Busi­ness com­pu­ter science and da­ta an­a­ly­sis for audit pro­fes­sio­nals - A mean­ing­ful and fruit­ful syn­the­sis of the skills and ob­jec­tives.

In June 2014, the dab:Group had the privilege to celebrate its 10th anniversary. The company was founded as a Spin-Off of the Deggendorf Institute of Technology. The foundation of our motto “Changing data into Knowledge” was laid in the years 2002 and 2003 in the lecture “Finance & Controlling” which is given by Prof. Dr. Georg Herde. (the name changed to “IT-Compliance & Audit and Monitoring” these days). Already with the implementation of the degree program “Business informatics” several years ago Professor Herde pushed the topic of data analytics. With him as one of the early adaptors in that exciting area, I am very happy to have a guest column written by him.

Regularly our customers and business partners do ask the question, what the key skills are which they should foucs on when hiring data analytic junior staff, and which know-how prerequisites are needed. One of the best prerequisites from my viewpoint is a tertiary education with “Business informatics” as degree program. As this is an interdisciplinary degree which combines aspects of business economics with computer science symbiotically, it provides an ideal base for working in the area of (big) data analytics. You will find viewpoints like this and more in the following post, written by Prof. Herde.

Stefan Wenig, CEO dab:GmbH

Busi­ness com­pu­ter science and da­ta an­a­ly­sis for audit pro­fes­sio­nals - A mean­ing­ful and fruit­ful syn­the­sis of the skills and ob­jec­tives.

If you ask students about their idea of the degree program in business computer science (informatics), then you get diffuse and diverse opinions presented.

Ideas about websites and web shop design, app programming via the familiar company names which would recruit business computer scientists as well as Google, Microsoft and SAP to differentiated notions such as database applications, IT security and SAP consultancy are made.

All these ideas are not really incorrect, but they focus on characteristics of tasks and job profiles and touch only the border of the basic idea of this program.

Business computer science consists of two word constituents, namely business and computer science. In the program both areas are taken into account with the aim to train students so that they are well positioned at the interface between business issues and IT-based solutions. They should be able to understand the needs of the business and target to be able to use the tools of computer science to solve those problems.

Students can sign up at the Technische Hochschule Deggendorf (Deggendorfer Institute of Technology - DIT) to study business computer science since the winter semester of 1999. During the last 15 years, the course has undergone various changes. Formally, out of the diploma course evolved a Bachelor's degree program with the possibility of a supplementary master's program. The program content was gradually adapted to the technological changes and the needs of industry and the economy.

Currently the Bachelor student’s are offered three focus areas to briefly specialize in the higher semesters before graduating:

  1. Development of Business Prozesses
  2. IT-Security and IT-Controlling
  3. IT-Compliance & Audit and Monitoring

At last I would like to focus on one as an example to illustrate how the interaction between the business issue and IT solution can already be included in the training and educational process and what lessons should be taught to the students there.

The training at a university of applied sciences is already designed very practical conceptually. It is considered a unique feature that all university professors have to have several years of professional practice before they take the position at a university.

My professional experience is in the field of auditing and was the background motivation for me to incorporate this aspect in the teaching courses in the degree program of business computer science.

Auditors, accountants, internal auditors and auditor of the financial administrations are summarized below to the group of ‘audit professionals’ because all members of these professions have at least one element in common. They all should get into, with different weighting, within an economically justifiable time an overview of the business practices of a company, form an opinion on the legality, regularity and completeness of transactions form and give statements about the value of assets and debt levels, or whether the basis was for the taxation correctly determined.

This task is made more difficult by the fact that for decades operational transactions and business processes are mapped to IT systems, and the education of many members in the audit profession is more likely dominated by the legal and business side than the IT side which has a shadowy existence in their training and professional examinations.

This interface between the business requirements and the availability of the necessary information in IT systems represents to my respect a prime example of the scope of business informatics.

The above focus on "IT Compliance & Audit and Monitoring" takes into account this challenge in the education. The course will be conducted as a seminar and without going into the module description in detail, I will briefly outline the main features and for the students to be gained insights.


In a first step it is important for students to develop a self-chosen question that can be asked in the broadest sense in the context of an audit. The range of possible questions ranges from personal issues to the ERP system dominated tasks such as:

  • "Is the current telephone provider for the present (individual) phone usage behavior the cheapest alternative?"
  • "Does the compensation settlement of the electricity plant correspond with the estimations and records of the self-powered photovoltaic system at the beginning of utilization?"
  • "Are there any multiple master records regarding potentially identical customers or vendors in a Financial Accounting System?" or
  • "Are there any special features in the material master records (double master records, not maintained cost prices, ...) and the associated transaction data sets (no more movements since months ...)?"

In this context, it is important that students bring in their knowledge of compliance and data protection aspects of the issues. The selected question itself is fundamentally detached from the availability of appropriate data. The seminar practice shows, however, the questions are chosen to carry out the work to which they have also meaningful data. Experience has shown that identification with the task is higher when a correlation between the availability of data and the question exists.

Da­ta col­lec­tion

This step is not necessarily technical in nature. Here, students learn that the data collection may well have political, legal aspects of data protection and organizational aspects.

As long as the data can be obtained in the personal environment of the students, these aspects are not too pronounced but are discussed in their work. If real data from companies is available a very high sensitivity is required here. Privacy and confidentiality issues are to be considered at the highest degree.

The successful execution of the work does not depend on the specific individual records, possibly even artificial data can be generated with similar structure, but the quality of work depends on the ability of students to derive answers to the questions out of the data.

However, the technical aspect very often plays a non-negligible role and generates a lot of experience and activates knowledge by the students from previous semesters. In the 6th semester business computer science student’s can handle different data formats, information systems, databases and file formats. Many students experience that not every operational IT system makes its data available without "resistance". Different file and data formats generate some considerable demands to the student’s on the data extraction from the IT application systems.

Da­ta pro­ces­sing and in­ter­pre­ta­tion

In a further step, the students have to recycle the data for the forthcoming analysis. The choice of analysis tool is open to the students. They can perform their analysis with the help of database applications (SQL Server, MS Access, ...), spreadsheet tools (MS-Excel, ...) or dedicated audit tools such as ACL.

The choice of the analysis tool and the questions they want to analyze require very often a cleanup and transformation of data and the generation of additional fields in the extracted tables.

Missing items in fields must be completed or loaded with default values; date and time fields must be separated and prepared in analytically ready formats. Character fields in number fields and vice versa must be transformed and adjusted.

This step uses among others, the content of teaching and the skills of the students from the first semester of their studies.

In addition to the syntactic processing of the data, to focus on the targeted interpretation of the fields for a successful project is essential. This step runs through the entire project. Already in the phase of generation the question, students must elicit whether the data base also contains corresponding fields in the tables which are suitable to provide information for answering the questions.

This knowledge cannot be taught extensively, for each IT application system the students have to understand other mechanisms and program logics it holds for the project. In the business computer science degree program at the DIT students get insight into SAP in the first semester and are thus capable to assess a complex ERP system. The student must understand how the business processes are to be carried out and how these are reflected in the concrete application system. Based on this understanding, he is able to decide which of the tables and fields for his questions are the important and the right ones.

Trans­for­ma­tion of the ques­tion in­to an Al­go­rithm

The most important step in my respect is the ability of the students to transform the question asked at the beginning in a goal-oriented algorithm on the basis of the data available.

It is about the implementation into the analysis tool of choice. Which tables will be linked together with what fields in which way and in what sequences. How should they be sorted and/or classified thus allowing the so-generated part, section, and/or union set of records or generated key numbers to accurately determine possible statements concerning the question raised?

Another skill comes to the surface here. Are the student’s able to question and to perform plausibility checks and interpret logically on avoidable results?

What assumptions underlay the interpretation? Are the conclusions of the analysis in force on all occurrences or could there be exceptions?

The process of generating an algorithm is closely related to the ability of the interpretation of the possible outcomes. Is an 'inner join' or 'outer join' more appropriately, should the data first be filtered and then classified or vice versa. Many of these questions can be answered intuitively in a first approach, and are then adjusted in the course of the project and the results indicate an adjustment or change.

Important in this context is the finding that even a non-confirmation of the initial hypothesis or question may be a solution of the project. Frequently subjective expectations related to the question have a meaning that cannot be confirmed based on the results. It is also a result and an experience that the question just cannot be answered in full on the basis of existing data and the analysis carried out or a different result was obtained as expected.

Ad­di­tion­al as­pects

Many students recognize in the course, not through a lecture but through their own experiences in a project, the importance of data quality, data consistency and timeliness of data for a meaningful and goal-oriented analysis.

Data Warehouse and Big Data projects fail very often because of the absence of these conditions, and so the students gain experiences which are helpful not only directly for data analysis for the audit profession but also of general importance for other IT fields.

In times of "App's", "Google Glasses", "voice and gesture control" forces itself superficially the impression everything was working at the push of the button and a tender touch of a glass surface. Data analysis and not only this activity, requires a conscientious method, goal-oriented approach, careful handling of resources (data and working of the participants), a deeper understanding of processes and their mapping into the IT systems, the control of analysis tools and a responsible use of data and the interpretation of analysis results.

IT compliance & audit and monitoring gives the students an insight into the importance of the raw material data, the responsible use of this resource and the possibility of using data to generate added value for the companies and the audit profession.

Prof. Georg Herde


You can get more information about the Deggendorf Institute of Technology under https://www.th-deg.de/en. There are some more details about Prof. Herde, his publications and educational focuses.

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