How do you automate and streamline the reporting and analysis of your KPIs with BI software?

I love the acronym SMART! I think I am going to commit it to my lexicon for stakeholders moving forward. The largest conflict in most organization that I have worked with is the fact that although they collect a lot of data, the data is not always relevant to the KPIs that they should be, or even want to, measuring!

Adding other operational data that may impact your KPI is what is needed for analysis and insights. In the example of NPS, does the representative’s tenure impact it positively or negatively? Is it a specific product? A certain subset of your customer base?

AI has the potential to transform the way we measure and track KPIs. With the ability to process vast amounts of data and detect patterns that may not be apparent to humans, AI can provide valuable insights for improving KPIs. For example, AI can be used to predict customer behavior, identify areas for process optimization, and even detect anomalies in financial data. Additionally, AI-powered dashboards and reports can provide real-time updates on KPIs, allowing businesses to make data-driven decisions faster. However, it's important to note that AI is only as good as the data it's trained on, so ensuring the accuracy and completeness of data is still crucial.

Visualizations and dash boarding is where the "art" of analytics comes into play. There is the way the analyst would "like to" present the data and there is the way that the stakeholders "best understand" the data. A seasoned analyst recognizes this nuance and finds a good balance between the two options. At the end of the day, a tool is only as good as how well the end user can utilize it.

Use Databricks for advanced analytics: Databricks is a cloud-based platform for advanced analytics, including machine learning and data engineering. You can use Databricks to perform complex data transformations and calculations that are not possible with Power BI alone. Databricks provides a unified analytics platform that allows you to process large amounts of data and run complex analytics jobs at scale. You can also use Databricks to build machine learning models that can be used to predict future trends and behaviors.