1. Data Model Optimizations: Optimizing the data model is one of the most effective ways to improve the performance of Power BI. This involves reducing the number of columns in tables, using calculated columns instead of measures, and creating relationships between tables. For example, if you have a table of sales data with five columns, you can create a calculated column that combines the data from the five columns into one column. This reduces the amount of data that needs to be processed and can drastically improve performance.
2. Data Compression: Data compression is a great way to reduce the size of data sets, which can help improve performance. Power BI has built-in data compression features, such as column store indexes, which can help reduce the size of data sets.
3. Optimizing Visuals: Optimizing visuals can also help improve the performance of Power BI. This includes reducing the number of columns and measures in visuals, using simpler visuals instead of complex ones, and using appropriate visual filters. For example, if you have a large table of data, you can reduce the number of columns and measures by using a simple bar chart instead of a complex visualization.
4. Query Optimization: Query optimization is another way to improve performance. This involves using appropriate filters and sorting to reduce the amount of data that needs to be processed. For example, if you have a large table of data and only need to analyze a subset of it, you can use a filter to reduce the amount of data that needs to be processed.
5. Caching: Caching is a great way to improve performance in Power BI. This involves storing data in memory so that it can be quickly accessed. Power BI has built-in caching features that can help improve performance.