System and method for processing a raw data is disclosed. The system is configured to identifying a pattern using a plurality of datasets selected from the raw data. Further, the system is configured to fetching a first set of data patterns associated with a first set of historical visualizations. The system further identifies a second set of data patterns from the first set of data patterns by matching the pattern with the first set of data patterns. Furthermore, the system is configured to identify a second set of historical visualizations associated with the second set of data patterns from the first set of historical visualizations. Further, the system is configured to represent the raw data graphically for predictive analysis based on at least one historical visualization selected from the second set of historical visualizations.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A system for processing a raw data, the system comprising: a memory; and a processor coupled to the memory, wherein the processor is configured to perform the steps of: identifying a pattern using a plurality of datasets selected from the raw data; fetching a first set of data patterns associated with a first set of historical visualizations; identifying a second set of data patterns applicable to the plurality of datasets by matching the pattern with the first set of data patterns, wherein the second set of data patterns is a sub set of the first set of data patterns; identifying a second set of historical visualizations associated with the second set of data patterns from the first set of historical visualizations; and representing the raw data graphically for predictive analysis based on at least one historical visualization selected from the second set of historical visualizations. 2. The system of claim 1, wherein the plurality of datasets are generated by sampling the raw data at predefined intervals based on a set of values associated with the raw data. 3. The system of claim 1, wherein the pattern is identified by performing keyword based analysis over the plurality of datasets. 4. The system of claim 1, wherein the first set of data patterns and the first set of historical visualizations are stored in an online repository. 5. The system of claim 1, further comprising selecting at least one historical visualization from the second set of historical visualizations. 6. The system of claim 1, further comprising categorizing and ranking the historical visualizations present in the second set of historical visualizations based on at least one of historical recommendations or geographical location of the users. 7. The system of claim 1, wherein the first set of historical visualizations is a set of graphs used to represent raw data. 8. The system of claim 1, wherein the first set of data patterns is indicative of features associated with historically analyzed data, wherein these features associated with the historically analyzed data include at least one of a skewed right, a skewed left, a uniform distribution, bell-shaped curves, and number of peaks. 9. A method for processing a raw data, the method comprising steps of: identifying, by a processor, a pattern using a plurality of datasets selected from the raw data; fetching, by the processor, a first set of data patterns associated with a first set of historical visualizations; identifying, by the processor, a second set of data patterns applicable to the plurality of datasets by matching the pattern with the first set of data patterns, wherein the second set of data patterns is a sub set of the first set of data patterns; identifying, by the processor, a second set of historical visualizations associated with the second set of data patterns from the first set of historical visualizations; and representing, by the processor, the raw data graphically for predictive analysis based on at least one historical visualization selected from the second set of historical visualizations. 10. The method of claim 9, wherein the plurality of datasets are generated by sampling the raw data at predefined intervals based on a set of values associated with the raw data. 11. The method of claim 9, wherein the pattern is identified by performing keyword based analysis over the plurality of datasets. 12. The method of claim 9, wherein the first set of data patterns and the first set of historical visualizations are stored in an online repository. 13. The method of claim 9, further comprising selecting at least one historical visualization from the second set of historical visualizations. 14. The method of claim 9, further comprising categorizing and ranking the historical visualizations present in the second set of historical visualizations based on at least one of historical recommendations or geographical location of the users. 15. The method of claim 9, wherein the first set of historical visualizations is a set of graphs used to represent raw data. 16. The method of claim 9, wherein the first set of data patterns is indicative of features associated with historically analyzed data, wherein these features associated with the historically analyzed data include at least one of a skewed right, a skewed left, a uniform distribution, bell-shaped curves, and number of peaks. 17. A computer program product having embodied thereon a computer program for processing a raw data, the computer program product comprising: a program code for identifying a pattern using a plurality of datasets selected from the raw data; a program code for fetching a first set of data patterns associated with a first set of historical visualizations; a program code for identifying a second set of data patterns applicable to the plurality of datasets by matching the pattern with the first set of data patterns, wherein the second set of data patterns is a sub set of the first set of data patterns; a program code for identifying a second set of historical visualizations associated with the second set of data patterns from the first set of historical visualizations; and a program code for representing the raw data graphically for predictive analysis based on at least one historical visualization selected from the second set of historical visualizations.