“How Analysts Translate Messy Data, DAX, and Dashboards into Action Using Power BI”

Source: Dev.to

Limit the Number of Visuals

• Reducing the number of visuals cuts the amount of data that must be fetched and displayed at once.
• Consider Power BI’s card visual, which can display multiple cards within a single container. This consolidates information into a single query, improves report performance, and minimizes the number of queries fired.

Choose the Right Data Gateway

• Use on‑premises data gateway (standard mode) instead of personal mode.

  • Standard mode does not import data into Power BI, making it more efficient.
  • It minimizes data duplication, reduces memory usage, and avoids potential performance bottlenecks.

• Separate gateways for live connections and scheduled refreshes.

  • Isolating these functions ensures each can operate efficiently without affecting the other.

Optimise Data Modelling

• Push calculations to the source and use calculated measures and filters to limit complex measures and aggregations in the model.
• Prefer a star schema over a snowflake schema when possible.
  • The star schema accelerates query execution, eases maintenance by reducing required joins, improves query efficiency, reduces data redundancy, and simplifies report development.
• Use calculation groups to reduce redundant measures.

Visual Design Best Practices

• Use slicers sparingly to avoid unnecessary query load.
• Host reports and data sources in the same region.
  • This minimizes network latency, enabling quicker data transfer, faster query execution, and faster report rendering.

Data Partitioning and Loading

• Partition large semantic models and process multiple partitions in parallel.
  • Power BI’s columnar indexes perform better with longer, leaner tables.
  • Import only the necessary fields and tables, which improves data loading efficiency, reduces resource consumption, and leads to faster report performance.