Forecasting from Big Data

A forecast is a forecast made by studying historical data and past patterns. Businesses use software tools and systems to analyse large volumes of data collected over time. Predictive research based on big data is usually divided into three main steps, namely data collection (collecting big data from relevant sources), data processing (pre-processing and representing big data and extracting predictive knowledge) and predictive improvement (by combining extracted predictive data). While there is a wide range of commonly used quantitative budget forecasting tools, in this article we focus on the first four methods: (1) straight line method, (2) moving average method, (3) simple linear regression method, and (4) multivariate Normal linear regression.

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