Currently, Data Quality Center (DQC) has 36 template rules every of which is described in this article.
Fluctuation calculation
Fluctuation=(Sample  Reference value)/Reference value
Fluctuation variance calculation
(Current sample  historical Nday average values) / standard deviation
Glossary
 Sample: The value of the specific samples collected per day, such as the number of rows in the SQL task table, oneday fluctuation detection. Sample is the number of partitions of the table in the current day.
 Reference value: Comparison of historical samples.
 For example, rule is the number of rows in the SQL task table and oneday fluctuation detection, then the reference value is the number of partitions of the table generated in the previous day.
 For example, rule is the number of rows in the SQL task table and sevenday fluctuation detection, then the reference value is the average data value in rows of the table for the previous seven days.
Verification logic
Currently, Data Quality only supports Fluctuation detection value and Comparison of fixed value verification methods.
Verification method  Verification logic 
Fluctuation detection value 

Comparison of fixed value 

Template rule
Template level  Template name  Description 
1  The average value of the field, fluctuation compared to the one day, one week, one month before.  Take the average value of this field, compare with the oneday, sevenday, onemonth period, calculate the fluctuation. Then compare it with the threshold, if there is an alarm, it is triggered. 
2  The summary value of the field, fluctuation compared to the one day, one week, one month before.  Take the sum value of this field, compare with the oneday, sevenday, onemonth period, calculate the fluctuation. Then compare it with the threshold, if there is an alarm, it is triggered. 
3  The minimum value of the field, fluctuation compared to the one day, one week, one month before.  Take the minimum value of this field, compare with the oneday, sevenday, onemonth period, calculate the fluctuation. Then compare it with the threshold, if there is an alarm, it is triggered. 
4  The maximum value of the field, fluctuation compared to the one day, one week, one month before.  Take the maximum value of this field, compare with the oneday, sevenday, onemonth period, calculate the fluctuation. Then compare it with the threshold, if there is an alarm, it is triggered. 
5  The number of unique values in the field.  Count the number after removing duplicates, then compare with an expected number, that is, fixed value verification. 
6  The number of unique values in the field, volatility compared to the one day, one week, one month before.  Count the number after removing duplicates, compare with one day, one week, one month, that is, fixed value verification. 
7  The number of rows in the table, fluctuation compared to the one day, one week, one month before.  Compare the number of rows in the table collected one day, one week, and one month before, and compare the fluctuation. 
8  The number of null values in the field.  The number of null values in this field compare to the fixed value. 
9  The number of null values in the field / Total number of rows.  Calculate the number of null values and the total number of rows to get a rate, then compare with a fixed value. Note: The fixed value is a decimal. 
10  The number of duplications in the field / Total number of rows.  The rate of the number of repeated values to the total number of rows, then compare with a fixed value. 
11  The number of duplicated values in the field.  The total number of rows minus the number after removing duplicates (that is the number of duplicated values in the field), and the number of duplicated values compared to the fixed value. 
12  The number of unique values in the field / Total number of rows.  The rate of the number of unique values to the total number of rows, then compare with a fixed value. 
13  The average value of the field, fluctuation compared to the one day before.  Take the average value of the field, compare with the previous period. Calculate the fluctuation, then compare with a threshold value. 
14  The summary value of the field, fluctuation compared to the one day before.  Take the sum value of this field, compare with the previous period. Calculate the fluctuation, then compare with a threshold value. 
15  The minimum value of the field, fluctuation compared to the one day before.  Take the maximum value of this field, compare it to the one day before. Calculate the volatility, then compare with a threshold value. 
16  The maximum value of the field, fluctuation compared to the one day before.  Take the maximum value of this field, compare it to the one day before, calculate the fluctuation, then compare with a threshold value. 
17  The summary value of the field, fluctuation compared to the previous period.  Take the sum value of this field, compare it with the previous period, calculate the fluctuation. Then compare it with the threshold, if there is an alarm, it is triggered. 
18  The minimum value of the field, fluctuation compared to the previous period.  Take the minimum value of this field, compare it with the previous period, calculate the volatility. Then compare it with the threshold, if there is an alarm, it is triggered. 
19  The maximum value of the field, fluctuation compared to the previous period.  Take the maximum value of this field, compare it with the previous period, calculate the fluctuation. Then compare it with the threshold, if there is an alarm, it is triggered. 
20  Table size (bytes) is unchanged, compared to the previous period.  Table size (bytes) is unchanged, compared to the previous period. 
21  Table size (bytes) has changed, compared to the previous period.  Table size (bytes) has changed, compared to the previous period. 
22  The number of rows in the table has changed, compared to the previous period.  The number of rows in the table has changed, compared to the previous period. 
23  The number of rows in the table is unchanged, compared to the previous period.  The number of rows in the table is unchanged, compared to the previous period. 
24  Table size, difference value compared to the previous period (bytes).  Table size, difference value compared to the previous period (bytes). 
25  The number of rows in the table, difference value compared to the previous period.  The reference value is the number of partitions of the table generated in the previous period. Compare to the number of table rows collected on the current day, then compare the difference value. 
26  The number of rows in the table.  The number of rows in the table. 
27  Table space size (bytes).  Table space size (bytes). 
28  The number of rows in the table, difference value compared to one day before.  The reference value is the number of partitions of the table generated one day before. Compare to the number of table rows collected on the current day, then compare the difference value. 
29  Table space size, difference value compared to one day before (bytes).  Table space size, difference value compared to one day before (bytes). 
30  Table space size, fluctuation compared to the one day before.  The template is the fluctuation of the table size monitoring. The sample is compared with the quota sample of the previous day. If the orange threshold is 5% and the red threshold is 10%, the orange alarm is triggered when the fluctuation is greater than 5% and less than or equal to 10%. The red alarm is triggered when the orange threshold is greater than 10%. 
31  Table space size, fluctuation compared to the one week before.  The template is the fluctuation of the table size monitoring. The sample is compared with the quota sample of the previous week. If the orange threshold is 5% and the red threshold is 10%, the orange alarm is triggered when the fluctuation is greater than 5% and less than or equal to 10%. The red alarm is triggered when the orange threshold is greater than 10%. 
32  Table space size, fluctuation compared to the one month before.  The template is the fluctuation of the table size monitoring. The sample is compared with the quota sample of the previous month. If the orange threshold is 5% and the red threshold is 10%, the orange alarm is triggered when the fluctuation is greater than 5% and less than or equal to 10%. The red alarm is triggered when the orange threshold is greater than 10%. 
33  The number of rows in the table, average fluctuation value compared to the last seven days.  The reference value is the average value of the number of table rows in the last seven days. 
34  The number of rows in the table, average fluctuation value compared to the last thirty days.  The reference value is the average value of the number of table rows in the last thirty days. 
35  The number of rows in the table, fluctuation compared to the one day before.  The reference value is the number of partitions of the table generated one day before. Compare to the number of table rows collected on the day, then compare the fluctuation. 
36  The number of rows in the table, fluctuation compared to the one week before.  The reference value is the number of partitions of the table generated one week before. Compare to the number of table rows collected on the current day, then compare the fluctuation. 
37  The number of rows in the table, fluctuation compared to the one month before.  The reference value is the number of partitions of the table generated one month before. Compare to the number of table rows collected on the current day, then compare the fluctuation. 
38  The number of rows in the table, the first day of the current month fluctuation compared to the one day, one week, one month before.  Compare the number of table rows collected on the first day of the current month to one day, one week, one month before, and compare the fluctuation. 
39  The number of rows in the table, fluctuation compared to the previous period.  The reference value is the number of partitions of the table generated in the previous period. Compare to the number of table rows collected on the current day, and compare the fluctuation. 
40  Discrete value monitoring (number of packets)  The number of packets is compared with a fixed value. 
41  Discrete value monitoring (group number fluctuation)  The number of divisions for fluctuation detection, one day, seven days, one month ago that day the number of groups is the benchmark. 
42  Discrete value monitoring (state value)  As in select count (*) from table group by table.id, the value of each group after grouping is compared to a certain number. 
43  Discrete value monitoring (state value and fluctuation of state value)  Like select count (*) from table group by table. id, it compares the value of each group after grouping with a certain number; and if the number of groupings increases, it will alarm, without alarming. 