06-20-2025, 05:05 AM
Lowering memory costs in Power BI datasets is important for their functionality, improving refresh times, and being within capacity limits - particularly in large models. One of the best methods is to lower column count by taking away data. Also to lower row count, use the correct data type (integers versus text) which will help with overall memory cost.
During Power Bi Classes in Pune students will learn to optimize data models using best practice star schema design, avoid using a calculated column when it is possible to replace it with a DAX measure. This not only reduces memory footprint but improves report efficiency and maintainability.
The full Power Bi Course in Pune covers advanced techniques like, summarizing data before loading, using aggregations, and filtering relevant and clean data through the source in Power query. Only bringing the relevant and clean data into the model and controlling when it can be used is another way to manage memory costs.
Individuals taking the Power Bi Training in Pune will also gain hands-on experience demoing VertiPaq Analyzer and DAX Studio to monitor and manage dataset size. Training prepares professionals to build enterprise-class scalable high-performance models suitable for reporting environments.
During Power Bi Classes in Pune students will learn to optimize data models using best practice star schema design, avoid using a calculated column when it is possible to replace it with a DAX measure. This not only reduces memory footprint but improves report efficiency and maintainability.
The full Power Bi Course in Pune covers advanced techniques like, summarizing data before loading, using aggregations, and filtering relevant and clean data through the source in Power query. Only bringing the relevant and clean data into the model and controlling when it can be used is another way to manage memory costs.
Individuals taking the Power Bi Training in Pune will also gain hands-on experience demoing VertiPaq Analyzer and DAX Studio to monitor and manage dataset size. Training prepares professionals to build enterprise-class scalable high-performance models suitable for reporting environments.