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What And Why Is Big Data So Important?
Data Analytics is the use of Big Data (large sets of data that are often challenging to examine and investigate due to their complexity and variability) with the methodologies of Lean Six Sigma (LSS). Big Data (BDA) can unveil hidden patterns, customer preferences, correlations between different products/parameters, market trends. The combination of Data Analytics and LSS is not common practice currently, however, this is the way forward for more efficient and defect free results. Data Analytics supports LSS through each of its phase.
Starting with the define phase, data mining (in our case it will be process mining) can be used. With the help of confidence interval (CI) the current situation can be mapped to measure for phase two. Phase three is to analyze, methods such as machine learning, clustering, classification, decision trees, and association rules can be used. Phase four is improvement, artificial intelligence, machine learning and flow diagrams can be used to optimize parameters for the LSS project. The last phase of control can be assisted by Data Analytics through an algorithm that can be developed to process control. After doing a thorough literature review it was found that not enough research has been done on how well Data Analytics complements the LSS methodologies to optimize and enhance the performance of an organization using them together. All the studies that were done on the matter had a positive conclusion.