In this section, we cover the best practice approach to optimizing the performance of your dashboards and reports.

Ensuring the performance of your dashboards and reports is critical to ensure a great user experience. As part of any analytics project, you should spend time to optimize your data environment and analytic content to meet the anticipated workload of end-users. Failure to do so will lead to low user adoption.

The performance of your reports and dashboards is directly linked to the performance of your: 

1. Hardware

2. Database

3. Data model  

4. Data Volume 

5. Metadata layer 

6. Report / Visualization construction; and 

7. Dashboard Design

You can optimize each of these areas to ensure your end-users have the level of query performance they need to be able to analyze their data in an efficient and frustration-free manner.

<insert image – layers of performance management – needs to be designed>

One of the most common causes of slow performance is not having an environment that is optimized for analytical workloads. This includes the infrastructure upon which you deploy, as well as the databases you are using to report from.

Assuming your data environment is well designed, there is a lot you can and should do to optimize your content to ensure fast reports and dashboards. We break this down into 4 steps.