The following procedure starts in Explorer. When you create a metric in Explorer the data asset info is filled in for you. However, you could instead select Create Metric + at the top of the the Metrics list to start without the data asset filled in, then proceed to Step 1 (Metric Info).

1. In the Explorer tree, select the data asset that you want to measure.
2. On the right, on the Actions menu select + Create Metric, then proceed to Step 1 (Metric Info).

Step 1 (Metric Info)

1. Under Metric Info, select a metric type.
2. Enter a Metric name.
3. By default, new metrics go Live shortly after you create them. If you want the metric to start off paused, under Metric status, set Status to Paused.
4. If desired, change the value of Quality dimension. Each data quality metric measures one dimension of data quality: accuracy, completeness, timeliness, or (if none of these applies), custom. You can sort and filter your metrics by dimension or view them by dimension in a Dashboard.

The rest of the process depends on which metric type you select. For the remaining steps, follow the link that corresponds to the metric's type (links are in the next section).

Types of deep metrics

To proceed, select your metric type:

Column metrics

• Aggregation metrics measure changes in the result of an aggregate function that you define.
• Conformity metrics measure the validity of data by checking whether values meet one or more conditions that you specify.
• Distribution metrics measure the distribution of values in a specified column.
• Null percent metrics measure the percent of a column's values that are null.

Comparison metrics

• Compare aggregate metrics let you compare existing metrics for a source table and a target table.
• Row by row metrics let you measure data value differences between a source table and a target table, by picking key fields (to match the rows) and which columns' values you want to compare.

Table metrics

• Data delay metrics measure delay in the arrival of expected data into data assets. Available for use with tables and schemas.
• Data volume metrics measure deviations from expected data volumes. Available for use with tables and schemas.

SQL metrics

SQL metrics measure whatever you model with valid SQL, but must include a SELECT statement that meets basic metric query requirements (details available on the subpage).

Edit a deep metric

1. In the Explorer tree, select the data asset that the metric is based on.
2. On the right, find the chart for the metric you want to edit. Then, in its top-right corner select the three vertical dots, and then select Edit.