A method, a computer program product, and an information handling system is provided for identifying a causal relationship between metrics performing steps. The steps include receiving a correlation significance Sij between a metric Mi and a metric Mj; receiving a mutability attribute Ai for the Mi and a mutability attribute Aj for the metric Mj from a data source; and identifying the metric Mi causing the metric Mj with the Sij if only if the Ai is immutable and the Aj is mutable.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method for identifying a causal relationship between metrics, the method implemented by a processor, comprising: receiving a correlation significance Sij between a metric Mi and a metric Mj; receiving a mutability attribute Ai for the metric Mi and a mutability attribute Aj for the metric Mj from a data source; determining if the attribute Ai is immutable and the attribute Aj is mutable to form a causal assessment of true or false of a causal relationship; and performing an action based on the causal assessment. 2. The method of claim 1, wherein the causal assessment is true and the action is identifying the causal relationship wherein the casual relationship indicates the significant Sij of the metric Mj caused by the metric Mi. 3. The method of claim 2, wherein the causal assessment is false and the action is not identifying the causal relationship. 4. The method of claim 3, wherein the data source contains domain specific information supporting a retrieval of the attribute Ai and the attribute Aj. 5. The method of claim 4, wherein the metric Mi is associated with a concept Ci and the metric Mj is associated with a concept Cj in the data source and retrieval of the attribute Ai is based on the concept Ci and retrieval of the attribute Aj is based on the concept Cj. 6. The method of claim 5, wherein the identification of the attribute Ai is by an artificial intelligence annotation system. 7. The method of claim 6, wherein the artificial intelligence system utilizes deep analytic analysis to annotate the domain specific information. 8. A computer program product identifying a causal relationship between metrics, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable on a processing circuit to cause the processing circuit to perform the method comprising: receiving a correlation significance Sij between a metric Mi and a metric Mj; receiving a mutability attribute Ai for the metric Mi and a mutability attribute Aj for the metric Mj from a data source; determining if the attribute Ai is immutable and the attribute Aj is mutable to form a causal assessment of true or false of a causal relationship; and performing an action based on the causal assessment. 9. The computer program product of claim 8, wherein the causal assessment is true and the action is identifying the causal relationship wherein the casual relationship indicates the significant Sij of the metric Mj caused by the metric Mi. 10. The computer program product of claim 9, wherein the causal assessment is false and the action is not identifying the causal relationship. 11. The computer program product of claim 10, wherein the data source contains domain specific information supporting a retrieval of the Ai and the Aj. 12. The computer program product of claim 11, wherein the metric Mi is associated with a concept Ci and the metric Mj is associated with a concept Cj in the data source and retrieval of the Ai is based on the concept Ci and retrieval of the Aj is based on the concept Cj. 13. The computer program product of claim 12, wherein the identification of the attribute Ai is by an artificial intelligence annotation system. 14. The computer program product of claim 13, wherein the attribute Ai is received by the artificial intelligence system based on input from a domain subject matter expert. 15. An information handling system identifying a causal relationship between metrics, the information handling system comprising: at least one processor; a memory coupled to the at least one processor; a set of instructions stored in the memory and executed by the at least one processor wherein the set of instructions perform operations including: receiving a correlation significance Sij between a metric Mi and a metric Mj; receiving a mutability attribute Ai for the metric Mi and a mutability attribute Aj for the metric Mj from a data source; determining if the attribute Ai is immutable and the attribute Aj is mutable to form a causal assessment of true or false of a causal relationship; and performing an action based on the causal assessment. 16. The information handling system of claim 15, wherein the causal assessment is true and the action is identifying the causal relationship wherein the casual relationship indicates the significant Sij of the metric Mj caused by the metric Mi. 17. The information handling system of claim 16, wherein the causal assessment is false and the action is not identifying the causal relationship. 18. The information handling system of claim 17, wherein the data source contains domain specific information supporting a retrieval of the attribute Ai and the attribute Aj. 19. The information handling system of claim 18, wherein the metric Mi is associated with a concept Ci and the metric Mj is associated with a concept Cj in the data source and retrieval of the attribute Ai is based on the concept Ci and retrieval of the attribute Aj is based on the concept Cj. 20. The information handling system of claim 19, wherein the identification of the attribute Ai is by an artificial intelligence annotation system.