Increase the data quality of your data effectively and sustainably

Data Quality

Data quality is an increasingly important component of business success. After all, what modern business process can function without data?

Companies make their most important decisions based on their data-driven insights. But the quality of the insights you gain from your data depends on the data itself. Data quality is therefore a basic prerequisite for effective implementation, so that your future decisions are based on resilient and sound facts and not on your gut feeling or intuition.

However, optimizing data quality is not an ad hoc activity, but a dynamic and continuous development with sustainability that takes place throughout the entire company at all levels. That is the only way to achieve the overarching goal: to preserve the meaningfulness of the data and its value.

Datenqualität Dienstleistungen

However, optimizing data quality is not an ad hoc activity, but a dynamic and continuous development with sustainability that takes place throughout the entire company at all levels. That is the only way to achieve the overarching goal: to preserve the meaningfulness of the data and its value.


Better decisions

To ensure that the right, unambiguous information is available at the right time in the appropriate form and granularity, and to improve the operational and strategic basis for decision-making.

Increasing customer satisfaction

Improve customer relationships and reduce business risks.

Reduce costs

Reduction of time and costs for data processing and avoidance or minimization of manual correction of erroneous data.

Regulatory and legal requirements

Simplified provision of the data required for this within the framework of the obligation to provide evidence.

your entrance

Our data quality products

Our data quality management model TIQ Cube represents the strategic framework of our coaching and consulting services on which we base our approach in projects. TIQ Cube combines our many years of project experience with established process models and special maturity models. In TIQ Cube, operational and strategic aspects are related to each other and developed into a dynamic concept. In addition, all relevant stakeholders of data quality management are adequately considered within the scope of their specific relevance and requirements. The interdependence of these levels thus enables a holistic view of data quality management in connection with short-, medium- and long-term perspectives.

Check and evaluate data quality

At the beginning of all activities in data quality management, problem analysis is the basis for identifying the causes of poor data quality. TIQ Assess is aimed at companies that are at the beginning of this major challenge and want to obtain a systematic overview of the quality in a meaningful section of their data world.

On the one hand, TIQ Assess sees itself as a quantitatively oriented, software-supported, interactive and intuitive analysis tool for data quality testing and data quality assessment. On the other hand, qualitative methods of problem identification are integrated via workshops and expert interviews. In doing so, the associated problem areas are identified very quickly and systematically.

This creates the basis for initiating a data quality project. The identified problem areas can now be structured, quick-win opportunities prioritized and the first steps towards establishing sustainable data quality management in your company defined.

Entry into data quality management

TIQ Sense is aimed at anyone who is just discovering data quality and the associated challenges for themselves and is looking for a practical approach to raising awareness among management and employees. Using industry-specific examples, the risks of neglect are highlighted, as are the enormous opportunities that lie in establishing sustainable data quality management.

In addition, methods and approaches on a strategic, tactical and operational level will be highlighted and discussed as a basis for your company’s entry into the world of data quality management. Based on this, qualification seminars can be defined and conducted depending on the data quality awareness and the respective responsibility or work environment.

The methodological framework of TIQ Sense is flexible. Depending on situational requirements, various options are available to raise awareness of the topic: Lectures, workshops, data quality simulation, seminars and questionnaires.

Keeping the target in sight!

A strategy is an essential component of successful data quality management. This is the only way to ensure the long-term development capability of data quality management. On the one hand, the entire company or division can orient itself to it and align its processes accordingly. On the other hand, a promising data quality strategy must be oriented to the concrete processes, organizational and IT structures as well as the cultural conditions of a company.

With TIQ Strategy, we offer you a strategy implementation process specifically for data quality management to meet precisely these challenges.

Think big – start small!

In practice, the development of a long-term data quality strategy and the introduction of data quality management itself are rarely initiated and implemented without preconditions. Rather, the players must win top management as the main sponsor as well as many other stakeholders over to their goals in the long term and need good arguments for this, including cost-benefit aspects. For this reason, a parallel approach is recommended in practice, in which clear proof of the benefits of data quality management is first provided on the basis of suitable quick wins, and initial activities are initiated in parallel to lay a strategic foundation for the establishment of a long-term, company-wide data quality organization.

Get fit for change!

Today, data quality management is discussed primarily from a technical and organizational perspective. Questions of corporate culture and the associated change management rarely play a role. In this context, data quality management runs the risk of being interpreted too mechanistically and of being limited in its possibilities for a living and sustainable culture. Data quality culture refers to the basic attitude of employees towards data quality, which is realized in their daily behavior. Change management related to data quality is oriented around actions and goals to influence patterns of perception and behavior among employees and managers.

The foundations for the ability to change are laid through adequate communication, but also through appropriate awareness-raising and qualification measures. The basis for the willingness to change, on the other hand, must be developed through appropriate motivational work as well as organization-specific influence.

Putting people at the center!

Since data quality culture cannot simply be “organized”, we offer specific approaches to support your employees in positively accepting and approaching the necessary changes according to their respective data quality awareness. For this purpose, in addition to methods and checklists for situation analysis, a framework with various levers is available that can be influenced depending on the company situation.

We support you

Data quality management
adapted to your company

Are you looking for a holistic solution for enterprise-wide data quality management? We advise and coach you in the sustainable improvement of your data quality. Benefit from our many years of expert knowledge and field-tested approach in this area. We support you with:

  • workshops (awareness and analysis)
  • operational measurement/evaluation/improvement/monitoring of data quality
  • data profiling as quantitative data quality analysis
  • methodical support in IT projects
  • training and coaching of various target groups in methodologies/techniques; strategy solutions/data governance
  • change Management
TIQ Mitarbeiter Tobias

Tobias Schulze 
Senior Consultant BI

TIQ Solutions GmbH

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