In today’s business world, the ability to make data-driven decisions is critical to an organization’s success.
Many companies rely on analyzing internal data to support key C-level decisions.
This data includes metrics such as the number of new and churned customers, customer segmentation and performance metrics.
But what happens if the underlying SQL query is faulty?
Example: Effects of an incorrect SQL query
A recent example from Senior Data Engineer Juri Sarbach’s own experience shows how a supposedly small discrepancy in an SQL query can have serious consequences.
At one of our customers, the company regularly analyzed its internal data in order to make strategic decisions.
However, the SQL query used to calculate the key figures and KPIs was not entirely correct.
The resulting figures deviated from reality, but not to such an extent that the error was immediately obvious.
Main cause: lack of data analytics expertise
The main cause of the problem was the lack of the necessary data analytics expertise within the company.
Without the necessary expertise to create and validate SQL queries, management made decisions based on incorrect evaluations.
This could have led to strategic mistakes that could have cost the company dearly.
Need for qualified data analysts
Despite the company’s laudable intention to act in a data-driven manner, the basis for this was lacking – in particular the necessary skillset.
Without qualified data analysts who are able to evaluate and interpret data correctly, the “data-driven” approach remains a dangerous illusion.
Skills development for error prevention in SQL queries
This case shows how important it is to have a good understanding of data analysis and to invest in the relevant skills.
Only in this way can companies ensure that their data-based decisions are based on solid foundations and not on false assumptions.
A strong team with these skills can not only identify and correct errors in SQL queries, but also raise the quality of decisions to a new level.
The path to a data-driven corporate culture
Ultimately, this case shows that the path to a truly data-driven corporate culture is not just about collecting data, but also about developing and deploying the right skills and technologies.
This is the only way to ensure that decisions are truly based on reliable data and that the company is successful in the long term.
Conclusion: Importance of correct data interpretation
Our experience with our client has shown us how important it is not only to collect data, but also to ensure that this data is interpreted and used correctly.
A small mistake in data analysis can have a big impact – but with the right skills and a dedicated team, these risks can be minimized and the full potential of the data can be exploited.
Find out more about data-based management in our detailed blog post.
