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General guidelines for optimizing the performance of a project
Follow these guidelines to ensure optimal performance of your project, increasing the overall user experience for both admins and report users. This is crucial for large and complex projects, i.e. a tracker with several years of data, but several of the below listed points should be considered vital in any project.
General Connectivity and Network Speed
Internet Speed: The user's download and upload speeds can significantly impact loading times.
Network Latency: The time it takes for data to travel from the user to the server and back.
Bandwidth Limitations: Restrictions on the amount of data that can be transmitted over the network, for instance congested office networks can have a dramatic effect.
Number of Objects
Visual Elements: More data objects will increase loading times.
Data Points: Larger data sets require more time to process and render. This also includes computed variables. Large complex computes could have a negative impact on data activation times.
Dashboard Design: The number of objects can often be reduced. For example, through the use of smart table layout options to reduce the number of data objects for the same result
In-Memory Loading and Caching
Preloaded Data: The pregen logic aids loading times when viewing the same data over and over.
Data Caching: Ensuring metadata and report settings caching is enabled.
In-memory: Should always be utilized
Refer to How Can Performance Be Increased for more information.
Custom JavaScript (CC)
Script Optimization: Well-optimized scripts can run faster and reduce load times.
Minification: Reducing the size of JavaScript files by removing unnecessary characters.
User -Side Performance
Browser Performance: Different browsers and their versions can affect loading times.
Device Specifications: The user's hardware (CPU, RAM) can impact how quickly data is processed and rendered.
Import frequency and Data Activations
Running large scheduled imports and data activations could potentially affect the overall performance of a project. Uploading large files and/or complex calculations (i.e. computed variables or data recoding), it is optimal to reduce the import frequency and schedule imports to outside office hours if possible.
Large Projects with Historical data House-keeping
Large long-time running projects (i.e. 3+ years) will grow heavier over time, which will affect import and data activation times but could also have an impact on general project maintenance work and end-user experience.
Guidelines:
Clean away data older than what is possible to see in the project
Clean away data that is no longer relevant / users are not really interested in
Split the project and store historical data (i.e. older than 2 years) in a separate project, if possible