top of page


challenges & opportunities.

Humans continuously strive for improvement and optimization.
Data and new technological approaches such as artificial intelligence (AI) and machine learning (ML) can help here.

Data is often initially unstructured and can only be stored, viewed and deleted. Only (algorithmic) processing ensures that useful information can be extracted from it. This is where the technology of machine learning or artificial intelligence comes into play.

Data model / modeling

Data alone is not of decisive value. Linking data, especially contextually, creates added value. It is important to develop a proper understanding of the data in order to find and link the relevant data (information) in the multitude of data in the different systems and technologies. A clean data model forms the basis for interactions between humans and technology as well as for information retrieval.

Data management

Complementing the data model is the need for an effective strategy, governance and data management model. The goal of data management is to ensure that data is accurate, consistent, available, secure, and accessible to those who need it. It encompasses various aspects to organize, store, analyze and protect data in an organization or business.

Process integration

In data management, process integration refers to connecting different business processes and activities in an organization as integrated as possible using data. It aims to improve efficiency, consistency, and collaboration between different processes by sharing and using data in a coherent and synchronized manner. In process terms, data management encompasses the collection, harmonization, organization, and access to data. Based on data models, technologies and architectural approaches such as database, data warehouse, data lake, data hub, etc. are used for this purpose. These technologies support in particular the challenges in the area of data collection, data preparation & data processing, data storage, data provision and data presentation. The decisive factor is which goals and use cases are to be achieved or addressed on the basis of the data.

Data strategy

Such a strategy focuses on controlling, organizing and directing the handling of data. It defines the goals, principles, guidelines and measures. In essence, it is about how data is to be collected, managed, used, protected and optimized in the organization. Focus topics are, for example, the IT system landscape (software portfolio), the data architecture including modeling and development guidelines, role concepts, and finally the definition of an associated organization including responsibilities, with the goal of developing data governance.

Tax relevant data

Managing tax-related data can be a challenge for many companies, especially when it comes to compliance with regulations (e.g. DSGVO) and the submission of reports. But with the right tax data management, companies can not only save time and resources, but also improve their efficiency and overview. With our colleagues, the tax experts, we refine the data management to a tax data management.


Effective data management enables companies to provide transparent information about their sustainability and ESG performance. This strengthens the trust of investors, customers and stakeholders. The quality and consistency of sustainability data is critical. Collecting and validating this data can be complex, especially when it comes from different sources (environmental, social and governance). Well-managed sustainability data provides companies with a solid foundation for data-driven decision making and required reporting compliance (CSRD).

Your contact persons

  • LinkedIn
Martin Krejci

Martin Krejci

Anker Datenmanagement

Companies can make the most of their data by combining data management and business intelligence to gain competitive advantage, optimize business processes, meet customer needs and drive innovation. Good data management ensures that data is reliable, consistent, up-to-date and accessible. The use of business intelligence enables data to be visualized, modeled, interpreted and communicated.

Combining data is critical to:
- Gain (new) information 
- Support decision making or underpin decisions (and document them)
- Develop new (digital) business models

our consulting. 

We combine many years of experience in handling data, reporting and analysis (data warehouse and business intelligence) in the context of general data management. 


In order to make data easily accessible to the user and integrated into business processes, we also design and implement data-driven and process-oriented innovative software solutions.


It does not matter whether it is purely (fiscal) data management or the implementation of reporting, analysis to extensive process and data driven solutions. In addition, we also offer small digital helpers that can greatly facilitate and optimize everyday work. The focus is on the (business) user, who should be supported in his daily work in the best possible way.


The targeted advancement of digitization enables the business user to focus on his or her tasks as much as possible, instead of having to deal with the tedious collection and processing of data.



1. analysis and identification of needs:

We start with a thorough analysis of your current (tax) processes, challenges and goals. This helps us to identify the existing and needed data / points.


2. individual strategy development:

Based on the analysis, we develop an individual data strategy tailored to your (fiscal) needs and goals. This strategy forms the framework for the further steps of our consulting.


3. technology integration:

In coordination with your internal IT and your company's IT strategy, we create an appropriate solution architecture that optimizes your (tax) processes, takes data requirements into account to open up new opportunities.


4. customized solutions:

Our experts develop customized solutions tailored to your specific needs. These solutions can range from the creation of data models to the development of individual solutions and the automation of processes.


5. support during implementation:

We accompany you during the implementation of the developed solutions, ensure that they are seamlessly integrated into existing processes, and provide support in the event of challenges that arise.


6. change management and training:

The success of change often lies in the successful management of change processes. We help communicate and implement the changes in the business and train teams accordingly.


7. Sustainable partnership:

Our approach aims to build long-term partnerships. We understand that continuous change and development in the specialist area makes long-term support possible. 


Our strength lies in not only identifying problems, but also developing and implementing innovative solutions that create sustainable added value for your department (e.g. the tax function). Our consulting approach is designed to optimize your (tax) processes, increase efficiency and improve the ability to make data-based decisions - all with the goal of making your departments fit for the future.


We at greenfield are happy to support you in all questions and topics related to (tax) data management. Feel free to contact us. 

fields of play. 


Databank (DB)The database is the central component in data management. It is where data is stored and subsequently made available. Depending on the requirements, different databases and data models are used (relational and non-relational databases)

Data Warehouse

Data Warehouse (DWH) Database for storing large amounts of data (structured, current and historical) from different sources, these are harmonized and interconnected. Use case or subject related and specific data is often provided as a data mart. Goal: - Business Intelligence (BI) support, - reporting and analysis, and - regulatory requirements


Data LakeData storage for structured and unstructured data. Preferably used for heterogeneous and extensive data volumes. Depending on the data source, the stored data can be available in different processing steps, e.g. in raw format or in already (partially) processed form.

Data Hub The "data hub" of the company. A large number of different data sources are connected and made available in a data hub. Supplemented with a "Data Catalog / Dictionary" such as the Azure Data Catalog, a 360° view of the data and existing interfaces is made possible. Enrichment with metadata leads to a simpler and better understanding of the data points.

Data Hub

Business Intelligence (BI), Reporting, Data Analysis The difference in terminology/disciplines lies in the type of question being answered. BI focuses on descriptive analysis that summarizes historical and current data to show what has happened or is happening. (combines Reporting and Analysis) Reporting is a part of BI that presents data in a formatted and easy-to-understand way, such as tables, charts, or dashboards. Reporting is divided into standard and ad-hoc reporting. Standard reporting refers to reports with a defined structure, a uniform layout. Ad-hoc reporting refers to reports that can be generated or customized by end users themselves to answer their own questions. Data Analysis deals with the analysis of existing data with the goal of gaining information in order to draw conclusions that support decision-making. This includes, for example, the identification of causes, trends or anomalies (retrospective).

Data Analysis

Data and Process-Driven SolutionsWe attach great importance to our solutions being "data driven". This ensures that they are very flexible and easy to use and can adapt automatically to changes, at least within a certain framework. In order to be able to integrate workflows, it is advisable to map them using Business Process Modeling (BPMN) in order to achieve the highest possible degree of technical abstraction. In addition, BPMN offers the advantage of integrating decision trees using the Decision Model Notion (DMN). The goal is to create a solution that is as flexible and integrated as possible, which can be adapted by the user to his needs. Customization of a solution should follow the approach 1. configure (business user) 2. customize (power user) 3. develop (IT-Pro. / Developer)

Do something great

Tax Technology In particular in the tax function of companies, the demands for data and information are constantly increasing. Faster, more and more detailed tax-relevant business data is to be made available. To cope with this, Tax Technology solutions are used to enable companies to meet these requirements. In combination with our tax experts, we develop innovative tax technology solutions.

Tax Time Wecker

contact greenfield

Fill out the form to schedule a 30 minute initial consultation with our data management experts.

Thank you for your interest, we will be in touch!

bottom of page