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Data Analysis and Performance Optimization Flashcards
Microsoft Power BI Data Analyst Flashcards
| Front | Back |
| How can customizing visuals improve performance? | Using tailored visuals reduces rendering complexity and minimizes resource consumption. |
| How can nested DAX measures affect performance? | They can create complex calculations, increasing query time and impacting overall efficiency. |
| How can you improve Power BI report performance? | Use aggregations, optimize DAX formulas, limit visuals per page, and disable unnecessary animations. |
| How can you reduce model size in Power BI? | Optimize column data types, remove unnecessary columns/tables, and use summarizations instead of detailed data. |
| How do measures differ from calculated columns? | Measures are calculations performed on aggregated data, while calculated columns create static values for each row. |
| How do you manage a slow Power BI dashboard? | Analyze query performance, simplify visuals, optimize DAX, and review data model efficiency. |
| How do you reduce filter complexity in Power BI? | Use slicers, well-defined relationships, and fewer calculated filters for faster performance. |
| How does caching improve Power BI performance? | Caching stores query results, reducing the need to fetch the same data repeatedly. |
| How does data modeling affect Power BI performance? | A well-structured data model reduces complexity, improves query performance, and enhances usability. |
| What are calculated columns in Power BI? | Calculated columns add new data to a table based on DAX expressions and row context. |
| What are common causes of high memory usage in Power BI? | Large datasets, complex relationships, high-cardinality columns, and inefficient DAX calculations. |
| What are Power BI aggregations useful for? | Aggregations pre-calculate data at higher levels, reducing query complexity and improving speed. |
| What are the benefits of disabling auto-refresh for visuals? | It prevents unnecessary data queries, improving dashboard loading times. |
| What does parallel loading of visuals in Power BI do? | It speeds up report rendering by loading multiple visuals simultaneously. |
| What is "DirectQuery" mode in Power BI? | DirectQuery keeps data in the source and queries it live, reducing storage but potentially increasing query latency. |
| What is "Import" mode in Power BI? | Import mode loads data into Power BI, enabling faster performance but requiring more memory/storage. |
| What is a "data lake" for Power BI? | A centralized repository for storing structured and unstructured data used for analysis. |
| What is a high-cardinality column? | A column with many unique values, which can increase processing time and memory usage. |
| What is DAX in Power BI? | DAX stands for Data Analysis Expressions and is a formula language used to create custom calculations and aggregations in Power BI. |
| What is table partitioning in Power BI? | Partitioning divides large tables into smaller subsets for optimized querying and processing. |
| What is the difference between a dataflow and a dataset? | A dataflow transforms and prepares data, while a dataset focuses on data ready for reporting. |
| What is the primary purpose of a Power BI gateway? | A gateway is used to access and refresh data sources that reside on-premises. |
| What is the purpose of relationship direction in Power BI? | It determines how filters flow between tables for accurate data analysis. |
| What is the role of column indexing in Power BI? | Indexing speeds up searches and queries by providing a faster path to data retrieval. |
| What Power BI feature allows column-based compression? | Power BI uses VertiPaq, a columnar storage engine for high data compression. |
| What tool checks Power BI report performance? | The Performance Analyzer tracks query duration and visual processing time. |
| Why should you avoid iterators like SUMX for large datasets? | Iterators loop row by row, which can significantly slow down performance for large datasets. |
This deck explores advanced analysis techniques, performance optimization strategies, and troubleshooting common issues in Power BI.