A private engineering degree is useless
No career without data knowledge
Anyone who understands Big Data Bahnhof will quickly reach their limits in a technical profession. Which may affect more engineers than one would like. Because among German company roofs, the importance of data competence does not seem to have really arrived - in contrast to China. James Hodge, Chief Technical Advisor EMEA at the software company Splunk, explains why this can be dangerous for the location and your own career.
INGENIEUR.de: Are data skeptics dominating in German companies?
James Hodge: No, not really. Because the German experts agree on the value of data for corporate success. But while business leaders and IT managers recognize how important data is to their success, many say that “data-driven” is still an empty phrase in their companies. In our latest survey, 91 percent of Chinese respondents say that they need data skills to be promoted; according to 92 percent, data skills are even necessary to achieve a leadership position. Your German colleagues, on the other hand, seem to be less concerned about the importance of data skills for their careers: only between 60 and 80 percent agree with these statements.
Also read: Data Scientist: What does the professional data evaluator do?
Where does this misjudgment come from?
The speed of innovation in Big Data is enormous: it is largely driven by advances in computing power and the development of flexible software that is able to analyze digital by-products. It's challenging to keep up with this pace. The survey shows that there is a discrepancy in people's heads: On the one hand, employees in German companies recognize that data knowledge is indispensable - on the other hand, the enthusiasm for acquiring skills in this area is limited. Many respondents may see this as a challenge that the next generation of managers should solve ...
... which would be pretty late! Meanwhile, could artificial intelligence iron out a lack of data literacy among staff?
A look at China: 85 percent of those surveyed there state that AI can close the skills gap in the IT industry. In an international comparison, they place the most trust in the technology. Taking the payment area as an example, more than 580 million people in China made at least one mobile payment in 2018, 10.7 percent more than in the previous year. The analyst firm Frost & Sullivan predicts that the number of users of mobile payment systems in China will reach nearly one billion by 2023. This is associated with a veritable data explosion - the information it contains can be used by companies if they are able to improve their service in order to differentiate themselves from the competition. In Germany, the increase in data has so far not been that revolutionary and, as a result, data-driven projects have been less successful.
What would have to change in people's minds for Germany to catch up?
Only half of the German respondents agree that data literacy will be important for the jobs of the future. The challenge, however, is that the data revolution is already here. In order for employees of a company to recognize how important data knowledge is or will be for them and their company, companies must already use the data within the given possibilities. To do this, they have to gain the customers' trust that their data is safe with the company. If this trust is not built, it is unlikely that people will see working with data as a valuable skill. The General Data Protection Regulation should be seen as a fundamental mechanism for building trust. This creates an environment in which data is used to drive innovations.
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To what extent should the search for personnel, training and on-the-job training change?
People are the focus of every company. Investing in data competence is therefore crucial for the employees to understand the relationships around them and then to recognize the correct relationships from the former “dark data” (unstructured, so far little-used data, editor). By continuously training employees in the responsible and ethical handling of data and by being able to access dark data, they can make better decisions. Making dark data usable is only part of it, however, because it is just as important that managers drive the change and are held accountable for it.
Which new competencies around data analysis and AI should engineers acquire?
Algorithms without records are useless and vice versa. When working with data, finding, moving and changing data currently takes more time than actually dealing with data sets and algorithms. However, this is the basis for taking possible measures and thus positively influencing the business result. As companies become more and more aware of the data they generate, the value of employees who can handle data, i.e. data scientists, increases. Skilled workers and engineers who understand the social and economic implications of their work and keep up with the rapid pace of development will be successful because they can add value to their company. That being said, they should also be familiar with data ethics and security. If you put these considerations at the beginning of the thinking and design process, you are guaranteed to be able to use your data knowledge quickly.
James Hodge speaks about the "German data skepticism".
A data engineer reports from his everyday life
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A contribution from:
Chris Löwer has been working as a freelance journalist for national media for more than 20 years. His main topics are science, technology and career.
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