These days, companies cannot avoid using analytical data to understand their business processes. Thus processes in general and relationships in detail can be better understood. The knowledge gained will help the company, for example to reduce risk, detect economic crime, or perhaps prevent both in advance. With data analysis, the data is structured in new ways by the targeted application techniques, ordered and displayed visually. A typical feature of data analysis is that it is built up in phases: The step by step findings based on consistent data support effective business decisions.

Data amoung
Data analysis

Lower risk, thanks to effective data analysis

These days, the intensive study of company-relevant data is particularly important for identifying and minimising business risks. However, the challenges facing the company in this are particularly large:

  • Already existing vast amounts of data

  • Increasing data flow and constant data growth

  • Growing challenges for multidimensional IT systems

  • Increasing data complexity and heterogeneity

Through the frequent accumulation of these factors, faster and more comprehensive insight into the company’s own data world is becoming increasingly difficult to achieve. In addition, susceptibility to errors and manipulations often grows in proportion to the increasing volume of data in all business processes. A basis for solving this problem is structuring, organising and consistent presentation of the data. These processes are part of data analysis and therefore part of a safety-oriented corporate solution.

Data analysis with modern technologies

Our solutions are based on solid Business Intelligence technologies such as Qlik and Jedox. These form the basis for robust and adaptable applications that enable a seamless integration of analysis, reporting and planning.

  • Technologien - Qlik
  • Technologien Jedox


Structured problem solving in five phases

Data analysis is based on a process-oriented structure and can be divided into five phases. Firstly, a problem must be identified and the objectives for data analysis are formulated in this context. Then problem solving is approached step by step:

  • Stage 1: Setting objectives

    • While taking stock, the problem is identified.
    • A problem-related objective is identified in a needs analysis.
    • Then questions are defined to solve the problem on the basis of the objective.
  • Stage 2: Data acquisition:

    • The systems supplying the data are defined.
    • The data relevant for data analysis are defined.
    • For this, the output formats are selected.
  • Stage 3: Data preparation

    • Insight into the existing data structures.
    • Generation of findings about data model and relations.
    • Taking into account of the particularities of different ERP systems.
  • Stage 4: Data evaluation

    • Grouping, sorting, compacting or filtering of the data.
    • Graphical representation of the data.
    • Making modes of effect and causal relationships recognisable.
  • Stage 5: Interpretation of results

    • Working on the basis of information obtained beforehand.
    • Formulating findings and deriving solution strategies.
    • Creating new knowledge for future data analysis.

Depending on the destination and the software used, data analysis can be applied, from ad hoc analyses to automated analyses.

Act in a business-safe manner, with data analysis

Efficient data analysis offers companies many advantages. Among other things, corporate data becomes more transparent, errors are exposed and manipulative treatments to avert damage are made possible. Selecting the right data analysis software is important for success, as is its effective and efficient application. With the advantages of using data analysis, companies can reduce their business and entrepreneurial risk.

High data quality

Informed decisions based on reliable data increase success in business operations.

Continual improvement

The exposure of safety vulnerabilities and weak spots helps to constantly optimise processes and controls in the business.

Legal clarity

As part of compliance, own data analysis is also legally relevant and provides security during internal controls or when auditing financial statements.

Total security

Automated full inspections by IT-supported data analysis offer continuous security against flukes in the audit.

Long-term viability

Thanks to continuous data analysis, business processes can be permanently improved and efficiency increased in the long term.

What our customers say about data analysis

When does data analysis make sense

  • When the quality of the data used in the company needs to be increased.

  • When it is necessary to detect and minimise possible vulnerabilities or errors in data traffic.

  • When consistent data for business decisions are desired.

  • When hitherto unfulfilled legal requirements are made on the data analysis in the company.

  • When particularly SMEs are looking for an effective solution to their risk management.

Our offer

We support discerning SME clients, using innovative business intelligence solutions, to find sound answers to business-related issues and so make the right decisions for safe and reliable company management.