Company had pipeline conversion issue. Their leads did not get converted. So their revenue got decreased from 35% to 25%.

· Understand the problem by requirement gathering, collect and clean the data

· Do the hypothesis to find out the reason of the problem then start processing on data, find out the problem using data analytics.

· Analyze the data and find out the KPI and find out the reasons.

· First steps was:- EDA approach

· Data segmentation, data modelling, data analysis and data predictions with classification technique.

· Apply Machine learning approach on Indian data, and find out the sale value of July 2019.

· Find out Budget, Profit margin of the company.

· Make the clusters (K-nn Algorithm) and find out which cluster provide the maximum sale.

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· Data analysis (data cleaning, formatting, Statistical analysis, hypothesis testing, pivot, lookups, charts) of insurance data using excel, find out the insights and data visualization using excel and tableau of the results.

· I have experienced to take the product Requirements(Agile), Generate BRD, FRD, Software deployment (WebSphere), Software development and testing, Feasibility Analysis, Technical Discussions, Application Migration, Code Integration, Production(Delivery Support), UAT.

· I worked on Machine Learning (Regression, Clustering, Classification, Time series predictions) algorithms using Python to solve the business related problems.