Open AccessExplore Big Data and Forecasting Future Values using Univariate Arima Model in R
Author(s) -
S Sagar Imambi,
Vidyullatha Pellakuri,
M V.B.T.Santhi,
P Haran Babu
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.7.12300
Subject(s) - autoregressive integrated moving average , univariate , big data , computer science , time series , data science , data mining , sales forecasting , series (stratigraphy) , econometrics , operations research , industrial engineering , machine learning , multivariate statistics , engineering , mathematics , biology , paleontology
Electronic equipment and sensors spontaneously create diagnostic data that needs to be stocked and processed in real time. It is not only difficult to keep up with huge amount of data but also reasonably more challenging to analyze it. Big Data is providing many opportunities for organizations to evolve their processes they try to move beyond regular BI activities like using data to populate reports. Predicting future values is one of the requirements for any business organization. The experimental results shows that time series model with ARIMA (3,0,1)(1,0,0) is best fitted for predicting future values of the sales.