs through the introduction of Amazon QuickSight and can focus on the content thanks to structured data visualisation

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Use Case

SV Darmstadt 98 is cloudifying its scouting data with AWS Glue.

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A Bundesliga club wanted a data-driven scouting system. By integrating external data sources, automating workflows, and implementing a central data lake, data quality and scouting efficiency were significantly improved.

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Use Case

SV Darmstadt 98 improves match data analysis with Amazon QuickSight

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The Bundesliga club was able to significantly improve data quality in the areas of athletics and scouting through centralized data visualization and the introduction of a QuickSight dashboard.

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Use Case

GenAI-supported generation of Ninox database models in AWS

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The goal of the software developer arcRider is to simplify the creation of Ninox database models in AWS with GenAI and to increase customer satisfaction...

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Use Case

Route optimization of a logistics company with AWS SageMaker

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The Faber Group BV offers pallet and pooling services. Due to the increasing complexity of supply chains and rising fuel prices, the company wants to optimize its route planning...

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Use Case

Introduction and coaching of the SAFe methodology

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FinTech startup with 50 developers aims to improve customer satisfaction with product quality and enhance internal collaboration through the use of SAFe and SCRUM methodologies...

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Use Case

Automated preprocessing of incoming email customer inquiries in inside sales

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In the inside sales department, a five-figure number of email inquiries are received annually, which are processed with a very high manual effort...

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Use Case

Digitalisation of processes / target concept for the specialist departments

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Shared responsibility for complex processes by two different authorities with many manual processes, decentralized data storage...

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Integration of affiliate, website analytics, SEA, and SAP into marketing analytics

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Data from affiliate marketing, website analytics, and SEA are manually analyzed side by side...

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Use Case

IT Architecture Support für die ‚New Car Architecture 2025‘

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The need for a data-driven automotive industry requires new data architectures in the vehicle and in the backend.

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Use Case

Architecture of a group data warehouse and project coaching

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There is a need for a group-wide data warehouse as the foundation for further BI applications.

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Use Case

Platform for automated creation of data-driven exposés for customer advisory services

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Desire for digitization, i.e., data-driven and automated customer advisory services in the healthcare sector...

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Use Case

Data governance concept at an automotive manufacturer

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The data lake is fed from various systems worldwide. Efficient utilization of the data lake therefore requires a company-wide, international data governance concept...

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Use Case

Concept and pilot implementation of the Alation Data Catalog

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For the large data lake with many diverse and unstructured data, central management and a consistently established data governance are required...

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Use Case

Standard reporting and data analysis in the business department with Tableau

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The reporting should be made more efficient, enabling self-service analytics and relieving the IT department...

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Use Case

Data-driven marketing for predicting the online customer journey with Dataiku

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There is a need for detailed analyses and forecasts of purchasing behavior, particularly for predicting the transformation of visitors into customers...

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Use Case

KPIs and visual analytics for optimising the planning of a transportation company

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The transportation company is looking for an automated, data-driven approach to assess the impact of individual construction projects on delays and optimize future planning.

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HPI Schulcloud with Jitsi and BigBlueButton

Use Case

High performance through auto-scaling of the open-source services Jitsi and BigBlueButton

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Covid-19 requires the rapid digitisation of school education. The open-source services Jitsi and BigBlueButton (bbb) have proven effective, but they are not automatically scalable...

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Use Case

Process transparency through analytical visualization of additive manufacturing

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The sensor data is available in various formats and resolutions and cannot be used for real-time analysis and quality monitoring

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Use Case

From Data Lab to 'Smart Data Factory' – Innovative data strategy based on Docker

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Managing non-financial risks requires a new data strategy. IT and the compliance department are seeking a way to collaboratively and iteratively implement data-driven risk analyses.

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Use Case

Cloud analytics unlocks vehicle data globally for R&D and quality management.

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Systematic use of vehicle data requires powerful cloud analytics, machine learning, and advanced visualisation.

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Use Case

Selection of a BI solution for near-realtime analytics in production

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Optimising the manufacturing plant requires the use of sensor measurement data from the production process in real time.

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Use Case

Prediction and prevention of component failures based on sensor data

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Real-time analytics are needed to effectively utilise the vast amount of machine data from the relevant production machines.

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Use Case

Design Thinking enhances innovation capability and opens up new revenue streams

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Market dynamics require greater innovation capability.

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Use Case

Training a decision model for churn prediction

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600 million data records of sales activities and purchase transactions.

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Use Case

Smart data platform as a data and data value broker

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Looking for a data hub that enables data-driven business models.

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Use Case

Strategic mid- and long-term planning

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Various data sources should be consolidated into a strategic overall picture and allow for detailed analysis...

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Use Case

Building a hybrid architecture for data analysis

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The system landscape for data analysis has become outdated and consists of isolated solutions...

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Use Case

Simulating and optimising airport charges

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Simulation of various fee scenarios considering multiple variables such as noise and pollutant emissions, noise classes, night-time and other surcharges.

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Use Case

Integration and development of an advanced analytics platform

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Aluminium wheels are produced using the low-pressure casting process, and after casting, they undergo an X-ray inspection.

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Use Case

Geo-fencing engine as a service based on HERE geo-data

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Geo-services have become essential for modern automobiles.

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Use Case

Development of the backend for driver assistance systems

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Vehicles can currently only use local sensors for information gathering.

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Use Case

Development of a software framework for sensor data analysis

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Data from over 170 channels in a proprietary format need to be stored, processed, and visually analysed.

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Use Case

Development of sensor processing chains on the HERE OLP

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The driver assistance systems are to be enhanced and improved with insights from the sensor data.

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Use Case

Building a data warehouse for enterprise-wide reporting using CI/CD

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A new Data Warehouse (DWH) is required for future bank management. The implementation will use the technologies Exasol and Tableau, supplemented by Jenkins and Docker for Continuous Integration (CI) and Continuous Delivery (CD).

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Use Case

Implementation of Planning Analytics and Tableau Self-Service

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Instead of time-consuming planning in Excel, both central departments and business units should be able to quickly and independently create analyses of the business plan and business performance in the future...

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Use Case

Implementation of an organisational concept and process model for a Data Science Lab

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The organisational structures and project processes of the existing BI Competence Center conflict with the requirements of Data Science projects.

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Use Case

Concept and implementation of a hybrid Big Data & BI architecture

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The analytical architecture landscape has reached the end of its lifecycle after 15 years of use.

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Use Case

Sales planning and forecasting with predictive planning

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Long production times (at least 9 months) require very accurate forecasting and planning of delivery quantities to avoid shortages.

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Use Case

Introduction of cost planning for development costs

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The planning of approximately 8,000 development projects is carried out in various Excel-based applications.

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Use Case

Sales planning and production planning

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Sales planning is carried out using Excel (across more than 20 workbooks).

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Use Case

Maintenance and operations of management information systems

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Expiry of the existing contracts for maintenance and operations for the applications of the automotive bank.

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Use Case

Real-time streaming of Teleloq vehicle data with Kafka and Storm

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Functional improvements are to be achieved for each market and vehicle model.

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Use Case

Setting up an HDP DEV Cluster - operation and onboarding of use cases

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Hadoop development clusters distributed across multiple business areas.

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Use Case

AfterSales potential and information system

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The profit share in the After Sales segment for automotive manufacturers is over 50%. Therefore, the potential in the After Sales area should be better utilised.

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Use Case

Achieving service goals through process implementation

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No transparency regarding the services provided by the Competence Center in the SAP BI Shared Service area.

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Use Case

Concept for establishing a BI Competence Center

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High coordination effort, long project start-up times, lack of technical expertise, and support quality.

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Use Case

Data warehouse system landscape using the Data Vault approach

Ausgangssituation

A regulatory authority with over ~400 insurance companies requires an information system with:

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Use Case

Building a Self-Service Analytics Platform with Tableau

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Complex requirements for data visualization cannot be implemented with the existing BI tools.

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Use Case

Building a Self-Service Analytics Platform with Tableau

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The existing BI tool cannot meet the complex requirements for data visualisation.

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Use Case

Introduction of the Notation Concept according to IBCS® for Status Presentations

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Preparing the weekly and monthly reports takes approximately 2 days each.

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Use Case

IBM Cognos Mobile Reporting for Sales

Ausgangssituation

The field sales representatives are often on the road and at customer sites. During this time, direct access to sales analytics is not possible.

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Use Case

Implementation of use cases with Microsoft HDInsight and Azure

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The department has no way to analyse data across applications.

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Use Case

KPI - Dashboard zur Unternehmenssteuerung

Ausgangssituation

Der Kunde nutzt unterschiedliche Software Systeme zur Analyse seiner wichtigsten Unternehmens-Kennzahlen. Dies führte zu zeitaufwendigen Analysen

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Use Case

Building a Big Data Platform with Fraud Detection

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There are no self-learning fraud detection mechanisms that examine transaction data for fraud patterns in real-time.

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Use Case

Building a Big Data Platform for the Corporation

Ausgangssituation

In order to offer and implement Big Data projects within the Group in a professional service environment in the future, a Big Data Service and Operations Platform should be created for two components: IBM SPSS and Hadoop 2.1

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Use Case

Building a BI Solution - Talent Management System International

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The qualification of potential touchpoints, customers, and prospects is not optimally established to manage and monitor the services offered in the retail channels.

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Use Case