How to Address Slow Loading Speeds in Looker Studio

Google Looker Studio (formerly Google Data Studio) is a fantastic tool for creating interactive dashboards. However, as dashboards become more complex, you may encounter slower loading speeds. A sluggish dashboard can hinder productivity and frustrate users, especially when timely insights are crucial.

In this blog, we’ll explore the key reasons behind slow loading speeds in Looker Studio and provide practical solutions to ensure your dashboards are fast, efficient, and responsive.

Why Do Dashboards in Looker Studio Load Slowly?

1. Large Data Sets

   • Pulling millions of rows or columns directly into Looker Studio can overwhelm the tool and increase processing time.

2. Complex Calculations

   • Using calculated fields or performing transformations in Looker Studio requires real-time computation, which can slow down performance.

3. Unfiltered Data

   • Querying raw, unfiltered data increases the load Looker Studio has to handle, leading to longer rendering times.

4. Too Many Visualizations

   • Each chart, graph, or table requires separate data queries, so dashboards with multiple visualizations can take longer to load.

5. Frequent Data Refreshes

   • Real-time or excessively frequent refresh intervals put additional strain on the system and may result in delays.

6. High Network Dependency

   • Dashboards rely on stable internet connections to fetch data. Slow or unreliable networks can exacerbate loading issues.

Solutions to Improve Looker Studio Loading Speeds

1. Optimize Your Data Source

Filter Data at the Source

• Apply filters directly in your data source to limit the data sent to Looker Studio.

• Example: If your dashboard focuses on the last 30 days, filter the data source to exclude older records.

Aggregate Data

• Aggregate data (e.g., sum, average) at the source to reduce the volume Looker Studio needs to process.

• Example: Instead of pulling raw transaction data, calculate daily totals beforehand.

Limit Dimensions and Metrics

• Only bring in the dimensions and metrics you need for analysis. Unused fields consume resources unnecessarily.

2. Use Extracted Data Sources

What Are Extracted Data Sources?

• Extracted data sources allow you to create a static snapshot of your data within Looker Studio. This eliminates the need for live queries to the original source.

Benefits:

• Faster loading times, as the data is preloaded.

• Reduced dependency on real-time connections.

How to Use It:

1. In Looker Studio, select your data source and create an extracted data source.

2. Define the fields and date range you want to extract.

3. Schedule regular updates (e.g., daily or weekly) to keep the data current.

3. Simplify Your Dashboard Design

Limit the Number of Visualizations

• Reduce the number of charts, graphs, and tables on each page. Use tabs or separate pages to organize your data effectively.

• Example: Instead of 10 visualizations on one page, split them into 2 pages with 5 visualizations each.

Optimize Filters

• Use fewer filters and avoid applying filters across all visualizations unless necessary. Global filters should be sparingly used for key dimensions like date ranges.

Avoid Overlapping Queries

• Ensure charts don’t redundantly query the same data. Consolidate visualizations where possible.

4. Perform Calculations Outside Looker Studio

Pre-Calculate Metrics

• Perform complex calculations in your database or data source instead of using Looker Studio’s calculated fields.

• Example: Instead of calculating “Revenue per User” in Looker Studio, compute it in your database and bring it in as a pre-defined metric.

Use Aggregated Tables

• Create pre-aggregated tables in your database for commonly used metrics, reducing the need for on-the-fly calculations.

5. Optimize Refresh Frequency

Adjust Update Intervals

• Avoid real-time updates unless absolutely necessary. For most use cases, daily or hourly refreshes are sufficient.

Schedule Updates During Off-Peak Hours

• For large datasets, schedule data refreshes during times of low activity to avoid overloading the system.

6. Improve Query Efficiency

Write Optimized Queries

• Use SQL to optimize queries before the data reaches Looker Studio.

• Example: Use indexed columns and efficient JOIN operations to speed up database queries.

Limit Rows Returned

• Use LIMIT statements in your SQL queries to restrict the number of rows returned, especially during initial testing or prototyping.

7. Ensure Network Stability

Use a Reliable Internet Connection

• A stable, high-speed internet connection minimizes latency and ensures data loads faster.

Monitor Network Traffic

• Check for other applications consuming bandwidth and prioritize your dashboard’s connection during critical times.

Quick Optimization Checklist

•  Apply filters at the data source to reduce unnecessary data.

•  Use extracted data sources for static snapshots.

•  Pre-calculate metrics and aggregate data at the source.

•  Limit the number of visualizations per page.

•  Adjust data refresh intervals to suit your needs.

•  Write optimized SQL queries to fetch only relevant data.

•  Test dashboards on a stable, high-speed network.

Conclusion

Slow loading speeds in Looker Studio can be a frustrating bottleneck, but they’re often caused by inefficiencies in data management and dashboard design. By filtering and aggregating data at the source, simplifying visualizations, and leveraging extracted data sources, you can create dashboards that are not only fast but also highly functional and user-friendly.

At Gyekz, we specialize in creating optimized dashboards tailored to your business needs. Contact us today to unlock the full potential of Looker Studio and deliver insights faster than ever!