This documentation is about Rakam BI. If you're looking for the documentation for Rakam API, please click here.
Rakam lets you model your data and analyze it in an ad-hoc manner. You model the data programmatically or use one of the recipes that we provide and analyze the data using the UI without requiring SQL. We aim to provide powerful analytical user interfaces for non-technical people, they slice/dice the data, create complex behavioral reports such as funnel & retention without any need of SQL.
Unlike most of the BI tools, Rakam requires you to model the data in order to be able to analyze it. Even though it has more friction compared to plug/play BI tools, it provides a consistent view across ally the company data inside your organization and allows non-technical people to analyze complex data structures such as event analytics.
The tool consists of the following concepts in this order:
In order to be able to use Rakam, you need to install recipes. Recipes are a set of models & dashboards, you can find the pre-built recipes in our marketplace under the
Develop page. If you want to model the data in your database, you can create a new recipe from scratch using our IDE. Here is how the
Develop page looks like:
If you're a data analyst who's planning to integrate Rakam, you can learn more about the recipes from Recipe Introduction.
Once you install the recipes, you can analyze the data through the models created via recipes. We have different Explores that let you analyze the data for different use-cases without any technical knowledge. Here are the current Explore features that you can use:
Segmentation: If you want to slice/dice the data, you can use segmentation in order to drill-down, filter, and measure values in your models. It's a great way to analyze marketing and financial data and also event metrics if you're analyzing customer event data. A typical segmentation query would be
How many pageviews and unique users do we do we have for the last 2 months grouped by countries? or
What's our total marketing spent compared to ROI grouped by channels?
Funnel: If you're analyzing customer event data, Funnel lets you ask questions such as
How many users completed our user onboarding flow? or "How many users added an item to their basket but didn't make any purchase?"
Retention: If you're analyzing the customer event data, Retention lets you analyze the user churns and their stickiness. You can ask questions such as
Do our users visit our app when they sign-up for the next 2 months from the time they signed up?
SQL: In case the other Explores are not enough for your use-case, you can always write SQL and use the SQL reports in your dashboards or save them along with the other Explores.
If you just want to see the dashboards, created reports, or find out what day is available in Rakam, you can visit boards under the Browse tab. It can be used for data taxonomy and also a way to navigate in between the reports & dashboards through the boards. You can learn more about Boards, Dashboards or Saved Reports if you want to go further.
Updated 17 days ago