System and a method for assessing data for analytics

A system for assessing readiness of data for data science and analytics, the system comprising:

• a memory storing program instructions;
• a processor configured to execute program instructions stored in the memory;
• and a data assessment engine in communication with the processor and configured to:
• derive a nucleus associated with a dataset and a plurality of time-ordered datasets respectively, wherein each nucleus is representative of minimum number of relevant records and features of corresponding dataset;
• evaluate a redundancy value and a relevancy value of each of the plurality of time-ordered datasets;
• evaluate a complexity and noise associated with each of the plurality of time-ordered datasets;
• evaluate a data insight quotient(DIQ)value for each of the plurality of time-ordered datasets as a function of the relevancy, the redundancy, the complexity and the noise associated with corresponding datasets;
• and
• determine readiness of each of the plurality of time-ordered datasets based on the DIQ value, wherein readiness of data is representative of ability of data for performing analytics to derive desired results.

A computer program product comprising:

• a non-transitory computer-readable medium having computer-readable program code stored thereon, the computer-readable program code comprising instructions that, when executed by a processor, cause the processor to:
• derive a nucleus associated with a dataset and a plurality of time-ordered datasets respectively, wherein each nucleus is representative of minimum number of relevant records and features of corresponding dataset;
• evaluate a redundancy value and a relevancy value of each of the plurality of time-ordered datasets;
• evaluate a complexity and noise associated with each of the plurality of time-ordered datasets by using a principle graph and manifold technique on each of the nucleus derived from corresponding time-ordered datasets;
• evaluate a data insight quotient(DIQ) value for each of the plurality of time-ordered datasets as a function of the relevancy, the redundancy, the complexity and the noise associated with corresponding datasets;
• and
• determine readiness of each of the plurality of time-ordered datasets based on the DIQ value, wherein readiness of data is representative of ability of data for performing analytics to derive desired results.