Businesses use forecasting extensively to make predictions such as demand, capacity, budgets and revenue. Among these different forecasting models identifying seasonal patterns in data can go a long way by providing seasonal insights to the business decision makers so that they can strategist for seasonal effects.

1. Time Series Analysis/ Forecasting
Samudra Kanankearachchi
Senior Software Architect @99XTechnology
Data Science Specialist

3. State of variable is
correlated to it self
t
t - 1
t + 1

4. Common time series patterns

5. Example Use Case (Banking Industry)

7. 1

8. 2

11. Stationarity / Differencing (None Stationary)
Importance of managing time series
Poor Indicators
Uncontrolled Positive or Negative Trends
Unhealthy Variation
Positive /Negative long runs away from the
mean
…

12. Hands on Demos
Modeling / Training
and Forecasting
Demonstrations

13. Demo

14. Time series Decomposition (Demo)
Demo

15. Time series Prediction Modeling (Demo)
Time Series Data Model
HoltWinters (Algorithm)
Perdition Model )
Perditions
Demo

16. Moving Average Base forecasting (Demo)
Demo

17. Thank You