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Business Intelligence Consultant

ANIRBAN, an astute professional brings with his out of total 19.10 years experience has spent significant time working with key customers across the globe (US, UK, Europe, Australia and Asia) & brings in extensive experience in area of Big Data, Analytics, Business Intelligence (BI) and Information Management.



Horizontals : E-Commerce (B2B, B2C, C2B) I CRM |Adv. Analytics I Logistics I ERP I



Requirement

Hourly, daily, monthly Forecasting of O2, N2 Gas Consumption using Time Series Analysis.



Solution

For implementing the same, I used statistical methods like ARIMA & Holt-Winter for the time series analysis. Also made use of R packages like tseries, forecast, digraph, Rserve to figure out best time series model in R. Used R-script through Tableau for data rendering.



Result

Forecasting gas consumption for different customers using last 2 years historical records of per hour gas consumption was successfully done. ARIMA and Holt-Winter have been used for forecasting next 6 hours, 6 days & 3 months consumption. Also, another data set was last 1 year minute level gas consumption data and have predicted the consumption for next 6 minutes and also for next 6 hours.