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Cost of poor data quality
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The cost of poor data quality can be evaluated using methodology outlined in reference **Data Quality Fundamentals** publication (1) as follows: 

*1) Identify downtime related to data incident*

It can be calculated based on the following:

    * Average time to detect data incident (TTD)
    * Average time to resolve data incident (TTR)
    * Number of data incident (N)

.. admonition:: Note

    DDT = N(TTD + TTR) 

    Downtime related to data incident equals the number of incidents (N) times the average time to detection (TTD) and the time it takes to resolve them (TTR)


*2) Calculate labor cost related to data downtime*

The cost of poor data quality can be evaluated directly by the cost of labor directly related to detecting and resolving data incidents based on the following parameters:

    * Number of data engineers (NBDE)
    * Number of worked hours per year (YWH)
    * Average hour cost of a data engineer (HCDE)
    * Average percentage of time spent on data incidents (AVGT) 
    * Average data quality downtime cost per year (YCOST)

.. admonition:: Note

    YCOST = NBDE(AVGT * HCDE * YWH) 

    Yearly average cost of poor data quality can be calculated by multiplying the number of data engineers by the average worked hours per year, average hourly cost of a Data Engineer and the % of his/her time dedicated to fixing Data Quality issues.


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**References**

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    <p style="font-style: italic;font-size:16px">(1) <a href="https://learning.oreilly.com/library/view/data-quality-fundamentals/9781098112035/">Calculating the cost of poor data quality</a></p>