CLIAMS:1. A computer implemented method for automated generation and updating of rules, the method comprising:
obtaining, by a processor (110), at least one data trend pertaining to at least one data stream for a pre-defined period of time, wherein the at least one data trend is indicative of a pattern followed by the at least one data stream during the pre-defined period of time;
computing, by the processor (110), at least one delta value pertaining to the at least one data stream, wherein the at least one delta value is indicative of a deviation in the at least one data stream with respect to the at least one data trend at a specific time instance;
identifying, by the processor (110), at least one relationship between a plurality of data streams including the at least one data stream, based on the at least one data trend and identity metadata associated with each data stream, wherein the identity metadata is indicative of a unique identity of each data stream;
generating, by the processor (110), at least one rule based on the at least one delta value and the at least one relationship, wherein the at least one rule includes a condition set by a user for tracking the deviation in the at least one data stream; and
providing, by the processor (110), a notification to the user when the at least one rule is violated, wherein the notification includes at least one of details pertaining to the rule violation, an action and a suggestion to overcome the rule violation.
2. The computer implemented method as claimed in claim 1 further comprising:
identifying, by the processor (110), a rule violation trend, wherein the rule violation trend includes a pattern of rule violations occurred over a period of time; and
updating, by the processor (110), the at least one rule based on a user response to the notification, the rule violation trend, the at least one delta value, and the at least one relationship.
3. The computer implemented method as claimed in claim 1, wherein the obtaining comprises:
retrieving, by the processor (110), data from at least one data source based on retrieval metadata, wherein the data source includes at least one of an in-house database, an external database, and an online portal, and wherein the retrieval metadata is indicative of details assisting in retrieval of the data from the at least one data source;
transforming, by the processor (110), the data into the at least one data stream, wherein the at least one data stream is in a pre-defined format; and
identifying, by the processor (110), the at least one data trend pertaining to the at least one data stream.
4. The computer implemented method as claimed in claim 3, wherein the obtaining further comprises selecting samples from the data for transforming into the at least one data stream.
5. The computer implemented method as claimed in claim 2, wherein the user responds to the notification by selecting one of an "accept", a "reject", and an "ignore" tab provided in the notification.
6. The computer implemented method as claimed in claim 2 further comprising generating, by the processor (110), a performance report for providing details pertaining to the automated generation and update of rules.
7. A rule generation system (102) for automated generation and dynamic update of rules, the rule generation system (102) comprising:
a processor (110);
a rule generation module (122), coupled to the processor (110), to,
obtain at least one data trend pertaining to at least one data stream for a pre-defined period of time, wherein the at least one data trend is indicative of a pattern followed by the at least one data stream during the pre-defined period of time;
compute at least one delta value pertaining to the at least one data stream, wherein the at least one delta value is indicative of a deviation in the at least one data stream with respect to the at least one data trend at a specific time instance;
identify at least one relationship between a plurality of data streams based on the at least one data trend and identity metadata associated with each data stream, wherein the identity metadata is indicative of a unique identity of each data stream;
generate at least one rule based on the at least one delta value and the at least one relationship, wherein the at least one rule includes a condition set by a user for tracking the deviation in the at least one data stream; and
provide a notification to the user when the at least one rule is violated, wherein the notification includes at least one of details pertaining to the rule violation, an action, and a suggestion to overcome the rule violation.
8. The rule generation system (102) as claimed in claim 7 further comprising an update module (124), coupled to the processor (110), to,
identify a rule violation trend, wherein the rule violation trend includes a pattern of rule violations occurred over a period of time; and
update the at least one rule based on a user response to the notification, the rule violation trend, the at least one delta value, and the at least one relationship.
9. The rule generation system (102) as claimed in claim 7 further comprising a trend analysis module (120), coupled to the processor (110), to,
retrieve data from at least one data source based on retrieval metadata, wherein the data source includes at least one of an in-house database, an external database, and an online portal, and wherein the retrieval metadata is indicative of details assisting in retrieval of the data from the at least one data source;
transform the data into the at least one data stream, wherein the at least one data stream is in a pre-defined format; and
identify the at least one data trend pertaining to the at least one data stream.
10. The rule generation system (102) as claimed in claim 9, wherein the trend analysis module (120) selects samples from the data for transforming into the at least one data stream.
11. The rule generation system (102) as claimed in claim 8, wherein the user responds to the notification by selecting one of an "accept", a "reject", and an "ignore" tab provided in the notification.
12. The rule generation system (102) as claimed in claim 8, wherein the update module (124) generates a performance report for providing details pertaining to the automated generation and update of rules.
13. A non-transitory computer-readable medium having embodied thereon a computer program for executing a method comprising:
obtaining, by a processor (110), at least one data trend pertaining to at least one data stream for a pre-defined period of time, wherein the at least one data trend is indicative of a pattern followed by the at least one data stream during the pre-defined period of time;
computing, by the processor (110), at least one delta value pertaining to the at least one data stream, wherein the at least one delta value is indicative of a deviation in the at least one data stream with respect to the at least one data trend at a specific time instance;
identifying, by the processor (110), at least one relationship between a plurality of data streams based on the at least one data trend and identity metadata associated with each data stream, wherein the identity metadata is indicative of a unique identity of each data stream;
generating, by the processor (110), at least one rule based on the at least one delta value and the at least one relationship, wherein the at least one rule includes a condition set by a user for tracking the deviation in the at least one data stream; and

providing, by the processor (110), a notification to the user when the at least one rule is violated, wherein the notification includes at least one of details pertaining to the rule violation, an action, and a suggestion to overcome the rule violation. ,TagSPECI:As Attached