Connect Snowflake from Rakam

With the native integration with Snowflake, you can model your data and build up analytical interfaces for end-users.

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.

Recipes

Segment Google Adwords
Segment Facebook Ads
Segment Mobile Analytics
Segment User Attribution
Segment Pageview Analytics
Segment Event Analytics

It provides marketing reports for your Adwords destinations

Dashboards

Google Adwords

Total Spend measures cost in adwords ad performance reports model

Total Clicks measures clicks in adwords ad performance reports model

Interactions measures interactions in adwords ad performance reports model

Average Time On Site measures average time on site in adwords ad performance reports model

Funnel measures impressionsinteractionsconversions in adwords ad performance reports model

Average Bounce Rate measures average bounce rate in adwords ad performance reports model

Engagements measures engagements in adwords ad performance reports model

Campaign Performance measures costconversions in adwords ad performance reports model grouped by campaign name

Active Ads Count measures total ads in adwords ad performance reports model grouped by is active

Models

adwords_ads points to database.schema.ads table

Measures: total ads

Dimensions: typestatusfinal urlsis activeoriginal idadwords customer id

Join Relations: adwords ad groups.ad_group_id is equal to id column

adwords_campaigns points to database.schema.campaigns table

Dimensions: end dateserving statusnamestatusstart dateadwords customer id

Adwords Click Performance points to database.schema.click_performance_reports table

Includes stats at the click level, including both valid and invalid clicks.

Measures: page shown

Dimensions: ad network type 2ad formatad network type 1creative iddeviceslotidgcl idcampaign iddateclick typepagecriteria parametersaoi most specific target id

Join Relations: adwords campaigns.campaign_id is equal to id columnadwords ad groups.ad_group_id is equal to id column

Adwords Campaign Performance points to database.schema.campaign_performance_reports table

Includes a daily snapshot of performance statistics per campaign.

Measures: invalid clicksvideo quartile 100 rateinteractionstotal video viewsviewabilitybudgetengagementsgmail savesaverage bounce rateclick assisted conversionsgmail forwardsaverage time on sitevideo quartile 50 ratecostvideo view rateclicksaverage video view rategmail secondary clicksconversion valueimpressionsconversions

Dimensions: interaction typesbase campaign idadvertising channel sub typecampaign statusdatecampaign trial type

Join Relations: base adwords campaign.base_campaign_id is equal to id columnadwords campaigns.campaign_id is equal to id column

Adwords Ads defined as sql

Dimensions: account descriptive nameaccount currency codeinteraction typesad group namead namecampaign namedate

Join Relations: adwords ads.ad_id is equal to id column

adwords_ad_groups points to database.schema.ad_groups table

Dimensions: statusnameadwords customer id

Join Relations: adwords campaigns.campaign_id is equal to id column

It provides marketing reports for your Facebook destinations

Dashboards

Facebook Ads

Average Frequency measures frequency in facebook insights model

Total Impressions measures impressions in facebook insights model

Campaign Performance measures total spendclicksimpressionsclick through rate in facebook insights model grouped by name

Total Spend measures total spend in facebook insights model

Total Clicks measures clicks in facebook insights model

Total Reach measures reach in facebook insights model

Click Through Rate measures click through rate in facebook insights model

Impressions by campaign type measures impressions in facebook insights model grouped by buying type

Models

facebook_ads points to database.schema.ads table

Dimensions: bid typestatusnameis active

Join Relations: facebook ad accounts.account_id is equal to id columnfacebook campaigns.campaign_id is equal to id columnfacebook ad sets.adset_id is equal to id column

facebook_campaigns points to database.schema.campaigns table

Dimensions: effective statusnamedateis activebuying type

facebook_ad_sets points to database.schema.ad_sets table

Dimensions: effective statusconfigured statusnameis activeend time

Join Relations: facebook ad accounts.account_id is equal to id columnfacebook campaigns.campaign_id is equal to id column

Facebook Ads defined as sql

Measures: total spendfrequencypost engagementsclicksimpressionssocial spendlink clicksclick through ratereach

Dimensions: ad group namead namecampaign namedate

Join Relations: facebook ad accounts.account_id is equal to id columnfacebook campaigns.campaign_id is equal to id columnfacebook ads.ad_id is equal to id columnfacebook ad sets.adset_id is equal to id column

facebook_ad_accounts points to database.schema.ad_accounts table

Measures: balancespend cap

Dimensions: name

It implements screen event for Segment Warehouse in order to track user actions on Android & iOS.

Dashboards

Mobile Overview

Devices measures total events in screens model grouped by context device type

Events by Mobile Applications measures total events in screens model grouped by context app name

Total Users measures unique users in screens model

Total Devices measures unique devices in screens model

Operating System Breakdown measures unique users in screens model grouped by context os name

Manufacturer measures unique users in screens model grouped by context device manufacturer

Network Carrier Breakdown measures unique users in screens model grouped by context network carrier

Device Type Breakdown measures unique users in screens model grouped by context device type

Models

[Segment] Mobile Screen points to database.schema.table table

A model with all of your screen method calls. This table will include all of the properties you record for screens as top-level columns, for example <source>.screens.title.

Measures: total eventsunique usersunique devices

Dimensions: context timezonereceived atcontext app namespacesent atcontext device tokencontext app namecontext library versionidcontext app versioncontext os namecontext screen heightcontext device advertising idcontext device manufactureroriginal timestamptimestampcontext device typecontext network cellularUser Ipcolumncontext device modeluser idcontext device ad tracking enabledcontext app buildcontext network carriercontext library namecontext network wificontext screen widthanonymous id

It provides user attribution analytics for Segment Warehouse

Dashboards

Users Overview

Total Attributions measures total identify in identifies model grouped by received at

7-Day Active Users measures total users in segment users model

By Device measures total users in segment users model grouped by context device type

Total Users measures total users in segment users model

30-day Active Users measures total users in segment users model

Models

Attributions points to database.schema.table table

Measures: Total Updatedistinct users

Dimensions: Dateidcolumn

All Segment Users points to database.schema.table table

Measures: total users

Dimensions: columnlast updateuser id

It provides session and pageview analytics for Segment Warehouse. For Segment Warehouse users, it provides basic reports similar to Google Analytics

Dashboards

No dashboards defined.

Models

[Segment] Pageview Sessions points to database.schema.table table

Website session information for the pageview event

Measures: Bounce RateAverage Session Per UserDistinct UsersTotal SessionsPages Per SessionAverage DurationNew SessionsReturning Sessions

Dimensions: utm mediumlast pathlast urlutm sourcefirst page url pathfirst page urlsession end tstamplast searchpage viewsreferrer hostsession idsession numberdevice categorysession start tstampdeviceduration in s tierutm campaignduration in sreferrerutm contentfirst page url query

[Segment] Pageview points to database.schema.table table

The pageview data that's collected via Segment Javascript SDK

Measures: Total Pageviews

Dimensions: received atpage referrer hostCampaign Sourcedevicecontext page pathsent atuser idSegment Library Versioncontext page searchCampaign MediumCampaign Nameidcontext user agentdevice categorycontext page referreroriginal timestampgclidtimestampcontext page urlPage Search ParameterUser Ippage url hostPage PathPage URLreferrercontext page titleSegment Library Nameanonymous idPage TitleCampaign Content

Join Relations: user.user_id is equal to id columnsession.anonymous_id is equal to anonymous_id column

It implements screen event for Segment Warehouse in order to track user actions on Android & iOS.

Dashboards

Events Overview

Events by Last Seen App Version measures context app version in tracks model grouped by event text

Top Events measures total events in tracks model grouped by event text

Top Events by Unique Users measures unique users in tracks model grouped by event text

Total Events measures total events in tracks model

Total Users measures unique users in tracks model

Total Devices measures unique devices in tracks model

Models

[Segment] All Events points to database.schema.table table

A table with all of your track method calls. This model will only include a few standardized properties that are all common to all events: anonymous_id, context_*, event, event_text, received_at, sent_at, and user_id. This is because every event that you send to Segment has completely different properties. For querying by the custom properties, use the event type models instead.

Measures: Platformstotal eventsLast Seen App Versionunique usersunique devices

Dimensions: received atidevent textUser Ipsent atSegment Library Nameanonymous idoriginal timestamptimestampSegment Library Versionuser id

Join Relations: user.user_id is equal to id column

WHY Rakam?

You don't have to write SQL for every report.

You might be familiar with SQL but not all the people are. We have a data modeling language that lets you model your data once and build up analytical interfaces that can answer complex questions.

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