Big data was created to deal with big and complicated datasets that are challenging to process using typical
data-processing methods. Big data is currently being utilized to extract value from datasets through predictive
analysis and other advanced data analytics. This paper introduces incremental Frequent Pattern (FP) analysis, a
novel approach. The suggested incremental FP-Growth analysis is used to build a tree structure with the lowest
redundancy, and the FP growth technique is used to locate frequent itemsets in a database without the need for
candidate generation. This will reduce the number of scans in the database, lowering latency.
Software And Hardware