To maximize the value of your analytical data models, it's essential to ensure that they can be easily and effectively consumed by business users through your BI tool. In Luzmo, several strategies can help streamline this process, enabling users to generate insights with minimal technical barriers. Below are some key tips to enhance data consumption in Luzmo.
Denormalized views simplify the data structure by flattening it into a more accessible format, empowering business users to create dashboards and reports efficiently in BI tools like Luzmo. This approach reduces the need for complex joins, allowing less technical dashboard designers to work with the data without needing in-depth knowledge of where specific data resides. You can create these denormalized views in your data source, or use the SQL datasets functionality in Luzmo to define them on the fly!
In Luzmo, you can optimize your datasets to align with the specific needs of your users. Enhance usability and ensures consistency across dashboards by preconfiguring aspects such as date-time columns, currency, duration, coordinates, and default formatting. Additionally, setting up translations for column names and data values can cater to a multilingual user base, improving accessibility and user experience. By tailoring these configurations, you reduce the setup time for dashboard designers, and enable more accurate and intuitive visualizations.
Complex business logic often requires specific formulas to calculate metrics accurately. By pre-creating these aggregation formulas in your dataset, you ensure that the desired insights are consistently defined and can be easily implemented in widgets. This not only standardizes calculations across reports but also reduces the need for users to create or understand complex formulas, thereby minimizing errors and saving time. This Academy article contains more information and examples around creating Formulas.
To ensure your organization's Luzmo users can gain full benefit of your tweaked datasets, you should make sure to share them with the other users who should be able to query those. In this Academy article you'll find more recommendations on how to share your datasets in Luzmo!
For datasets that are frequently accessed but don’t change often, enabling query caching can significantly improve performance of identical queries. Cached data reduces the load on your data sources and speeds up data visualizations in Luzmo, making the user experience smoother when dealing with large datasets. It’s essential to balance the cache settings to ensure data freshness while optimizing performance. More details can be found in this Academy article.
Luzmo's WARP feature allows you to periodically synchronize the data from your source into Luzmo's analytical data storage layer. This is useful when your data source is not able to performantly handle the typical analytical load of customer-facing analytics. More information about WARP is available in this Academy article.
Now that your datasets are ready to be consumed, the last article will guide you in gracefully handling future updates to your data model.