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Expected Segment data

Here’s a sample of the raw Segment data that Stitch will replicate to your analytics warehouse:


This table records all user information.

Table name: identify


This table records all event information.

Table name: track


This table records page events, along with any information about page properties.

Table name: page


This table records screen events, along with any information about screen properties.

Table name: screen


This table records group information, including traits and all additional properties.

Table name: group

View all tables

Learn more about syncing Segment data


Detailed documentation on how to start syncing Segment data.

Segment Documentation

Jumpstart your Segment analytics with reusable blocks

dbt packages can speed up your work

Once you replicate your Segment data with Stitch, you can use it in many ways. For example, you can use the data modeling and transformation tool dbt to prepare data for reporting, analytics, or machine learning applications.

Dbt has prebuilt packages for many Stitch data sources, including Segment. Here’s a look at code for modeling Segment data. This particular block of code quickly cleans your Segment data and categorizes your web page views.

View the source on GitHub →
                            {% macro segment_web_page_views() %}
    {{ adapter_macro('segment.segment_web_page_views') }}
{% endmacro %}
{% macro default__segment_web_page_views() %}
with source as (
    select * from {{var('segment_page_views_table')}}
renamed as (
        id as page_view_id,
        received_at as received_at_tstamp,
        sent_at as sent_at_tstamp,
        timestamp as tstamp,
        url as page_url,
        {{ dbt_utils.get_url_host('url') }} as page_url_host,
        path as page_url_path,
        title as page_title,
        search as page_url_query,
        {{ dbt_utils.get_url_host('referrer') }} as referrer_host,
        context_campaign_source as utm_source,
        context_campaign_medium as utm_medium,
        context_campaign_name as utm_campaign,
        context_campaign_term as utm_term,
        context_campaign_content as utm_content,
        {{ dbt_utils.get_url_parameter('url', 'gclid') }} as gclid,
        context_ip as ip,
        context_user_agent as user_agent,
            when lower(context_user_agent) like '%android%' then 'Android'
            else replace(
                {{ dbt_utils.split_part(dbt_utils.split_part('context_user_agent', "'('", 2), "' '", 1) }},
                ';', '')
        end as device
        {% if var('segment_pass_through_columns') != [] %}
        {{ var('segment_pass_through_columns') | join (", ")}}
        {% endif %}
    from source
final as (
            when device = 'iPhone' then 'iPhone'
            when device = 'Android' then 'Android'
            when device in ('iPad', 'iPod') then 'Tablet'
            when device in ('Windows', 'Macintosh', 'X11') then 'Desktop'
            else 'Uncategorized'
        end as device_category
    from renamed
select * from final
{% endmacro %}

Simplify your PostgreSQL migration

When it comes to replicating your data to PostgreSQL, conventional ETL is no longer the only game in town.

Writing ETL code requires big investments of time, money, and expertise that might otherwise be used for innovation. Most importantly, newer approaches to data ingestion deliver faster implementation than traditional ETL, so you can produce data analytics and business intelligence more quickly.

This is where Stitch can help.

All your data, where you need it

Give your analysts, data scientists, and other team members the freedom to use the analytics tools of their choice.

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Asset analysis tools
Stitch allowed us to set up a data pipeline within a day. It helped us avoid the hassle of building a data infrastructure team. The quick turnaround time allowed us to gather insights almost near real time.

Ashok Varma

Founder and CEO, ReportGarden

Why our customers choose Stitch

Stitch is a simple, powerful ETL service built for developers. Stitch connects to your first-party data sources – from databases like MongoDB and MySQL, to SaaS tools like Salesforce and Zendesk – and replicates that data to your warehouse. With Stitch, developers can provision data for their internal users in minutes, not weeks.

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Simple setup
Start replicating data in minutes, and never worry about ETL maintenance.
Own your own data infrastructure
Stitch replicates to your warehouse, meaning you’re always in control.
Mature replication engine
Accurate data from any structure, all the time.
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Connect to your ecosystem of data sources

Stitch integrates with leading databases and SaaS products. No API maintenance, ever, while you maintain full control over replication behavior.