Time Series Analysis and Forecasting Model in Power BI

Learn how to use Power BI for time series exponential smoothing and handle errors using advanced Power Query techniques

What you'll learn
Visualise time series data in Power BI
Apply and manipulate time series exponential smoothing forecast
Transform unstructured data into time series data
Understand time series theory, and the concepts of seasonal and cyclical data
Handle time series forecasting errors using advanced techniques in Power Query
Compare actual values versus forecast values

Requirements
A prior, basic understanding and usage of Power BI is recommended
Prior experience using Power Query or writing M scripts is useful but not required
An interest in stock trading is appreciated but not required
Have Power BI desktop and Microsoft Excel installed

Description
In this course, students will learn about the forecasting models available in Power BI. By understanding how time series exponential smoothing works, students will be able to manipulate the forecast line efficiently for daily, monthly and yearly predictions of univariate data.

As part of the course, students will gain hands-on experience in advanced error handling techniques in Power Query and be able to tune parameters efficiently for cyclical and seasonal datasets.

Who this course is for
Business analysts interested in time series analysis
Finance professionals curious about Power BI and trend analysis
Python developers curious about Power BI and trend analysis
Power BI and Excel users interested in trend analysis
Business professionals curious about Power BI, forecasting and time series analysis

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