Snowplow Analytics

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Data Connector Description:

Data Connector Type: Event

Data Connector Documentation:

[Snowplow, Snowplow Analytics, is an event tracking platform that allows you to track events across all channels and action the data in real-time. Snowplow uses , trackers, to track your information in whichever language your project is built., Features, Feature Name, Supported, Notes, Capture Deletes, Custom Data, check, Data Blocking, Column Hashing, Re-sync, check, Connector level. Complete historical data., History, API Configurable, check, Priority-first sync, dbt Package, Supported trackers, We pull information about your events from the code that tracks your events. We officially support tracking in JavaScript, but can integrate tracking events from other languages such as Ruby and Python. , Enrichments, We support the following Snowplow enrichments:, Enrichment, Version, Custom Configuration, Notes, IP Lookup, 2-0-0, Data is enriched using the , GeoIP2 City, database., UA Parser, 1-0-0, Referer Parser, 1-0-0, Campaign Attribution, 1-0-1, check, If there is no configuration file, we consider the default , Snowplow fields, for populating the marketing columns. Name the configuration file , campaign_attribution.json, ., IP Anonymization, 1-0-1, check, IPv6 anonymization changes are backward compatible with schema version 1-0-0. If the , anonSegments, parameter is missing, we use the , anonOctets, parameter for IPv6 addresses. Name the configuration file , anon_ip.json, ., Note: Your JSON configuration file must follow the , Snowplow schema format, . You must use the enrichment-specific name (see the Notes section of the table above) for your configuration file., To disable an enrichment, in the JSON configuration file, set the , enabled, field to false., Setup guide, Follow our step-by-step , Snowplow setup guide, to connect Snowplow with your destination using Fivetran connectors., Sync overview, “After instrumenting the Snowplow tracking code on your website, server, or mobile application, Fivetrans robust event pipeline will collect, enrich, and load all of this data into your destination in near real-time:”, Snowplow events sent to ,, Events collected , Events queued , Events processed and enriched, Events prepared (transformed and cleaned) and written to CSV file, Loaded into your destination, Snowplow does not allow Fivetran to sync your historical data. We can only capture data from your connection date forward., Schema information, Snowplow has standard and custom fields. Each integration creates a single schema, shown below. If you choose to use custom events, each custom event type will have its own table., To zoom, open ERD in new window, Snowplow has a primary standard table, event, with the following columns. , “The COLUMN section lists the title of every column in the table, and TYPE tells you the columns data type. The MODIFIERS section tells you which column is a primary key. The REFERENCE section tells you which table and column you can join the current table with.”, Fivetran deduplicates events based on , event_id, i.e. if there are two events with the same , event_id, it would overwrite the first event., event, Column, Type, Reference, event_id üîë, TEXT, app_id, TEXT, br_colordepth, INTEGER, br_cookies, BOOLEAN, br_family, TEXT, br_features_director, BOOLEAN, br_features_flash, BOOLEAN, br_features_gears, BOOLEAN, br_features_java, BOOLEAN, br_features_pdf, BOOLEAN, br_features_quicktime, BOOLEAN, br_features_realplayer, BOOLEAN, br_features_silverlight, BOOLEAN, br_features_windowsmedia, BOOLEAN, br_lang, TEXT, br_name, TEXT, br_renderengine, TEXT, br_type, TEXT, br_version, TEXT, br_viewheight, TEXT, collector_tstamp, TIMESTAMP, doc_charset, TEXT, doc_height, TEXT, doc_width, INTEGER, domain_sessionid, TEXT, domain_sessionidx, INTEGER, domain_userid, TEXT, dvce_ismobile, BOOLEAN, dvce_screenheight, TEXT, dvce_sent_tstamp, TIMESTAMP, dvce_tstamp, TIMESTAMP, dvce_type, TEXT, event, TEXT, event_format, TEXT, event_name, TEXT, event_vendor, TEXT, event_version, TEXT, mkt_campaign, TEXT, mkt_content, TEXT, mkt_medium, TEXT, mkt_source, TEXT, mkt_term, TEXT, mkt_clickid, TEXT, mkt_network, TEXT, name_tracker, TEXT, network_userid, TEXT, os_family, TEXT, os_manufacturer, TEXT, os_name, TEXT, os_timezone, TEXT, page_referrer, TEXT, page_title, TEXT, page_url, TEXT, page_urlfragment, TEXT, page_urlhost, TEXT, page_urlpath, TEXT, page_urlport, INTEGER, page_urlquery, TEXT, page_urlscheme, TEXT, platform, TEXT, pp_xoffset_max, INTEGER, pp_xoffset_min, INTEGER, pp_yoffset_max, INTEGER, pp_yoffset_min, INTEGER, refr_medium, TEXT, refr_source, TEXT, refr_term, TEXT, refr_urlfragment, TEXT, refr_urlhost, TEXT, refr_urlpath, TEXT, refr_urlport, INTEGER, refr_urlquery, TEXT, refr_urlscheme, TEXT, refr_domain_user_id, TEXT, refr_dvce_tstamp, TIMESTAMP, se_action, TEXT, se_category, TEXT, se_label, TEXT, se_property, TEXT, se_value, DOUBLE, sequence_number, TEXT, ti_category, TEXT, ti_currency, TEXT, ti_name, TEXT, ti_orderid, TEXT, ti_price, DOUBLE, ti_quantity, INTEGER, ti_sku, TEXT, tr_affiliation, TEXT, tr_city, TEXT, tr_country, TEXT, tr_currency, TEXT, tr_orderid, TEXT, tr_shipping, DOUBLE, tr_state, TEXT, tr_tax, DOUBLE, tr_total, DOUBLE, txn_id, TEXT, user_fingerprint, BIGINT, User agents are also parsed into a separate context, following the Snowplow enrichment explained , here, ., These user agent parser contexts have the following columns:, UA Parser Context, Column, Type, Reference, useragent_family, TEXT, useragent_major, TEXT, useragent_minor, TEXT, useragent_patch, TEXT, useragent_version, TEXT, os_family, TEXT, os_major, TEXT, os_minor, TEXT, os_patch, TEXT, os_patch_minor, TEXT, os_version, TEXT, device_family, TEXT, “If you implement Snowplows custom click feature, all the custom-clicks will be loaded into the events table in your destinations Snowplow schema.”, You can however, track your custom objects as well. Fivetran supports unstructured events. Follow these instructions to load custom fields in your destination: , Write a JSON schema describing your custom attributes known as an , iglu file, ” in the Snowplow documentation. Iglu files are JSON schemas and Snowplows integration is setup to work with JSON schemas. For more information you can see an explanation of how “, JSON schemas, work., Validate, your schema before you start sending your data to us. , We dont have a repository thats analogous to Snowplows “iglu”, so just put your schema at a regular URL such as a public github repository, such as:n,, orn,, Use the URL that you established in step 3 as the schema URL when you call Snowplow:, “window[snowplowName](trackPageView, null, [{nschema:,ndata: {nhello: Hello world!,nhello_array: [Hello, world!]n}n}]);n”, Make sure to have a “title” attribute for the schema, which will become the name of the table where the data gets stored. For example, the following will create a table named , example, (id int):, {n “title”: “example”,n “properties”: {n “id”: { n “type”: “integer”n }n }n}n, If you want to create a decimal type (for example, for storing currency values), just use the multipleOf property:, {n “title”: “example”,n “properties”: {n “value”: { n “type”: “number”,n “multipleOf”: 0.01n }n }n}n, This will create a destination table example (value decimal (18, 2)). , If you want to store an enum value, add a type associated with it. All the enum values should be of same data type: , {n “properties”: {n “value”: { n “type”: “string”,n “enum”: [“value1”, “value2”]n }n }n}n, “We only support values and homogenous arrays. Nested objects and tuple-style arrays are stored in but not extracted into your destination since they dont have an obvious representation.”, Excluding source data, “We dont yet have a way to exclude source data. You can independently, however, limit the data you send to Fivetran. “]

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