Data Health Dashboard
To monitor the health of your data on an ongoing basis, Telmai provides you with a business dashboard about all your data sources and their respective health metrics. You can see your alerts and data
Telmai Data Health Dashboard
This KPI helps to track changes in the total size of the monitored table and is only available when CDC is enabled (i.e., the “delta only” flag is on). If the flag is off or the monitored source is not an SQL database, this field will be set to N/A.
This KPI helps to track changes in the size of the monitored data. If CDC is enabled it reflects the size of the delta, otherwise, it's the size of the entire set of data.
This KPI helps to track the percentage of null/missing/placeholder values. Completeness is tracked both at the data source level as well as the attribute level:
- Attribute level: percent of records where the attribute value is not null, not empty, or not one of the user-defined placeholders like N/A.
- Data Source level: the compounded average of all attribute level completeness within a data source.
This KPI helps to track the validity of values, based on expectations set by a user. Correctness is tracked both at the data source level as well as the attribute level. Correctness is calculated only for attributes where Expectations are set, otherwise, the default is 100%.
- Attribute level: percent of records where the attribute value meets all expectations, set for the attribute.
- Source level: the compounded average of all attribute level correctness within a data source
This KPI helps to track record level freshness. Record level freshness is defined by setting an expectation on a timestamp attribute within the data source (e.g.,. “Record Update Date” attribute to be no more than 1 month from now). To mark an attribute as a timestamp use the Advanced section of the Edit Connection menu. If the timestamp attribute is not configured this KPI will be N/A.
This KPI helps to track the uniqueness of the records based on an ID attribute. The KPI measures the ratio of records with unique id versus the total number of records. For example, if out of 10 records, there are 2 records sharing the same value the uniqueness is 80%.
An attribute can be marked as an ID attribute in the Advanced section of the Edit Connection menu. If ID attribute is not configured this KPI will be N/A
This KPI tracks the accuracy of the values, based on historical data analysis, and detects when current values don’t match predictions. For example, if the revenue for the company Acme Inc was slowly growing from $4M to $5M over the past year, but in today’s observation it’s 20M, then such a value is considered inaccurate. Accuracy is only calculated for attributes that have “Business Metrics” Configured, otherwise, the default is 100%.
- Attribute level: the ratio between business metrics dimensions where no drift was detected to the total number of dimensions. If multiple business metrics are defined for an attribute, then the minimum accuracy is picked for this attribute.
- Data Source level: the compounded average of all attribute level accuracy within a data source.