As digitalization progresses, data analysis and artificial intelligence (AI) are becoming increasingly important for companies. The recently published Lünendonk study on the data & analytics (D&A) market shows that 86% of the companies surveyed want to develop into data-driven organizations.
But why is this change so important and how is it changing the data landscape and data management? Dr. Gero Presser, Managing Director of Dataciders, and Christian Schneider, Managing Director of QuinScape, explored these questions in an interview with Mario Zillmann from Lünendonk.
To the recording: https://www.youtube.com/watch?v=C5Z1KLjMPsg
The transformation to a data-driven organization
Data has played an important role in companies for some time now, according to Gero Presser's observation. However, it is only thanks to the increasing availability and variety of data, as well as advances in data quality and processing, that it is increasingly becoming a reliable basis for well-founded decisions.
"Software projects have actually always also been data projects, but the software aspect was previously the main focus," adds Christian Schneider. Today, this focus is increasingly shifting to the data aspect. "With the diversity of data and the resulting possibilities, companies are increasingly realizing how important data is in software development."
The importance of artificial intelligence
Artificial intelligence is another important trend on the way to becoming a data-driven company. AI has already generated a lot of hype in the past, says Gero Presser, but it was only with Generative AI that it achieved a breakthrough that appealed to the masses. The accessibility and ability of AI models to automate tasks that were previously considered human skills have led to a rethink and will cause major upheavals in almost all areas.
Companies should be prepared to keep pace with developments, recommends Christian Schneider. "We need to start working with our customers now to incorporate and use AI and generative AI in projects in order to be prepared for what's to come."
Changes in data management and customer requirements
But what does the increased market maturity of artificial intelligence and the diverse possibilities of data usage mean for companies? How will this affect the future data landscape and data management?
Gero Presser is convinced that the previous approach of centralized data management will no longer work in the future. The transformation to a data-driven organization is increasingly moving towards decentralization. This means that data provision and responsibility will be located in the specialist departments, i.e. where the data is created, where it is processed and where it is made available to others as data products. "This is a trend that we are currently seeing everywhere in organizations," says Gero Presser.
A key challenge here is combining the domain knowledge of the specialist departments with data and analytics expertise. According to Gero Presser's observations, many companies do not yet have sufficient internal expertise in relation to data. The task now is to adapt the organization accordingly and establish the necessary data governance to enable decentralized data provision.
Decentralization also has an impact on companies' requirements for service providers such as Dataciders. Gero Presser has observed that, as a result of increasing decentralization, data projects are increasingly appearing in the guise of a wide variety of specialist topics. Instead of only seeking specialized support in certain technological areas, many customers now prefer a full-service approach that combines project-specific expertise with technical know-how.
Conclusion and outlook: Challenges and opportunities in the D&A market
In conclusion, the trends in the data & analytics market are moving inexorably towards data-driven organizations and artificial intelligence. Companies must adapt to the changes in data management in order to remain competitive. A close link between domain knowledge and data & analytics competencies as well as the establishment of data governance are crucial in order to make the best possible use of the diverse possibilities of data utilization. The decentralization of data management is also placing new demands on service providers in the direction of a full-service approach.
It will be exciting to see how companies develop in the future and successfully meet the challenges of the digital age.
