Narrator

Narrator is a data analytics platform that, according to the vendor, aims to empower analysts in answering questions more efficiently. The platform offers advanced processing tools to address common data processing problems such as identity resolution, anomaly detection, and incremental updates. It also provides automatic helper columns, intelligent debuggers, and data checks to ensure data integrity and prevent loss.

According to the vendor, data analysts can leverage Narrator to easily combine modeled data using flexible building blocks called activities. They can handle changes and follow-up questions instantly by swapping activities, redefining connections, or switching columns. The platform allows them to add features without duplication or dropping rows, potentially speeding up their workflows.

For data engineers, Narrator provides the ability to build an Activity Schema using either Narrator or dbt with reusable building blocks. This, according to the vendor, allows analysts to independently add features to their datasets, reducing the need for tickets and maintenance. Everything can be compiled into SQL and easily shared with clear lineage and contained self-service.

The vendor claims that Narrator can improve efficiency and speed for heads of data by providing a data tool that allows unlimited data questions without overwhelming the team. Real-time data modeling enables them to keep up with questions and empower stakeholders to handle their own follow-up questions. By building efficient teams that work together, they can deliver easy-to-understand data stories.

With Narrator, users can generate queries and send data to Excel or Google Sheets for quick analysis. They can interpret the data, add context, or create full reports with impact analyses, A/B tests, and funnels. The platform also allows data manipulation and pushing to production, with transparent and editable SQL queries, as claimed by the vendor.

According to the vendor, Narrator offers flexibility for exploring data, whether starting with existing datasets or creating new ones. Users can validate the data, inspect example customers, or delve into metrics to better understand the data. They can easily slice and dice the data, change their mind, add more features, or create new aggregations without any hassle.