Data governance consulting

Data governance consulting

Data governance is for every data-driven company essentialbecause it offers the Framework for data integrity, dataquality and data security. Furthermore ensures she compliance with rules and regulations, enables more transparency and contributes to a more efficient and effective use of data. This paves the way for advanced analytics, AI applications and ultimately better business results.

Data governance - solutions for your company

Generates Does your company continuously use valuable data, but encounter obstacles such as lack of data acceptance, unregulated availability or poor data quality in the practical implementation of data projects? Is data use inhibited by organisational obstacles and uncertainties? We accompany you on your way to a performant Data governance framework! We advise you on the assessment - the recording and evaluation of the status quo - as well as on the development of the framework. and implementation a data management system tailored to your needs governance. We help you align technology and processes by providing a comprehensive and holistic picture of your Data governance Draw structures.

Good Data governance offers numerous advantages:

  • N Improved data quality for more precise analyses
  • NIncreased efficiency and easier use of your data
  • NImproved compliance and data security
  • NMore accurate predictions and better decision making
  • NCompliance with a data standard throughout the company
  • NIdentify, understand and mitigate potential risks in their data management practices

Our data governance consulting

Data Governance Assessment & Data Maturity Assessment

Alexander Thamm GmbH delves into the core areas of your data governance: roles & responsibilities, policies & standards, and processes & procedures. Through our practice-oriented maturity model, we identify the current state and work closely with your employees to identify pain points and optimisation potential. This not only enables an in-depth assessment of your current positioning, but also a valuable industry comparison to derive targeted recommendations for action and deliver superior value to your business.

Data Governance Education & Training

In Data Governance Education & Training, we provide in-depth knowledge on the key aspects of effective data governance. Through practical training and education programmes, we strengthen your teams in the areas of roles & responsibilities, policies & standards, and processes & procedures. Our experts accompany you in anchoring a robust and future-oriented data governance structure in your company and thus ensure the quality and efficiency of your data projects.

Development of a data governance strategy

Under the guiding principle "Design - Enable - Implement - Live", we offer a systematic introduction to the sustainable establishment of data governance. In doing so, we design company-specific goals and an individual target picture for your customised data governance organisation. Step by step, we define the streams of action to develop a shared commitment to the elaboration and implementation of holistic data governance. Ultimately, through our holistic data governance consulting, we create a roadmap tailored to your business to effectively treat your data like a strategic asset. Unplanned use cases, misuse of technology and lack of accountability will soon be a thing of the past.

Creation of a Data Catalog

A structured data catalogue is the key to transparent and efficiently managed data resources. By creating a data catalogue, we create a central source of information for you in which all data resources and their relationships are systematically recorded. This not only enables quick access to relevant data, but also promotes its consistent use throughout the company. Our experts support you in eliminating ambiguities in data origin and use and thus strengthen the basis for data-driven decisions.

Implementation of data governance

When implementing data governance, Alexander Thamm GmbH follows the previously developed roadmap by practically implementing and testing initial use cases. In doing so, we take into account individual factors of your company, especially with regard to the structural set-up of organisational units, entities and roles, including tasks, responsibilities and competences. We support the concrete design of the mandating process and guide the role holders in the execution of their function. Together we accompany the successive roll-out of the individual steps and identify further requirements for guidelines, standards and process tools. The result is the core for a company-wide implementation of pragmatic data governance.

Your data governance experts

Ursula Besbak, Data Strategist, Alexander Thamm GmbH

Ursula Besbak

Data Strategist | Alexander Thamm GmbH

José Manuel Berutich Lindquist, Data Scientist, Alexander Thamm GmbH

Dr Carsten Dittmar

Partner and Area Director West | Alexander Thamm GmbH

Sarah Lallié, Data Strategist, Alexander Thamm GmbH

Sarah Lallié

Data Strategist | Alexander Thamm GmbH

Customer references

Data Goverance Operating Model at an automobile club, a circus clown in a ring

Data Governance Operating Model

for a traffic club

Data sharing in the aviation industry, a collection of hot air balloons in a vast foothills landscape

Data sharing

for an aviation company

Creation of a Collibra Data Catalogue, a figure made of tropical fruit sitting reading a catalogue

Data Catalog

for a trading company

Designing a data governance framework, an angler on a calm lake to the setting sun

Data Governance Framework

for a reinsurer

Our methodology: the [at] Data Journey

Today, much of the business value is based on the analysis of data. The crucial question is how do we generate value from data to turn problems into concrete solutions?

With the Data Journey we have developed a holistic system for Data & AI projects, with which we can determine the starting position and Taking a holistic view of our customers' problemsin order to be able to offer them the best possible advice and the best possible solutions:

From comprehensive consulting and development of a data strategy, through proof of concept and prototypes, to the finished product and subsequent continuous maintenance and optimisation.

[Data Journey by Alexander Thamm GmbH, Data Strategy, Data Lab, Data Factory and DataOps in a Flowchart

Further services

Data Science Consulting

Use the potential of your data. We support you in your AI and data analytics projects.
Learn more

Data strategy consulting

Independent advice and development of your data strategy: We promote a living "data culture" for your company's success.
Learn more

MLOps Consulting & Services

Monitor and optimise your machine learning products. We advise you on the operational use of MLOps.
Learn more

NLP Consulting & Services

Advice on the use of language models to make efficient use of your company's knowledge.
Learn more

Keynote speaker

Our experienced keynote speakers offer you in-depth expertise and practical business insights.
Learn more

Generative AI Workshops

Develop a competitive strategy and implement it with our support.
Learn more

Resources

Informative blog content, inspiring webinars, entertaining videos and engaging podcasts: valuable subject content for further in-depth study.

Sales forecasts with AI

Sales forecasts with AI

A step ahead of the competition

Forecast models point to the future

Looking into the future with forecasting models

Basic contribution

Data visualisations

How to deal with missing values

Tech Deep Dive

Data Science Consulting

AI and Data Science Consulting

As a data science consulting company, we support you in your data journey. Benefit from our data consulting experience from over 1,000 AI & data projects with more than 100 customers in various industries - including numerous DAX companies.

Consulting services

We help you plan and implement your data strategy and set up a data department with all the necessary processes. We also work with you to identify the greatest potential in your company and get the most out of your data.

Data Audit

Together with you, we review your current data and identify potential and opportunities.

Data Roles & Skills

We help you identify the right people with the right skills for your data project. 

Workshops

Workshops help you to find a strategy, develop a use case or work on a specific use case. Together we will find the right format for you.

Technologies

Thanks to our many years of experience, we can optimally support you in the selection of the right tools and software.

Digital transformation starts with the data strategy

 

Data is the fuel for digitalisation. Only those companies that are able to generate real benefits from data will be successful in the future. Don't make the same mistakes that others have already made, but use our tried and tested approach and learn from our experienced experts. We combine the best of strategy consulting, thought leadership and extensive project experience - developed and proven in perhaps the toughest market in the world in terms of data protection and customer scepticism.

WHAT DOES A CONSULTING PROJECT WITH [at] LOOK LIKE?

Initial situation

Many companies face the challenge of building, developing or optimising AI & Data Science capabilities within the organisation. In the end, the goal is always to generate a better return on investment. Often, companies do not know who to look to for guidance in their industry, what trends to expect and what the best practices are in terms of organisational form, technology and processes. We support you in clarifying these open questions and help you to master all challenges in the field of data and AI.

Project procedure

To start with your data strategy, we first carry out a site assessment. Our assessment workshop has proven its worth for this purpose. In this workshop, you will learn about the strategically important components of a data strategy. In addition, we assess your status quo together and benchmark your current data strategy. Big DataAI and analytics capabilities. To develop your vision for a data-driven enterprise and the corresponding data roadmap, we work with design thinking methods. We then define the 5 pillars of your data operating model together: organisational structure, processes, roles, data governance and IT system landscape. We help you with change management in your company. We also conduct individual coaching sessions for the management or project team while supporting you in the continuous improvement of your project portfolio.

Data Science Use Cases

Insurance Automotive Logistics Energy Trade & E-Commerce

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Overview of methods used

Assessment Workshop

Design Thinking

Individual coaching

The Assessment Workshop

You don't know yet how to implement your data strategy in your company? With the Data Strategy, you will receive an introduction to the 5 most important elements from our experts and present best practices. Afterwards, the current status and the target picture for the 5 dimensions are assessed. The dimensions include, organisational structure, processes & use case pipeline, roles, Data governance and IT system landscape. This makes it possible concrete recommendations for action for you and to develop an individual data strategy.

References

from [at]

AI & DATA SCIENCE CONSULTING

What makes [at] stand out

Leader for
AI and Big Data

We have been recognised as a #1 Value Creator in Machine Learning by CRISP Research and as a Big Data Leader in Germany by experts.

Sector-specific
Know-how

We have completed over 1,000 AI & Data Science projects in over 15 different industries.

Technology-independent
Consulting

We find the right technology for our customers depending on their needs and support them in the implementation.

Data projects implemented

Use cases identified

AI and Data Experts

Years of experience

FAQ

Empty

blank

What is a data strategy?

A data strategy is the definition of the long-term goals for the value-added contribution of asset data in organisations as well as the activities and resources required for this. The data strategy thus defines the master plan for creating added value through data in organisations and is thus a core component of the overarching digitalisation strategy.

A data strategy must provide an aligned response to all design objects. The sub-strategies are integrated into an overall programme for transformation into a data-driven organisation.

Can you guarantee us a Rol?

In order to be able to generate added value from data, it is essential that we work together with the client to calculate a business case for each project and to be able to check this measurably during the project. However, due to the innovative nature of many of our projects, this is not always possible - so in such cases we have to work with assumptions. A Rol guarantee is not possible due to the innovative nature of the project.

Can we develop individual training?

[at] already offers standardised Data Science Trainings on various topics. We are also happy to develop individual solutions. We are happy to adapt these to the technologies you already use.

What skills do your advisors have?

Our data and AI experts have a wide range of knowledge and skills. Professional backgrounds include:

  • Mathematics 16 %
  • BWL & VWL 14 %
  • AI, Big Data & Data Science 6 %
  • Engineering 14 %
  • Physics 9 %
  • Computer Science 41 %

Do you only advise or do you also take over the implementation and realisation of this?

With the help of our Data Journey we accompany you from your first idea to the finished data product.

Do you also provide non-binding cost estimates?

We will be happy to provide you with a non-binding cost estimate for your project after an initial discussion. 

What is the Data Journey?

With the data journey, we accompany you from the first idea to the finished data product. With the help of this framework, projects can be classified at any time according to the maturity of the data products and the subsequent phase can be planned. This enables us to generate real added value from data projects across the board.

Who do I approach with a specific project enquiry? What is the bidding process here?

For an initial exchange on your request, please contact our Head of New Business Simon Decker!
He will be very happy to help you with your concerns and will call in the appropriate experts depending on the areas in which your challenges are to be located.

Request here

We still need expertise in one of our ongoing projects. Can I book individual profiles in the course of this?

We would also be happy to send you profiles to match your enquiry. 

Does [at] offer teams or is there the possibility for single sourcing?

Our experience has shown that we can best react to the (sometimes unplanned) requirements in the project if we support you as a team. Depending on the issue, it usually requires more than one person.  In cases where the requirements are very clear, we can also plan with fixed project staff.

Data & AI Knowledge

Creating added value from data & AI together

Blog

Discover professional articles on Data & AI as well as the latest industry news.

Webinars

Best Practices and Industry Exchanges - Watch Live or On Demand.

Whitepaper

Learn more about the use of Data & AI in your industry and department.

Data Strategy Consulting and Development

Data Strategy Consulting & Development

In the age of AI, a well-considered and effective business data strategy is crucial to remain competitive. It is the foundation for the successful Implementation any data projects and creates a holistic target picture. All too often, however, a comprehensive data strategy is missing or only exists in the broad outlines. We develop together with you to develop a data strategy that fits in with your strategic company-targets - from the data basis and data governance to use cases, organisation, architecture and roadmaps. 

Data strategy consulting for your company

Your data strategy didn't work out, the results remained below your expectations or you don't have a well-defined data strategy for your company yet? Then we should talk! At Alexander Thamm GmbH, we provide you with independent and technology-agnostic advice. We always think of strategy holistically, because even the best strategy can fail if people are not involved. We therefore attach great importance to the participation of employees - in the sense of a living "data culture" - and involve all relevant stakeholders in your data strategy development from day one.

The development of a sustainable and future-proof business data strategy offers numerous advantages:

  • NBetter scalability of data products and projects
  • NClear goals and defined roadmaps
  • NCompetitiveness in the dynamic AI era
  • NStrengthening the commitment of employees (support in change management)
  • NCreation of transparent processes and structures (data governance)

Our Data Strategy Services

Development of a data strategy

Looking for a well thought-out, goal-oriented data strategy that seamlessly integrates data collection, data quality, data management, data protection and data analysis? At Alexander Thamm GmbH, we design a comprehensive data strategy for your company that is tailored to your specific needs.

Data Strategy Assessment

Our Data Strategy Assessment provides an in-depth analysis of your current data landscape, identifies strengths and potentials and offers concrete recommendations for action to optimise your data-driven processes and ensure the success of your data strategy.

Your experts

Ursula Besbak, Data Strategist, Alexander Thamm GmbH

Ursula Besbak

Data Strategist | Alexander Thamm GmbH

Dr Carsten Dittmar, Partner and Area Director West, Alexander Thamm GmbH

Dr Carsten Dittmar

Partner and Area Director West | Alexander Thamm GmbH

Florian Harsch, Data Strategist, Alexander Thamm GmbH

Florian Harsch

Data Strategist | Alexander Thamm GmbH

Customer references

Data strategy for a mobility worker, an orange chess piece on a board

Data strategy development

for a mobility provider

Great Lakes in Data Analytics for a reinsurer, two hands touching each other in an elegy of depth and dream

Data Analytics

for a reinsurer

Data Strategy Workshop for a car company, a sculpture course in a studio with a vintage car

Data Strategy Workshop

for an automotive group

Data Mesh for an industrial company, a fisherman in his dinghy, catching fish with a net

Conceptual design of a data mesh

for an industrial company

Our methodology: the [at] Data Journey

Today, much of the business value is based on the analysis of data. The crucial question is how do we generate value from data to turn problems into concrete solutions?

With the Data Journey we have developed a holistic system for Data & AI projects, with which we can determine the starting position and Taking a holistic view of our customers' problemsin order to be able to offer them the best possible advice and the best possible solutions:

From comprehensive consulting and development of a data strategy, through proof of concept and prototypes, to the finished product and subsequent continuous maintenance and optimisation.

[Data Journey by Alexander Thamm GmbH, Data Strategy, Data Lab, Data Factory and DataOps in a Flowchart

Further services

Data Science Consulting

Use the potential of your data. We support you in your AI and data analytics projects.
Learn more

Data Engineering Consulting

Gain valuable insights from your company's data infrastructure.
Learn more

MLOps Consulting & Services

Monitor and optimise your machine learning products. We advise you on the operational use of MLOps.
Learn more

Data Science Academy

Learn from experienced data scientists and acquire practical know-how to generate added value from your data.
Learn more

Keynote speaker

Our experienced keynote speakers offer you in-depth expertise and practical business insights.
Learn more

Generative AI Workshops

Develop a competitive strategy and implement it with our support.
Learn more

Resources

Informative blog content, inspiring webinars, entertaining videos and engaging podcasts: valuable subject content for further in-depth study.

Smart Factory in Industry 4.0

Smart Factory

How the right data strategy makes the production environment a success

Top Ten Data Strategy

Building blocks of a data strategy

Top 10

Data Mesh vs Data Fabric, a humanoid robot in a white robe, in Elegy, wrapped in an orange robe, Alexander Thamm GmbH Blog

Data Mesh vs. Data Fabric

Comparison of data management concepts

Predictive Maintenance Service

PREDICTIVE MAINTENANCE WITH [at]

In the past, maintenance was always carried out according to fixed, predefined intervals. Today, you can realise predictive maintenance scenarios with the help of AI models. These models can compare current sensor data with historical data and thus recognise unusual behaviour patterns in components of a machine that would otherwise remain hidden. In this way, measures can be taken at an early stage to prevent a downward trend in product quality, a deterioration or even a failure of the machine.

Our predictive maintenance approach

Even though some companies suggest that they can offer predictive maintenance as a ready-made software solution, the reality is often different. Predictive maintenance using AI is an automation task that requires a fundamental understanding of the process and the data generated from it, and thus usually requires an individual solution. In order to deal with the very heterogeneous circumstances at our customers, we have developed a 4-stage maturity model. This helps to better understand the status quo and enables a joint iterative approach.

1.

State-
monitoring

In the classic understanding of pure condition monitoring, AI does not yet play a role at this point. The focus here is on the Display of sensor data in the form of dashboards.

However, it is possible that domain-specific logic for call-to-action is integrated, such as an alarm when threshold values are exceeded.

2.

Anomaly-
recognition

Machine learning methods are then used to detect changes in the data patterns. The aim is to identify changes that indicate potential damage so that Repairs can be carried out before a breakdown occurs.

At this level, the aim is not to predict when the failure will occur, but to detect anomalies in order to carry out maintenance steps close to the potentially imminent failure.

s

3.

Extension of the fault diagnosis

This stage extends the pure anomaly detection to the point of Fault diagnosis. After the onset of the ageing process has been detected by machine learning algorithms, the diagnostic component is triggered.

This component is intended to Fast and targeted maintenance by using Explainable AI to localise the cause.

4.

Prediction of the residual utilisation
duration

At the highest level of maturity, the pure detection of the ageing process around the Prediction of the expected process behaviour expanded.

The problem to be solved is now no longer a classification problem (machine state is ok / not ok), but a regression problem with the prediction of the time of machine failure. With this level of knowledge, the Choice of the timing of the maintenance be done in the best possible way.

4 Success factors for
Predictive Maintenance Projects

Predictive maintenance is inconceivable without comprehensive data. However, data can vary greatly in terms of quality and level of detail. This has a major impact on the development of AI models, as they can only achieve good results if the data contain a large amount of information.
For production machines, the data is often available in different levels of detail:

  • Raw data
  • Event-based data
  • High-level information
  • High-level actions

For the development of AI models, it makes a big difference whether only error codes or the raw data from the sensors are available. A common problem is often the lack of important contextual information. Different batches with 2 kg and 2.5 kg workpiece weights have different effects on the sensor data and must be taken into account so that these differences are not wrongly classified as an anomaly.

A smooth flow of data processing and the use of trained AI models for maintenance optimisation is only possible through an orchestrated interaction of several systems. Here is a brief overview of the different components needed for an infrastructure:

  • A connectware to connect sensors or machines from different manufacturers to a uniform system
  • Scalable data storage and a Big Data processing engine to handle streaming data (if real-time data is required)
  • Computing resources and environments for training AI models
  • Services to communicate the predictions of the AI models to the end user

A common problem in the area of predictive maintenance is the large number of sensor manufacturers with different protocols for transmitting data. Together with our partner Cybus, who specialises in the area of Connectware, we can overcome this challenge.

A deep understanding of the basics of machine learning is something every Data Scientist should know. What are the important assumptions of an algorithm? How can you avoid the pitfalls of information leakage when training?

In addition to the correct selection of algorithms, however, the art usually lies in correctly formulating the automation task as a machine learning problem. This is especially true in the field of predictive maintenance. The fundamental problem of anomaly detection is the lack of a definition of how different a novelty must be before classifying it as abnormal. Marked data for training models is often not available to this context.

Either it is not possible to observe normal and abnormal behaviour in all possible ways, or it is too expensive to obtain specific labels.
Thanks to the numerous projects we have carried out in the field of predictive maintenance, we can provide optimum support for your project with a wealth of experience.

User-centricity is important for all products with an AI component. Black-box solutions are often built that are not trusted in daily use.

Human in the loop is the central approach here. In a dashboard for the worker at the machine or in the process control centre, it must be recognisable why certain forecasts or anomaly detections were made. When we implement AI technology for our customers, existing processes and ways of working are always changed, so change management plays an important role in the success of the project.

Our partners

aws logo
Microsoft Partner
Cybus Logo

Our Predictive Maintenance Experts

Projects of our customers

Since 2012, we have successfully implemented numerous predictive maintenance projects. Learn more about some of our customer projects on the topic of AI in the manufacturing industry here.

Any questions?

You want to know how AI and Data Science can reduce maintenance costs and machine downtime in your production, but you still have many questions:

 

  • For which machines does a predictive maintenance approach using AI make sense?
  • What framework conditions must be in place to ensure that anomaly detections are also used to create concrete added value in production?
  • Is the data stored so far sufficient for training AI models?
  • Which features can be taken into account in addition to the sensor data?
  • How do I integrate different production machines into the company-wide Big Data infrastructure?

Then talk to our experts and get an initial assessment of your project plan!

    Talk to us

    Simon Decker

    Simon Decker

    Predictive Maintenance Projects

    Data Science Workshops

    AI and Data Science Workshops

    If you are still at the beginning of your data journey, [at]'s AI and data science workshops give you the opportunity to make a big impact without a big investment. Whether virtually or on-site, you can quickly see what is possible in your company to gain real added value from data.

    The starting signal for the concrete project

    In the course of digitalisation, innovation methods such as Design Thinking and Business Model Canvas are also spreading in traditional companies. Global players have adopted approaches such as Lean Startup or Agile Working from start-ups. Digital business models should be thought of and implemented from the customer's perspective. This usually contradicts the organisational structure of traditional companies. Here, the product is still at the centre of the processes. Therefore, data and data competences are usually distributed and found in silos. But where do you start with the topics of (Big) Data and Artificial intelligence? Where do the potentials in the data lie for you and your company personally?

    We support you in this with our AI and Data Science Workshops.

    Learning from each other
    You need to bring different stakeholders together internally and benefit from the knowledge of your colleagues. Our AI and Data Science Workshops are the best format for this. What's more, you and your colleagues will learn more from us in one day than in almost any other format. We share our experience from over 1,000 AI and Data Science Projects from a wide range of industries and present selected best practices for your company.

    Overview AI and Data Science Workshops

    Z

    Assessment Workshop

    Are you wondering how to set up and implement the right data strategy in your company? We give you an introduction to the 5 core elements of a data strategy and present best practices. We then assess the status quo and the target picture for the 5 dimensions: Organisational Structure, Processes & Use Case Pipeline, Roles, Data Governance and IT System Landscape. The assessment of the status quo and the target picture is then used to derive concrete recommendations for action (GAP analysis) and to develop the individual data strategy.

    Roadmap Workshop

    Do you have a data strategy and want to learn how to derive use cases from it? In our roadmap workshop, we start with a stimuli session in which we present relevant Data Science Use Cases Using design thinking and brainstorming methods, we identify suitable use cases and then prioritise them. The existing business questions are then translated into data-driven questions. We then evaluate the potential feasibility.

    Use Case Workshop

    You have a use case and want to find out how you can now get into the AI development? After presenting the status quo of the current use case, we use a design thinking session to generate hypotheses in a data science context. We then validate and check the necessary data to ensure the feasibility of the current use case. Finally, we develop an analytical concept for the use case.

    Virtual Use Case Quick Start

    The quick start for your first data science projects in just one day. Find suitable use cases in 4 hours with the right tool selection and benefit from our experience from over 1,000 projects.
    Price: 999 €

    Data Journey Kickstarter

    With this workshop you get the first prototype within one month. You start with your best use case for your department. For maximum success, we put together the best data science workshop formats for you. After the proof of concept, we develop your prototype.

      Not the right one for you?

      We also offer customised workshops for your team. Talk to our experts about this.

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      Data Science Use Cases

      Insurance Automotive Logistics Energy Trade & E-Commerce

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      Customer testimonial

      "The cooperation with Alexander Thamm GmbH was convincing with its very efficient and professional approach and was rated super positively by the 50 participants."

      Stefan Jaboci | Porsche AG

      Known from

      Why with Alexander Thamm GmbH

      Innovative workshop formats with high information density

      Benefit from the experience of over 1,000 data projects in various industries

      Experts with practical experience in data science, AI and machine learning

      Data & AI Knowledge

      Creating added value from data & AI together

      Blog

      Discover professional articles on Data & AI as well as the latest industry news.

      Webinars

      Dive into our Best Practices and Industry Exchanges. Discover new dates and recordings of past webinars.

      Whitepaper

      Learn more about the use of Data & AI in your industry with our white papers, case studies and research.