Data export refers to transferring data collected through analytics platforms to external systems for further analysis, reporting, or storage. This capability is crucial for businesses seeking to leverage their analytics data beyond the confines of the platform itself.
Companies can typically use two types of data exports:
- Raw data export involves transferring data in its most granular form. This allows analysts to access detailed information about user interactions, enabling in-depth analysis and customized reporting beyond what is available in the analytics platform. For instance, Piwik PRO Analytics Suite allows you to export raw data to platforms like BigQuery, facilitating advanced data processing and analysis.
| Read more: How to use raw data in web analytics |
- Aggregated data export provides summarized information, which is easier to manage and interpret and can be helpful for high-level overviews but lacks the detail necessary for deep analysis. Many analytics platforms offer this export type as a standard feature, allowing users to download reports in formats like CSV for easy sharing and visualization.
Businesses can utilize data export for various purposes:
- Custom reporting: Users can create tailored reports that combine data from different sources, improving the quality of their analysis and decision-making processes.
- Data integration: Exporting data allows companies to merge analytics insights with other platforms or databases, providing a more holistic view of business or marketing performance.
- Long-term storage: By exporting data, organizations can retain historical records beyond the retention limits set by analytics platforms.
- Advanced analysis: Analysts can use exported raw data for machine learning, predictive analytics, and other advanced analytical techniques that require detailed datasets.
