The monthly median gross salary for Master Of Science - Business Intelligence And Data Science in Germany is €5,870.00.Based on 18,778 gross salaries
The best-earning Master Of Science - Business Intelligence And Data Science are Combined of Above 55 age groups who live in Bavaria. Their median salary is above €7,100.00, which is a 21% increase over the median salary (€5,870.00) of the selected category.
18,359,909 full-time employees in Germany subject to social insurance earn less than those working as Master Of Science - Business Intelligence And Data Science in Germany. This corresponds to about 84% of full-time employees. A similar gross salary is earned by 161,878 full-time employees subject to social security contributions, or 1%.
At the sector level, median earnings ranged from €5,160 in the banking, finance and insurance sector to €1,890 in the temporary employment sector, where very low-paid manual jobs are clearly overrepresented.
Higher wages are generally associated with employment in larger companies and with longer periods of employment.
A median wage is a number that takes into account several wages and arranges them in ascending or descending order. The median salary is the salary that is in the middle of the sorted salaries. So if you see a median salary, you can be sure that half of the indicated salaries are lower and half are higher.
The exact middle number in a list is called the median. For example, the median of a sorted list of numbers 2300, 2400, 2500, 2600, 2700, 2800 and 6000 is 2600 because half the numbers are lower and half are higher.Mean
Mean wages are calculated by summing up all of the salaries on a list and dividing by the number of salaries on the list. This is important to remember while examining wages, since it implies that extremely high and extremely low incomes are weighted equally in the final average. When data includes a few abnormally high or low wages, mean salary reporting might be misleading.
Rather of looking for the middle number in the list, the mean is calculated by using additions and division. For example, to calculate the mean of 2300, 2400, 2500, 2600, 2700, 2800 and 6000 add them all together to get 21300. Divide them by 7, which is the number of entries on the list, and you get 3042.85.