A time series is a series of data points indexed (or listed or graphed) in time order. Most commonly, a time series is a sequence taken at successive equally spaced points in time. Thus it is a sequence of discrete-time data.
Time series analysis comprises methods for analyzing time series data in order to extract meaningful statistics and other characteristics of the data. Time series forecasting is the use of a model to predict future values based on previously observed values. While regression analysis is often employed in such a way as to test theories that the current values of one or more independent time series affect the current value of another time series, this type of analysis of time series is not called "time series analysis", which focuses on comparing values of a single time series or multiple dependent time series at different points in time. Interrupted time series analysis is the analysis of interventions on a single time series.
Goal of the project is to develop an open, free and easy to use solution for time series data analysis. It is expected that users will be able to upload time series snapshots or stream data to the cloud and apply various kinds of analytics. It is expected that solution will provide wide range of instuments, based both on clssical analytics along with modern Machine Learning based approaches.