Organizations that are performing usage analytics on their own BI analytics platform make better progress towards establishing a data-driven culture. This is because they are able to measure factors such as content usage, features and functionality usage, and which business teams are avid users of the platform. Additionally, they can pinpoint potential power users who can be recruited to help with support and training. Finally, alert the analytics team to potentially broken data pipelines or potential errors. All of this information is critical in establishing a data-driven culture within an organization.
Content usage
Features and functionality usage
Which business teams are avid users of the platform and which teams may need additional training or support to fully embrace it
Help identify potential power users who can be recruited to help with support and training
Alert the analytics team to potentially broken data pipelines or system/process errors
The tool uses advanced events capture capability and streaming event processing to get real-time insights into the health of your BI platform and usage stats.
There are a few different ways that you can go about performing usage pattern analytics. One way is to use a tool such as the Xplora.ai CDAO Dashboard. This tool is specifically designed for measuring a company’s level of BI usage and maturity. Another way is to manually collect data from your BI platform and analyze it yourself. However, this can be time-consuming and may not give you as accurate of results as using a tool like the Xplora.ai CDAO Dashboard.
It is important for organizations to perform usage pattern analytics on their own BI analytics platform in order to establish a data-driven culture. This valuable information will help the leadership team make informed decisions about their data analytics strategy and ensure that their organization is getting the most out of their investment in data analytics. Contact us today to learn more about the Xplora.ai CDAO Dashboard and how it can benefit your organization.