How can you ensure your BI solution provides trend analysis?

2 Define clear and relevant KPIs

Key performance indicators (KPIs) are the metrics that measure your progress and performance against your strategic objectives. To ensure your BI solution provides trend analysis that is meaningful and actionable, you need to define clear and relevant KPIs that align with your business goals and reflect your data quality and availability. For example, if you want to analyze the trend of customer satisfaction, you need to have a reliable and consistent way to collect and measure customer feedback, as well as a clear definition of what constitutes satisfaction. You also need to ensure your KPIs are SMART: specific, measurable, achievable, relevant, and time-bound.

4 Apply data transformation and analysis methods

Data transformation and analysis are the processes of manipulating and processing your data to extract insights and information. Data transformation and analysis can help you improve your data quality, accuracy, and consistency, as well as enhance your data analysis capabilities and outcomes. However, not all data transformation and analysis methods are suitable for trend analysis. You need to apply data transformation and analysis methods that match your data characteristics, assumptions, and limitations, as well as your analytical goals and questions. For example, if you want to analyze the trend of revenue growth, you may need to apply data transformation methods such as normalization, standardization, or logarithmic transformation, as well as data analysis methods such as regression, correlation, or forecasting.

5 Validate and verify your results

Validation and verification are the processes of checking and confirming your results and conclusions. Validation and verification can help you ensure your BI solution provides trend analysis that is reliable, valid, and robust, as well as avoid errors, biases, and misinterpretations. However, not all validation and verification methods are suitable for trend analysis. You need to validate and verify your results using appropriate methods that match your data quality, reliability, and variability, as well as your analytical assumptions, models, and hypotheses. For example, if you want to validate and verify your trend analysis results, you may need to use methods such as cross-validation, sensitivity analysis, or hypothesis testing.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?