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.
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:
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.
iVIEW: Our BI platform for data analysis
Conceived as «Individual Standard» platform, iVIEW can be implemented quickly and cost effective in an IT environment due to high standardization. iVIEW analyzes millions of data in seconds and reduces the complexity of data integration by 60%.
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.
The exposure of safety vulnerabilities and weak spots helps to constantly optimise processes and controls in the business.
As part of compliance, own data analysis is also legally relevant and provides security during internal controls or when auditing financial statements.
Automated full inspections by IT-supported data analysis offer continuous security against flukes in the audit.
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
"I’m delighted with QlikView," says Patrick Gruenig. "It was our goal to make data analyses more economical, more reliable and more freely available. We have definitely achieved this with QlikView. When preparing data, I just have to take care of the monthly accrual: all other data are supplied automatically. I save up to 70 percent of my workload each month. And employees can simply create their entirely individual analyses at the touch of a button. This straightforward application allows us to operate the system with virtually no external support."
– Patrick Gruenig, Head of Finance & Controlling, Lamprecht Transport AG