Time Series Analysis in Power BI

Starting at USD 39.00
4 hours duration

Learn to analyze data over time with this practical course on Time Series Analysis in Power BI. Work with real datasets & practice common techniques.

Enhance Your Data Analysis Skills with Time-Series Data in Power BI As a seasoned data analyst, you understand the importance of exploring datasets from various perspectives. However, have you ever considered the significance of analyzing data over time? Time is a crucial dimension that impacts every analysis. In our comprehensive Time Series Analysis in Power BI course, you will gain valuable insights into analyzing data over time. Through hands-on exercises, you will work with two diverse datasets and learn essential techniques for time-series analysis. Firstly, you will delve into the Superstoredata, which encompasses Point of Sale (PoS) data across different locations and timeframes. By utilizing various window, period-to-date, and period-over-period functions, you will calculate changes and uncover valuable trends. Furthermore, you will explore financial data from Microsoft (NASDAQ: MSFT) and discover how to forecast future data. This will involve leveraging both built-in and DAX algorithms to make accurate predictions. By the end of this course, you will possess a comprehensive toolkit to effectively analyze time-series data and master the fourth dimension. Elevate your data analysis skills and unlock new insights by enrolling in our Time Series Analysis in Power BI course today.

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DataCamp is an online learning platform that offers interactive courses and tutorials for data science and analytics. It provides a wide range of courses covering topics such as Python, R, SQL, machine learning, data visualization, and more. The platform offers a hands-on learning experience through coding exercises and projects, allowing users to practice and apply their skills in real-world scenarios. DataCamp also offers a personalized learning experience with adaptive learning technology that adjusts the course content based on the user's skill level and progress. It is widely used by individuals, professionals, and organizations to enhance their data science skills and stay up-to-date with the latest trends and technologies in the field.
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