You model your data once and unlock
marketing, product and business teams.

Once the data analyst model your data,

The non-technical people will see the similar interfaces to run queries on data easily:

Segmentation
for product managers
Event metrics and Transactional Data

Drill-down and pivot your data in order to understand how to data distributes.
SELECT
                        
      CAST(DATE_TRUNC('week', "install_date") AS DATE) ,   
      "apps"."name" AS "name",
      sum("iap_revenue") AS "Revenue"
  FROM
     "tenjin"."reporting_cohort_metrics"
  LEFT JOIN
       "tenjin"."apps" AS "apps"
          ON
          (
              "reporting_cohort_metrics"."app_id" = "apps"."id"
       )
  WHERE(
          "apps"."platform" = 'ios'
        )
      AND(
          "install_date" BETWEEN '2019-10-30' AND '2019-11-13'
          )
  GROUP BY
      1,
      2
  ORDER BY
      1 DESC

Compiles to this SQL query

The UI above compiles this SQL query. Hover the SQL in order to see the details.

P.S: The users can export the SQL query whenever they want and customize it later on.

Funnel
for product managers
Event Analytics

See how your users are using your app
Retention
for product managers
Event Analytics

See how your users churning from your app
Features for

End-users

Data Catalog with Models

With label, category, and description, you can make the data access much more easy and seamless.

Customizable for Your Use-case

The analysts can make the charts and tables interactive by adding actions to your model definitions.

Dashboards for Sharing Insights

You can add the reports to your dashboard, make them dynamic with filters and customize the layout as you wish.

Looking for a way to embed the models into your app?

Schedule a call

Features for

Data analysts & engineers

Jinja Templates for Dynamic Models

You can use Jinja templating engine in order to build dynamic models. It helps you to JOIN, UNION data different data-sets easily, use macros that can be used in multiple models.

Embedded Materialization with DBT

You can use embedded DBT models if you need models that will persist to your database periodically. We also allow you to export the models as a DBT project later on and sync DBT projects externally once your project scales.

Integration with GIT with Recipes

You can develop your models via Jsonnet and push it to GIT and sync them in Rakam without any extra work. Build composable recipes with programmable analytics.

Looking for a way to collect customer event data into your data-warehouse?

Learn more about Rakam API

Ready for a demo?

You can see an example project with dummy data and play with it.