As a user i want to use data that i have selected from data source/tags so that i can see:
Trend analysis: Just plotting data against time can generate very powerful insights. One very basic use of time-series data is just understanding temporal pattern/trend in what is being measured. In businesses it can even give an early indication on the overall direction of a typical business cycle.
Outlier/anomaly detection: An outlier in a temporal dataset represents an anomaly. Whether desired (e.g. profit margin) or not (e.g. cost), outliers detected in a dataset can help prevent unintended consequences.
Examining shocks/unexpected variation: Time-series data can identify variations (expected or unexpected) and abnormalities, detect signals in the noise.
Association analysis: By plotting bivariate/multivariate temporal data it is easy (just visually) to identify associations between any two features (e.g. profit vs sales). This association may or may not imply causation, but this is a good starting point in selecting input features that impact output variables in more advanced statistical analysis.
Forecasting: Forecasting future values using historical data is a common methodological approach – from simple extrapolation to sophisticated stochastic methods such as ARIMA.
Predictive analytics: Advanced statistical analysis such as panel data models (fixed and random effects models) rely heavily on multi-variate longitudinal datasets. These types of analysis help in business forecasts, identify explanatory variables, or simply help understand associations between features in a dataset.
USER STORY
As a user i want to use data that i have selected from data source/tags so that i can see:
ACCEPTANCE CRITERIA
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