It may seem counterintuitive to think of data engineers needing to improve Data Literacy, the ability to read, work with, analyze, and argue with data. After all, data engineers apply technical Data Literacy skills to build and optimize operating systems and pipeline channels. At the same time, data engineers show gaps in using organizational Data Literacy and communicating internally across their companies, and this is where they require Data Literacy training.
Managers see that data engineers apply their Data Literacy skills well to solve problems like prompt data delivery among several services. However, the same data engineers work inefficiently by moving data across more services than necessary, suggesting poor organizational Data Literacy.
Consequently, data engineers produce mixed results, saving the Business money in some areas while costing companies 11.4% in resources – and wasted time starts to add up quickly when you consider that the average data engineer gets a salary of $117,000.
Businesses tend to frame this problem as needing better project management. While better project management helps to leverage data engineers, organizations also need to understand this unevenness in Data Literacy exhibited by data engineers and its impacts.
Organizations must empower data engineers to share their Data Literacy strengths with non-technical businesspeople while advancing the data engineers’ Data Literacy through this collaboration. By addressing this organizational Data Literacy imbalance, data engineers will have an expanded toolset applying organizational Data Literacy.
Get a team of sound data engineers, and you will find they understand many Data Literacy basics – statistical concepts about data throughput, how to read a dashboard to identify and solve a data blockage, why a system has outputted some data, and so on. Those Data Literacy skills used to manipulate, comprehend, and argue with data are invaluable beyond data engineering.
When other businesspeople learn these kinds of Data Literacy skills, they can make better decisions based on repeatable and systematic findings. Ninety percent of Business leaders agree that Data Literacy dramatically impacts a company’s success.
Data engineers help increase overall Data Literacy in the Organization by showing businesspeople how to best interpret, explore, and process data through a user interface. In these activities, businesspeople can gain and apply basic Data Literacy skills.
Data engineers step in where situations call for more Data Literacy than required in a typical businessperson’s role. They can leverage automation and build and maintain a good Data Architecture behind the scenes. For example, data engineers from team A make software services, recording when changes to big datasets occur. Other data engineers from team B use these algorithms in their constructions to act on those significant dataset changes.
The technical Data Literacy skills applied by both teams work underneath the hood of the user interface. But the businesspeople can skip knowing these inner workings to accomplish their tasks.
While advanced in technical Data Literacy, data engineers require support to improve their organizational Data Literacy. They get “overwhelmed with developing and maintaining enterprise data systems” and end up overworked.
Many data engineers have left or will consider leaving their jobs because of their organizational Data Literacy gaps. This reality bodes poorly for companies.
Finding sound data engineers with needed programming and statistical skill sets alone poses significant challenges, even with a recessionary economy. Add to these demands to use and communicate key organizational data capabilities across different divisions and businesses and ask the almost impossible.
