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Big Data Analytics is considered to be the key disruptive technology of the decade, and is revolutionizing the industries like never before with its ubiquitous applicability. Though the term "Big Data" gained more traction since 2011 after the McKinsey Report [1], some business models have been generating huge volumes of data for several decades. Some prominent examples include the Government [2] and Private [3] Meteorological Departments forecasting weather on the basis of Satellite Imagery [4] and the Logistics industry working with Geospatial Data [5]. There has been a significant boost to the efficiency of operations and the accuracy of results in both sectors after the advent of Big Data Analytics. This paper examined the Geolocation Data provided by Google based on the Location Service API [6], and suggested different ways to preprocess and visualize the data for a business analysis later. The data had been taken from the operational fleet of a leading logistics service provider in India and a small subset has been analyzed to assess the suitability of the application of this paper in a general purpose manner. This study is a part of research[7] on applications of IoT and Big Data Analytics in the supply chain management being conducted by the authors, but can be used independently in other applications as well. [ABSTRACT FROM AUTHOR]

In cloud environment, big data analytics is a very innovative idea;Big data is defined as a very huge quantity of data. To extract meaning full value from it we need different technologies for analysis of the data. Big data Analytic is used to study pattern of historical data and the effect of changes of different parameters. Rainfall Forecasting has been a standout amongst the most intriguing and captivating space and it assumes a noteworthy part in meteorology and daily human life. Rainfall forecasting is used to estimate the probability of whether it will rain or not. Rainfall situation is the state of atmosphere at a given time in terms of different parameter like temperature, humidity and wind speed. Forecasting of rainfall is important to facilitate preparing for the finest and the nastiest of the climate. India is agrarian country so it is essential to know in advance about climate. This paper presents big data analytics for Rainfall forecasting and studies the advantage of using it. The algorithm which is used in this project is Time Series. The intention of time series analysis is generally in two ways, one is to recognize or representation the stochastic mechanisms that gives rise to an observed series and second is to predict or forecast the future value of an arrangement in light of the historical backdrop of that arrangement. Forecasts are prepared for new data when the actual result may not be known until some future date. What's to come is being anticipated, yet all earlier perceptions are quite often treated similarly. [ABSTRACT FROM AUTHOR]