- Blog
- AnalyticsTrends, Opinion
- 4 min reading time
Dr. Eric Trumm
From the technologies of the future
In the analytics environment, new technologies and concepts are also changing the way companies use data and transform it into valuable insights. However, not all innovations live up to their promises. Some establish themselves sustainably and shape the analytics environment, while others quickly lose importance. In this article, we will shed light on the currently relevant technologies and their potential to shape the future of data analysis. We will take a look at the Tops, Flops, and Superpowers – categories that help to understand the developments and identify the true drivers of innovation.
Goals and challenges of modern technologies
The goal of modern technologies is clear: they should be so accessible and user-friendly that even users without in-depth technical expertise are able to solve problems independently. Not only is ease of use important, but also the acceptance of a technology. Especially at the beginning, innovative technologies are often met with skepticism or rejection. But over time, this attitude often changes into broad acceptance and increased use, a process that can be observed particularly with disruptive technologies.
Tops: The current favorites in the analytics field
Self-service BI (Business Intelligence) is one of the most groundbreaking developments. Modern BI tools such as SAP Analytics Cloud (SAC) or SAP Datasphere enable users to create queries and reports independently of IT. The advantage: The flexibility to make your own drilldowns on existing data and combine it with other data sources strengthens the independence of the users. This allows informed decisions to be made quickly and efficiently, while significantly reducing the susceptibility to errors. The IT department also benefits, as it is relieved of routine tasks and can concentrate on more complex tasks.
The democratization of data is another key topic, because for data-driven decisions in companies, it is crucial to enable as many employees as possible to access data – regardless of their technical know–how. This includes not only easy access to data from different departments, but also the necessary training of employees in the use of BI tools, e.g. the SAP Data Catalog, which functions as a central cataloging system for data and helps users to quickly find the relevant information.
Flops: Technologies that did not bring the hoped-for success
One example is the standardized notation in BI reports, which is intended to ensure greater consistency and transparency, but did not achieve the desired success due to the high learning curve and limitations regarding creative design. The SAP Analytics Cloud (SAC) now offers solutions with which users can create visualizations that meet the common standard without much effort.
Another example of a flop in the analytics environment is the concept of self-service predictive analytics. The idea of creating forecasts automatically and without in-depth expertise did not lead to the desired success, as many users did not trust the underlying algorithm, especially if they could not understand the models. Another problem is the lack of data quality, because the forecasts are based on historical data that can be distorted by unusual events, so the hoped-for effect fails to materialize.
Superpowers: Technologies that will shape the future
Cloud technologies have not only revolutionized the infrastructure for data analysis, but also the way companies implement and use their data solutions. The initial concerns regarding data security and access to cloud data have been overcome by innovative functions, such as live reporting, and ensuring data security in company networks, and have established themselves as indispensable. The scalability and global availability of the cloud also offer enormous cost advantages and flexibility for companies.
AI and ML are undoubtedly the superpowers. They have simply revolutionized our work with data. Thanks to cloud computing and scalable computing power, these technologies are now accessible to many companies. Despite the current hype surrounding AI, which strictly speaking does not always reflect reality, the further development and increasing importance of these technologies in the coming years is very likely. They are guaranteed to not only shape SAP products such as SAC and SAP Datasphere, but also open new doors in the world of data analysis. We can be curious!
Further Information
In the Ruring the Analytics Online Conference, I gave a presentation on this topic. For anyone who would like to delve deeper, the recording of the presentation is available here.
Conclusion: The best technology is useless if the foundation isn't right
The observation shows: Many technologies that are celebrated as tops today could already be flops tomorrow, because the analytics world is subject to constant change. But the technology itself is not the only decisive factor, but above all how it is integrated into business processes and what practical added value it delivers.
No matter which technologies are implemented, the importance of high-quality data remains central. Especially in the age of AI and ML, the principle of "garbage in, garbage out" is more relevant than ever. Companies can only exploit the full potential of modern technologies if they ensure that they work with a solid data foundation from the start.
Those who rely on the right technologies and combine them with a solid data foundation will be able to master the challenges of the future and fully exploit the potential of digitization. The journey is far from over, and the developments in the analytics environment will continue to offer us many exciting opportunities (and challenges).
We would be happy to provide you with a more in-depth look at the topic. Please feel free to contact us here.
