Rakam is joining LiveRamp. See the full announcement ->
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Connect rakam, enable ad-hoc analytics

Connect to your data warehouse and run queries efficiently without pulling out or duplicating any data.
rakam doesn't charge you based on the data volume so you can keep growing without worrying about pricing.
Connect your dbt project and define your data models and metrics as code by collaborating with your teams via GIT.
Let your non-technical teams run custom segmentation, funnel, retention and flow queries without the barrier of SQL.

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Powerful ad-hoc reporting features

rakam provides verticalized reporting features for different teams's reporting needs so, your teams are not restricted in a single interface. rakam turns the questions you ask within user interface to SQL while hiding the complexity from the end-users.

How many unique users purchased at least one product in the last two weeks?

Table Image #marketing #finance #product #business #data

What is the conversion rate from rewarded ad watch to purchase?

Funnel 1 Image #marketing #finance #product #business #data

How often do users who watched rewarded ad come back to our app and watch another rewarded ad?

Funnel 2 Image #marketing #finance #product #business #data

What are the common paths that our users take through our application before they make a purchase?

Funnel 2 Image #marketing #finance #product #business #data

How many unique users canceled an order last month?

Funnel 2 Image #data #engineering






Leverage your data warehouse for product analytics, get started now!

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For analytics engineers' favor

rakam connects to your dbt core project. You can transform and document your data with dbt and define your metrics as code with our data modeling tool, Metriql.

rakam doesn't load any data into your data warehouse, it expects you to have all the data inside your data-warehouse and lets you analyze the data without pulling the data outside your data warehouse, the single source of truth. Link to our blog post about the topic.

rakam natively supports dbt core as the data modeling layer. rakam doesn't run your dbt transformations, instead connects to your GIT repository and synchronizes your dbt models automatically.
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rakam can create incremental dbt models, make use of them to speed up your queries and reduce the query costs on your database. When you define aggregates in your dbt resource files, rakam creates roll-up models programmatically hiding the complexity from end-users.
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rakam shines on product data. You can connect it to your raw event data and run complex behavioral analytics queries such as funnel, retention, and path analysis without any compromise on performance.
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Where we share, learn, work together to make a change! Check out the open-source projects we built with our community

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How is rakam different?

BI Tools vs rakam

Traditional BI tools like Tableau and Looker has only one interface for all reporting types and still fails at providing true ad-hoc exploration for non-technical people. rakam offers out of the box reporting features for different types of reporting needs such as segmentation, funnel, retention, flow so your teams can analyze product(event) data using the right interface without technical teams’ help.

TP Product Analytics Tools vs rakam

Third party product analytics tools like Amplitude and Mixpanel only let you analyze the data which has been tracked via their SDKs and loaded into their servers. rakam connects to your data warehouse directly and lets you make use of all your company data in your analysis. While rakam doesn’t ingest or duplicate any of your data into its servers, it also doesn’t charge you based on the data volume.