If you're using a platform that connects to many analytics tools and helps you get tracking up and running quickly, Avo is a good option. Avo has a full set of tools for event data quality, including data observability, monitoring, and collaborative schema management. It connects to common analytics tools like Amplitude, Google Analytics and Segment, and offers tools like Avo Inspector for data quality problems and branched workflows for collaboration. That can speed up data quality work and lower development costs.
Another powerful option is Metaplane, a data observability platform that automates end-to-end data monitoring. Metaplane offers ML-based monitoring, column-level lineage and real-time schema change alerts, which can help you quickly identify and troubleshoot data issues. It also connects to many modern data stack tools, which can dramatically reduce the time spent on data quality issues and increase data trust.
If you want a more collaborative data analysis approach, Airbook is a collaborative data workspace that connects to more than 150 data sources and lets you query it with SQL, Python and no-code interfaces. It has features like query saving, visualization and version control, so it's good for a variety of analytics tasks from marketing to financial analytics. Its broad range of integrations, including Google Analytics and Amazon Redshift, means it can handle a lot of use cases.