5 Key Considerations to Get the Most Out of Your Data with Digital Analytics Platforms

Many organizations struggle to get a comprehensive view of their data. In fact, cited managing data across silos as a challenge affecting data analysis capabilities.

Between in-house and third-party solutions, the average business is typically importing and exporting data to a range of customer data platforms, marketing software, social media platforms, ad networks, attribution sources, and data warehouses. This infrastructure tends to be siloed and naturally evolves over time—making data management costly and complex.

To make life easier, choose a digital analytics solution that fits your overall tech stack and allows data to be easily imported and exported across your environment. Look for solutions that provide SDKs and pre-built connections to help with data ingestion, streaming to other parts of your stack, and data export to centralized data lakes or lake houses.

Your data analytics platform should also accommodate and complement your overall data strategy, whether this means centralizing your data into a single warehouse or implementing a decentralized data mesh architecture. Having a solution that flexibly meets and scales with your organization's needs is key.