women computer tablet office

Data Analysis: AI as a Decisive Success Factor

published on 23.06.2021

These days, both private-sector companies and public administration institutions have a huge treasure trove of data at their disposal. When used strategically and in accordance with data protection law, they hold enormous potential. Artificial intelligence can become a decisive factor here.

Big Data: Clever Analysis Brings Competitive Advantages 

Collecting and managing data has long since ceased to be a nerve-racking chore for companies and public institutions. Not only does digitisation make it easier and faster to manage the information collected, but it can also be the basis for important decisions. Those who analyse, evaluate and use data correctly can gain enormous competitive advantages. With state-of-the-art methods, it is not only possible to process facts intelligently, but predictions of future trends can also be made. 

Before beginning any analysis, it is necessary to properly prepare the existing data. This requires taking an inventory: What data is available and what is their quality and quantity? And are the data even sufficient for an analysis? 

“Anyone who wants to use data in a useful way first needs to understand it correctly. For this reason, a good understanding of the particular organisation’s processes is an important prerequisite for the success of data analysis and AI projects.”

Alev Kuyas, data analysis and AI expert at Bundesdruckerei

It is therefore necessary to bring all data to a high qualitative and standardised level before starting the actual analysis. Data sets may need to be cleaned up or converted to make them optimally usable. Once this first step has been taken, a goal can be agreed upon. After all, only those who know the desired results of the data analysis will be able to choose the right method and technology for it.

How AI Gets the Best out of Data

Different technologies can be used for preparing and processing data. One of these is artificial intelligence. It is AI that makes it possible for data analysis to be automated. For example, if forms, applications or images need to be evaluated, AI can take over this time-consuming task. This relieves employees of a lot of work, thereby increasing the efficiency of processes – especially when massive amounts of unstructured data are involved. 

And there are other specific use cases where AI can play a key role as well:

Recognising and Understanding Complex Interrelationships

Many data sets are so huge that it would be almost impossible to comprehend and structure them manually. Artificial intelligence can remedy this by first collecting all the available data and then trying to identify patterns in the large quantities of information. AI can thus derive various correlations from the complex data streams, thereby providing information about target groups or markets, for example. In addition, artificial intelligence prepares the analysed data in a clear manner so that it can be further processed in the best possible way.

Warning Metrics Predict Crises Early

The best way to counteract an entrepreneurial crisis is to recognise it at an early stage when it is still possible to act. In practice, however, this is often a problem. When artificial intelligence is used to analyse data, it is capable of learning to recognise deviations in the existing data records at a very early stage and immediately sound the alarm in the event of anomalies. Crises can therefore be detected at an early stage, allowing countermeasures to be initiated quickly.

Predictive Analytics Provides Information about Trends and Developments

Data sets not only contain important information about the status quo – correctly analysing data also allows future events to be predicted. Predictive analytics detects trends in existing data and creates a mathematical model from it. This makes it possible to predict which developments can be expected with a high degree of probability. The staff are thus given an opportunity to take appropriate steps before an event occurs. Predictive analytics can be used in a wide variety of industries and markets, such as in the financial sector or the mobility sector. 

Using AI: Security the Top Priority

Regardless of the specific application, security needs to be the top priority when using artificial intelligence to analyse data. Personal information in particular is subject to the most stringent regulatory security and data protection requirements. Only those who consistently adhere to them can optimally use this innovative technology to meet their strategic goals.

“The trustworthiness of the AI used is essential. Other important factors are transparency, explainability and traceability when dealing with artificial intelligence.  

Alev Kuyas, data analysis and AI expert at Bundesdruckerei

When implementing data analysis and AI projects, different precautions are therefore necessary to ensure that security is the top priority. Users need to pay particular attention to customising the application for their particular situation. This is the only way to ensure that the analysis methods used will produce the best results – without losing sight of the importance of data protection and user-friendliness. Bundesdruckerei GmbH develops solutions for data analysis and AI projects with versatile application possibilities options for public administration and for companies in the regulated private sector – trustworthy, transparent, open to technology and legally secure.