Perform rapid analysis of your app platform data

With Fivetran’s new App Reporting data model, you can easily roll your Apple App Store and Google Play data into a unified schema for seamless reporting.

App platform source data is notorious for highly normalized data spanning tens of tables, requiring data teams (such as data analysts, analytics engineers or data scientists) to possess a fair amount of knowledge about the data before transforming it across sources.

As a result, it’s challenging to quickly gauge app performance or pinpoint the pain points. Not to mention, spotting growth opportunities is more challenging than it ought to be.

Instead of spending time writing join logic between tables while also tracking complex queries—you can now use Fivetran's App Reporting data models to do that and more. The App Reporting data models allow the aggregation and modeling of data using Fivetran’s pre-built connectors for Google Play and Apple App Store. 

With App Reporting, you can standardize the schemas from the various app platform connectors and create reporting models for all activity aggregated daily and by app along the following dimensions:

  • Country
  • OS version
  • App version
  • Traffic source
  • Device

The data model also includes a data dictionary and model lineage graph for customer references. 

To further optimize your analytics practice, leverage Fivetran Transformations for dbt Core to centralize your end-to-end managed ELT pipelines into one platform.

With integrated scheduling, available as of February 2022, your app reporting data model only runs upon the completion of your connector syncs, ensuring your end models are accurately generated with the most up-to-date data.

Find more information about Fivetran App Reporting on this page.

Kostenlos starten

Schließen auch Sie sich den Tausenden von Unternehmen an, die ihre Daten mithilfe von Fivetran zentralisieren und transformieren.

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Perform rapid analysis of your app platform data

Perform rapid analysis of your app platform data

June 1, 2022
June 1, 2022
Perform rapid analysis of your app platform data
With Fivetran’s new App Reporting data model, you can easily roll your Apple App Store and Google Play data into a unified schema for seamless reporting.

App platform source data is notorious for highly normalized data spanning tens of tables, requiring data teams (such as data analysts, analytics engineers or data scientists) to possess a fair amount of knowledge about the data before transforming it across sources.

As a result, it’s challenging to quickly gauge app performance or pinpoint the pain points. Not to mention, spotting growth opportunities is more challenging than it ought to be.

Instead of spending time writing join logic between tables while also tracking complex queries—you can now use Fivetran's App Reporting data models to do that and more. The App Reporting data models allow the aggregation and modeling of data using Fivetran’s pre-built connectors for Google Play and Apple App Store. 

With App Reporting, you can standardize the schemas from the various app platform connectors and create reporting models for all activity aggregated daily and by app along the following dimensions:

  • Country
  • OS version
  • App version
  • Traffic source
  • Device

The data model also includes a data dictionary and model lineage graph for customer references. 

To further optimize your analytics practice, leverage Fivetran Transformations for dbt Core to centralize your end-to-end managed ELT pipelines into one platform.

With integrated scheduling, available as of February 2022, your app reporting data model only runs upon the completion of your connector syncs, ensuring your end models are accurately generated with the most up-to-date data.

Find more information about Fivetran App Reporting on this page.

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Schließen auch Sie sich den Tausenden von Unternehmen an, die ihre Daten mithilfe von Fivetran zentralisieren und transformieren.

Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.