- Introduction
- Getting Started
- Data Ingestion
- Data Loading
- Loading Data in a Database Destination
- Loading Data to a Data Warehouse
- Optimizing Data Loading for a Destination Warehouse
- Manually Triggering the Loading of Events
- Scheduling Data Load for a Destination
- Loading Events in Batches
- Data Loading Statuses
- Data Spike Alerts
- Name Sanitization
- Table and Column Name Compression
- Parsing Nested JSON Fields in Events
- Pipelines
- Data Flow in a Pipeline
- Familiarizing with the Pipelines UI
- Working with Pipelines
- Managing Objects in Pipelines
-
Transformations
-
Python Code-Based Transformations
- Supported Python Modules and Functions
-
Transformation Methods in the Event Class
- Create an Event
- Retrieve the Event Name
- Rename an Event
- Retrieve the Properties of an Event
- Modify the Properties for an Event
- Fetch the Primary Keys of an Event
- Modify the Primary Keys of an Event
- Fetch the Data Type of a Field
- Check if the Field is a String
- Check if the Field is a Number
- Check if the Field is Boolean
- Check if the Field is a Date
- Check if the Field is a Time Value
- Check if the Field is a Timestamp
-
TimeUtils
- Convert date string to required format
- Convert date to required format
- Convert datetime string to required format
- Convert epoch time to a date
- Convert epoch time to a datetime
- Convert epoch to required format
- Convert epoch to a time
- Get time difference
- Parse date string to date
- Parse date string to datetime format
- Parse date string to time
- Utils
- Examples of Python Code-based Transformations
-
Drag and Drop Transformations
- Special Keywords
-
Transformation Blocks and Properties
- Add a Field
- Change Datetime Field Values
- Change Field Values
- Drop Events
- Drop Fields
- Find & Replace
- Flatten JSON
- Format Date to String
- Format Number to String
- Hash Fields
- If-Else
- Mask Fields
- Modify Text Casing
- Parse Date from String
- Parse JSON from String
- Parse Number from String
- Rename Events
- Rename Fields
- Round-off Decimal Fields
- Split Fields
- Examples of Drag and Drop Transformations
- Effect of Transformations on the Destination Table Structure
- Transformation Reference
- Transformation FAQs
-
Python Code-Based Transformations
-
Schema Mapper
- Using Schema Mapper
- Mapping Statuses
- Auto Mapping Event Types
- Manually Mapping Event Types
- Modifying Schema Mapping for Event Types
- Schema Mapper Actions
- Fixing Unmapped Fields
- Resolving Incompatible Schema Mappings
- Resizing String Columns in the Destination
- Schema Mapper Compatibility Table
- Limits on the Number of Destination Columns
- File Log
- Troubleshooting Failed Events in a Pipeline
- Mismatch in Events Count in Source and Destination
- Activity Log
-
Pipeline FAQs
- Does creation of Pipeline incur cost?
- Why are my new Pipelines in trial?
- Can multiple Sources connect to one Destination?
- What happens if I re-create a deleted Pipeline?
- Why is there a delay in my Pipeline?
- Can I delete skipped objects in a Pipeline?
- Can I change the Destination post-Pipeline creation?
- How does changing the query mode affect data ingestion?
- Why is my billable Events high with Delta Timestamp mode?
- Can I drop multiple Destination tables in a Pipeline at once?
- How does Run Now affect scheduled ingestion frequency?
- Will pausing some objects increase the ingestion speed?
- Can I sort Event Types listed in the Schema Mapper?
- How do I include new tables in the Pipeline?
- Can I see the historical load progress?
- Why is my Historical Load Progress still at 0%?
- Why is historical data not getting ingested?
- How do I restart the historical load for all the objects?
- How do I set a field as a primary key?
- How can I load only filtered Events to the Destination?
- How do I ensure that records are loaded only once?
- Why do the Source and the Destination events count differ?
- Events Usage
- Sources
- Free Sources
-
Databases and File Systems
- Data Warehouses
-
Databases
- Connecting to a Local Database
- Amazon DocumentDB
- Amazon DynamoDB
- Elasticsearch
-
MongoDB
- Generic MongoDB
- MongoDB Atlas
- Support for Multiple Data Types for the _id Field
- Example - Merge Collections Feature
-
Troubleshooting MongoDB
-
Errors During Pipeline Creation
- Error 1001 - Incorrect credentials
- Error 1005 - Connection timeout
- Error 1006 - Invalid database hostname
- Error 1007 - SSH connection failed
- Error 1008 - Database unreachable
- Error 1011 - Insufficient access
- Error 1028 - Primary/Master host needed for OpLog
- Error 1029 - Version not supported for Change Streams
- SSL 1009 - SSL Connection Failure
- Troubleshooting MongoDB Change Streams Connection
- Troubleshooting MongoDB OpLog Connection
-
Errors During Pipeline Creation
- SQL Server
-
MySQL
- Amazon Aurora MySQL
- Amazon RDS MySQL
- Azure MySQL
- Google Cloud MySQL
- Generic MySQL
- MariaDB MySQL
-
Troubleshooting MySQL
-
Errors During Pipeline Creation
- Error 1003 - Connection to host failed
- Error 1006 - Connection to host failed
- Error 1007 - SSH connection failed
- Error 1011 - Access denied
- Error 1012 - Replication access denied
- Error 1017 - Connection to host failed
- Error 1026 - Failed to connect to database
- Error 1027 - Unsupported BinLog format
- Failed to determine binlog filename/position
- Schema 'xyz' is not tracked via bin logs
- Errors Post-Pipeline Creation
-
Errors During Pipeline Creation
- MySQL FAQs
- Oracle
-
PostgreSQL
- Amazon Aurora PostgreSQL
- Amazon RDS PostgreSQL
- Azure PostgreSQL
- Google Cloud PostgreSQL
- Generic PostgreSQL
- Heroku PostgreSQL
-
Troubleshooting PostgreSQL
-
Errors during Pipeline creation
- Error 1003 - Authentication failure
- Error 1006 - Connection settings errors
- Error 1011 - Access role issue for logical replication
- Error 1012 - Access role issue for logical replication
- Error 1014 - Database does not exist
- Error 1017 - Connection settings errors
- Error 1023 - No pg_hba.conf entry
- Error 1024 - Number of requested standby connections
- Errors Post-Pipeline Creation
-
Errors during Pipeline creation
- PostgreSQL FAQs
- Troubleshooting Database Sources
- File Storage
-
Engineering Analytics
- Apify
- Asana
- Buildkite
- GitHub
-
Streaming
- Android SDK
- Kafka
-
REST API
- Writing JSONPath Expressions
-
REST API FAQs
- Why does my REST API token keep changing?
- Can I use a bearer authorization token for authentication?
- Does Hevo’s REST API support API chaining?
- What is the maximum payload size returned by a REST API?
- How do I split an Event into multiple Event Types?
- How do I split multiple values in a key into separate Events?
- Webhook
- GitLab
- Jira Cloud
- Opsgenie
- PagerDuty
- Pingdom
- Trello
- Finance & Accounting Analytics
-
Marketing Analytics
- ActiveCampaign
- AdRoll
- Apple Search Ads
- AppsFlyer
- CleverTap
- Criteo
- Drip
- Facebook Ads
- Facebook Page Insights
- Firebase Analytics
- Freshsales
- Google Campaign Manager
- Google Ads
- Google Analytics
- Google Analytics 4
- Google Analytics 360
- Google Play Console
- Google Search Console
- HubSpot
- Instagram Business
- Klaviyo
- Lemlist
- LinkedIn Ads
- Mailchimp
- Mailshake
- Marketo
- Microsoft Advertising
- Onfleet
- Outbrain
- Pardot
- Pinterest Ads
- Pipedrive
- Recharge
- Segment
- SendGrid Webhook
- SendGrid
- Salesforce Marketing Cloud
- Snapchat Ads
- SurveyMonkey
- Taboola
- TikTok Ads
- Twitter Ads
- Typeform
- YouTube Analytics
- Product Analytics
- Sales & Support Analytics
-
Source FAQs
- From how far back can the Pipeline ingest data?
- Can I connect to a Source not listed in Hevo?
- Can I connect a local database as a Source?
- How can I push data to Hevo API?
- How do I connect a CSV file as a Source?
- Why are my selected Source objects not visible in the Schema Mapper?
- How can I transfer Excel files using Hevo?
- How does the Merge Table feature work?
- Destinations
- Familiarizing with the Destinations UI
- Databases
-
Data Warehouses
- Amazon Redshift
- Azure Synapse Analytics
- Databricks
- Firebolt
- Google BigQuery
- Hevo Managed Google BigQuery
- Snowflake
-
Destination FAQs
- Can I move data between SaaS applications using Hevo?
- Can I change the primary key in my Destination table?
- How do I change the data type of table columns?
- Can I change the Destination table name after creating the Pipeline?
- How can I change or delete the Destination table prefix?
- How do I resolve duplicate records in the Destination table?
- How do I enable or disable deduplication of records?
- Why does my Destination have deleted Source records?
- How do I filter deleted Events from the Destination?
- Does a data load regenerate deleted Hevo metadata columns?
- Can I load data to a specific Destination table?
- How do I filter out specific fields before loading data?
- How do I sort the data in the Destination?
- Transform
- Alerts
- Account Management
- Personal Settings
- Team Settings
-
Billing
- Pricing Plans
- Time-based Events Buffer
- Setting up Pricing Plans, Billing, and Payments
- On-Demand Purchases
- Billing Alerts
- Viewing Billing History
- Billing Notifications
-
Billing FAQs
- Can I try Hevo for free?
- Can I get a plan apart from the Starter plan?
- Are free trial Events charged once I purchase a plan?
- For how long can I stay on the Free plan?
- How can I upgrade my plan?
- Is there a discount for non-profit organizations?
- Can I seek a refund of my payment?
- Do ingested Events count towards billing?
- Will Pipeline get paused if I exceed the Events quota?
- Will the initial load of data be free?
- Does the Hevo plan support multiple Destinations?
- Do rows loaded through Models count in my usage?
- Is Hevo subscription environment-specific?
- Can I pause billing if I have no active Pipelines?
- Can you explain the pricing plans in Hevo?
- Where do I get invoices for payments?
- Account Suspension and Restoration
- Account Management FAQs
- Activate
- Glossary
- Release Notes
- Release Version 2.13
- Release Version 2.12
- Release Version 2.11
- Release Version 2.10
- Release Version 2.09
- Release Version 2.08
- Release Version 2.07
- Release Version 2.06
- Release Version 2.05
- Release Version 2.04
- Release Version 2.03
- Release Version 2.02
- Release Version 2.01
- Release Version 2.00
- Release Version 1.99
- Release Version 1.98
- Release Version 1.97
- Release Version 1.96
- Release Version 1.95
- Release Version 1.93 & 1.94
- Release Version 1.92
- Release Version 1.91
- Release Version 1.90
- Release Version 1.89
- Release Version 1.88
- Release Version 1.87
- Release Version 1.86
- Release Version 1.84 & 1.85
- Release Version 1.83
- Release Version 1.82
- Release Version 1.81
- Release Version 1.80 (Jan-24-2022)
- Release Version 1.79 (Jan-03-2022)
- Release Version 1.78 (Dec-20-2021)
- Release Version 1.77 (Dec-06-2021)
- Release Version 1.76 (Nov-22-2021)
- Release Version 1.75 (Nov-09-2021)
- Release Version 1.74 (Oct-25-2021)
- Release Version 1.73 (Oct-04-2021)
- Release Version 1.72 (Sep-20-2021)
- Release Version 1.71 (Sep-09-2021)
- Release Version 1.70 (Aug-23-2021)
- Release Version 1.69 (Aug-09-2021)
- Release Version 1.68 (Jul-26-2021)
- Release Version 1.67 (Jul-12-2021)
- Release Version 1.66 (Jun-28-2021)
- Release Version 1.65 (Jun-14-2021)
- Release Version 1.64 (Jun-01-2021)
- Release Version 1.63 (May-19-2021)
- Release Version 1.62 (May-05-2021)
- Release Version 1.61 (Apr-20-2021)
- Release Version 1.60 (Apr-06-2021)
- Release Version 1.59 (Mar-23-2021)
- Release Version 1.58 (Mar-09-2021)
- Release Version 1.57 (Feb-22-2021)
- Release Version 1.56 (Feb-09-2021)
- Release Version 1.55 (Jan-25-2021)
- Release Version 1.54 (Jan-12-2021)
- Release Version 1.53 (Dec-22-2020)
- Release Version 1.52 (Dec-03-2020)
- Release Version 1.51 (Nov-10-2020)
- Release Version 1.50 (Oct-19-2020)
- Release Version 1.49 (Sep-28-2020)
- Release Version 1.48 (Sep-01-2020)
- Release Version 1.47 (Aug-06-2020)
- Release Version 1.46 (Jul-21-2020)
- Release Version 1.45 (Jul-02-2020)
- Release Version 1.44 (Jun-11-2020)
- Release Version 1.43 (May-15-2020)
- Release Version 1.42 (Apr-30-2020)
- Release Version 1.41 (Apr-2020)
- Release Version 1.40 (Mar-2020)
- Release Version 1.39 (Feb-2020)
- Release Version 1.38 (Jan-2020)
- Upcoming Features
Twitter Ads
On This Page
Hevo can replicate your Twitter Ads’ data to your data warehouse using Twitter API.
For creating Pipelines using this Source, Hevo provides you a fully managed BigQuery data warehouse as a possible Destination. This option remains available till the time you set up your first BigQuery Destination irrespective of any other Destinations that you may have. With the managed warehouse, you are only charged the cost that Hevo incurs for your project in Google BigQuery. The invoice is generated at the end of each month and payment is recovered as per the payment instrument you have set up. You can now create your Pipeline and directly start analyzing your Source data. Read Hevo Managed Google BigQuery.
Prerequisites
-
A Twitter Ads account with ACCOUNT_ADMIN, AD_MANAGER, or CREATIVE_MANAGER permissions.
-
A Twitter Developer Account.
-
You are assigned the Team Administrator, Team Collaborator, or Pipeline Administrator role in Hevo to create the Pipeline.
Apply for a Developer Account
To connect Twitter Ads to Hevo, you need a Twitter app with access to the Twitter Ads API. If you already have a developer account, skip ahead to Step 2.
-
Go to Twitter’s Apply for access page.
-
Select Apply for a developer account.
-
Select Build customized solutions in-house.
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Input your organization details and explain how you intend to use the Twitter data in subsequent application screens. For the use case description field, we recommend using the following paragraph:
We will use Twitter API to pull our advertising data and load it into our data warehouse for internal analytics purposes. My organization is keen to understand our ads' performance on Twitter and also perform comparative analysis with other ads platforms. We will be only pulling data out of Twitter and don't plan to trigger any action on the platform.
Note: It may take few days for Twitter to approve your developer account.
Create a Twitter Application
-
If you already have an application that you can use to connect to HEVO, skip to Step 3.
-
After your developer account is approved, go to Twitter’s Create Application page to create a Twitter app.
-
In the Website URL field, fill
https://hevodata.com/
. -
In the Tell us how this app will be used field, you can fill the following:
This application will be used to pull analytics on the advertising that I run on the Twitter platform in order to analyse performance.
Submit the Advertising API License Agreement Form
-
Navigate to the Advertising Api License Agreement.
-
Fill and submit the form.
Generate Keys and Tokens for Your Account
-
Go to your Twitter App Dashboard.
-
Select the application that you created in Step 2.
-
Click on the Keys and tokens tab.
-
Create your keys and tokens.
-
Make a note of these keys and tokens. You will need them to configure Twitter Ads source at HEVO.
Configure Twitter as a Source
Perform the following steps to configure Twitter Ads as the Source in your Pipeline:
-
Click PIPELINES in the Navigation Bar.
-
Click + CREATE in the Pipelines List View.
-
In the Select Source Type page, select Twitter Ads.
-
In the Configure your Twitter Ads Source page, specify the following:
-
Pipeline Name: A unique name for the Pipeline.
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Enter the following keys and tokens that you created.
- Consumer API Key
- Consumer API Secret
- Access Token
- Access Token Secret
-
-
Click TEST & CONTINUE.
-
Proceed to configuring the data ingestion and setting up the Destination.
Data Replication
Default Pipeline Frequency | Minimum Pipeline Frequency | Maximum Pipeline Frequency | Custom Frequency Range (Hrs) |
---|---|---|---|
1 Hr | 15 Mins | 24 Hrs | 1-24 |
Note: The custom frequency must be set in hours, as an integer value. For example, 1, 2, 3 but not 1.5 or 1.75.
Objects
-
Historical data: In the first run of the Pipeline, Hevo ingests the data of all the objects in your account and loads it to the Destination.
-
Incremental data: Once the historical load is complete, Hevo ingests the incremental data as per the ingestion frequency. Default duration: 1 Hour.
Reports
-
Historical data: In the first run of the Pipeline, Hevo ingests the data of the past 90 days from all the reports in your Twitter Ads account.
-
Incremental data: Once the historical data ingestion is complete, every subsequent run of the Pipeline fetches new and updated data for the reports. Default duration: 1 Hour.
Note: From Release 1.79 onwards, Hevo ingests your historical data using the Recent Data First approach, whereby, the data is ingested in the reverse order, starting from the latest to the earliest. This enables you to have quicker access to the most recent data. This change applies to all new and existing Pipelines.
Schema and Primary Keys
Primary Keys for Objects
Object | Primary Keys |
---|---|
ACCOUNTS | ACCOUNT_ID, ID |
FUNDING_INSTRUMENTS | ACCOUNT_ID, ID |
CAMPAIGNS | ACCOUNT_ID, ID |
LINE_ITEMS | ACCOUNT_ID, ID |
PROMOTED_TWEETS | ACCOUNT_ID, ID |
MEDIA_CREATIVE | ACCOUNT_ID, ID |
Primary Keys for Reports
Unsegmented reports
Report | Primary Keys |
---|---|
ACCOUNT_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, PLACEMENT |
CAMPAIGN_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, PLACEMENT |
FUNDING_INSTRUMENT_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, PLACEMENT |
LINE_ITEM_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, PLACEMENT |
PROMOTED_TWEET_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, PLACEMENT |
MEDIA_CREATIVE_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, PLACEMENT |
Segmented reports
Report | Primary Key |
---|---|
ACCOUNT_AGE_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
ACCOUNT_APP_STORE_CATEGORY_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
ACCOUNT_DEVICES_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT, PLATFORM_TARGET_VALUE |
ACCOUNT_EVENTS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
ACCOUNT_GENDER_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
ACCOUNT_INTERESTS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
ACCOUNT_LOCATIONS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
ACCOUNT_PLATFORMS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
ACCOUNT_PLATFORM_VERSIONS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT, PLATFORM_TARGET_VALUE |
ACCOUNT_POSTAL_CODES_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT, COUNTRY_TARGET_VALUE |
ACCOUNT_REGIONS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT, COUNTRY_TARGET_VALUE |
CAMPAIGN_AGE_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
CAMPAIGN_APP_STORE_CATEGORY_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
CAMPAIGN_CONVERSION_TAGS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
CAMPAIGN_DEVICES_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT, PLATFORM_TARGET_VALUE |
CAMPAIGN_EVENTS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
CAMPAIGN_GENDER_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
CAMPAIGN_INTERESTS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
CAMPAIGN_KEYWORDS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
CAMPAIGN_LANGUAGES_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
CAMPAIGN_LOCATIONS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
CAMPAIGN_PLATFORMS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
CAMPAIGN_PLATFORM_VERSIONS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT, PLATFORM_TARGET_VALUE |
CAMPAIGN_POSTAL_CODES_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT, COUNTRY_TARGET_VALUE |
CAMPAIGN_REGIONS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT, COUNTRY_TARGET_VALUE |
CAMPAIGN_SIMILAR_TO_FOLLOWERS_OF_USER_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
CAMPAIGN_TV_SHOWS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
FUNDING_INSTRUMENT_AGE_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
FUNDING_INSTRUMENT_APP_STORE_CATEGORY_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
FUNDING_INSTRUMENT_CONVERSION_TAGS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
FUNDING_INSTRUMENT_DEVICES_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT, PLATFORM_TARGET_VALUE |
FUNDING_INSTRUMENT_EVENTS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
FUNDING_INSTRUMENT_GENDER_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
FUNDING_INSTRUMENT_INTERESTS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
FUNDING_INSTRUMENT_LOCATIONS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
FUNDING_INSTRUMENT_PLATFORMS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
FUNDING_INSTRUMENT_PLATFORM_VERSIONS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT, PLATFORM_TARGET_VALUE |
FUNDING_INSTRUMENT_REGIONS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT, COUNTRY_TARGET_VALUE |
LINE_ITEM_AGE_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
LINE_ITEM_APP_STORE_CATEGORY_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
LINE_ITEM_CONVERSION_TAGS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
LINE_ITEM_DEVICES_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT, PLATFORM_TARGET_VALUE |
LINE_ITEM_EVENTS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
LINE_ITEM_GENDER_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
LINE_ITEM_INTERESTS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
LINE_ITEM_KEYWORDS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
LINE_ITEM_LANGUAGES_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
LINE_ITEM_LOCATIONS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
LINE_ITEM_PLATFORMS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
LINE_ITEM_PLATFORM_VERSIONS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT, PLATFORM_TARGET_VALUE |
LINE_ITEM_POSTAL_CODES_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT, COUNTRY_TARGET_VALUE |
LINE_ITEM_REGIONS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT, COUNTRY_TARGET_VALUE |
LINE_ITEM_SIMILAR_TO_FOLLOWERS_OF_USER_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
LINE_ITEM_TV_SHOWS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
PROMOTED_TWEET_AGE_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
PROMOTED_TWEET_APP_STORE_CATEGORY_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
PROMOTED_TWEET_CONVERSION_TAGS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
PROMOTED_TWEET_DEVICES_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT, PLATFORM_TARGET_VALUE |
PROMOTED_TWEET_EVENTS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
PROMOTED_TWEET_GENDER_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
PROMOTED_TWEET_INTERESTS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
PROMOTED_TWEET_KEYWORDS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
PROMOTED_TWEET_LANGUAGES_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
PROMOTED_TWEET_LOCATIONS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
PROMOTED_TWEET_PLATFORMSREPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
PROMOTED_TWEET_PLATFORM_VERSIONS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT, PLATFORM_TARGET_VALUE |
PROMOTED_TWEET_POSTAL_CODES_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT, COUNTRY_TARGET_VALUE |
PROMOTED_TWEET_REGIONS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT, COUNTRY_TARGET_VALUE |
PROMOTED_TWEET_SIMILAR_TO_FOLLOWERS_USER_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENT_NAME, PLACEMENT |
PROMOTED_TWEET_TV_SHOWS_REPORT | ACCOUNT_ID, ENTITY_ID, DATE, SEGMENTNAME, PLACEMENT |
Data Model
The following is the list of tables that are created at the Destination when you run the Pipeline configured for Twitter Ads:
Objects
-
ACCOUNTS
-
FUNDING_INSTRUMENTS
-
CAMPAIGNS
-
LINE_ITEMS
-
PROMOTED_TWEETS
-
MEDIA_CREATIVE
Reports
You can retrieve the following types of reports:
Unsegmented reports
Unsegmented reports give you the overview-level information of your ad campaign.
-
ACCOUNT_REPORT
-
CAMPAIGN_REPORT
-
FUNDING_INSTRUMENT_REPORT
-
LINE_ITEM_REPORT
-
PROMOTED_TWEET_REPORT
-
MEDIA_CREATIVE_REPORT
Segmented reports
Segmented reports retrieve metrics such as AGE or APP_STORE, allowing partners and advertisers to get detailed information for a particular segment type. For example, to know the success of a campaign based on age, you can fetch the CAMPAIGN_AGE_REPORT.
Read Twitter Ads API Analytics and Metrics and Segmentation.
-
ACCOUNT_AGE_REPORT
-
ACCOUNT_APP_STORE_CATEGORY_REPORT
-
ACCOUNT_DEVICES_REPORT
-
ACCOUNT_EVENTS_REPORT
-
ACCOUNT_GENDER_REPORT
-
ACCOUNT_INTERESTS_REPORT
-
ACCOUNT_LOCATIONS_REPORT
-
ACCOUNT_PLATFORMS_REPORT
-
ACCOUNT_PLATFORM_VERSIONS_REPORT
-
ACCOUNT_POSTAL_CODES_REPORT
-
ACCOUNT_REGIONS_REPORT
-
CAMPAIGN_AGE_REPORT
-
CAMPAIGN_APP_STORE_CATEGORY_REPORT
-
CAMPAIGN_CONVERSION_TAGS_REPORT
-
CAMPAIGN_DEVICES_REPORT
-
CAMPAIGN_EVENTS_REPORT
-
CAMPAIGN_GENDER_REPORT
-
CAMPAIGN_INTERESTS_REPORT
-
CAMPAIGN_KEYWORDS_REPORT
-
CAMPAIGN_LANGUAGES_REPORT
-
CAMPAIGN_LOCATIONS_REPORT
-
CAMPAIGN_PLATFORMS_REPORT
-
CAMPAIGN_PLATFORM_VERSIONS_REPORT
-
CAMPAIGN_POSTAL_CODES_REPORT
-
CAMPAIGN_REGIONS_REPORT
-
CAMPAIGN_SIMILAR_TO_FOLLOWERS_OF_USER_REPORT
-
CAMPAIGN_TV_SHOWS_REPORT
-
FUNDING_INSTRUMENT_AGE_REPORT
-
FUNDING_INSTRUMENT_APP_STORE_CATEGORY_REPORT
-
FUNDING_INSTRUMENT_CONVERSION_TAGS_REPORT
-
FUNDING_INSTRUMENT_DEVICES_REPORT
-
FUNDING_INSTRUMENT_EVENTS_REPORT
-
FUNDING_INSTRUMENT_GENDER_REPORT
-
FUNDING_INSTRUMENT_INTERESTS_REPORT
-
FUNDING_INSTRUMENT_LOCATIONS_REPORT
-
FUNDING_INSTRUMENT_PLATFORMS_REPORT
-
FUNDING_INSTRUMENT_PLATFORM_VERSIONS_REPORT
-
FUNDING_INSTRUMENT_REGIONS_REPORT
-
LINE_ITEM_AGE_REPORT
-
LINE_ITEM_APP_STORE_CATEGORY_REPORT
-
LINE_ITEM_CONVERSION_TAGS_REPORT
-
LINE_ITEM_DEVICES_REPORT
-
LINE_ITEM_EVENTS_REPORT
-
LINE_ITEM_GENDER_REPORT
-
LINE_ITEM_INTERESTS_REPORT
-
LINE_ITEM_KEYWORDS_REPORT
-
LINE_ITEM_LANGUAGES_REPORT
-
LINE_ITEM_LOCATIONS_REPORT
-
LINE_ITEM_PLATFORMS_REPORT
-
LINE_ITEM_PLATFORM_VERSIONS_REPORT
-
LINE_ITEM_POSTAL_CODES_REPORT
-
LINE_ITEM_REGIONS_REPORT
-
LINE_ITEM_SIMILAR_TO_FOLLOWERS_OF_USER_REPORT
-
LINE_ITEM_TV_SHOWS_REPORT
-
PROMOTED_TWEET_AGE_REPORT
-
PROMOTED_TWEET_APP_STORE_CATEGORY_REPORT
-
PROMOTED_TWEET_CONVERSION_TAGS_REPORT
-
PROMOTED_TWEET_DEVICES_REPORT
-
PROMOTED_TWEET_EVENTS_REPORT
-
PROMOTED_TWEET_GENDER_REPORT
-
PROMOTED_TWEET_INTERESTS_REPORT
-
PROMOTED_TWEET_KEYWORDS_REPORT
-
PROMOTED_TWEET_LANGUAGES_REPORT
-
PROMOTED_TWEET_LOCATIONS_REPORT
-
PROMOTED_TWEET_PLATFORMS_REPORT
-
PROMOTED_TWEET_PLATFORM_VERSIONS_REPORT
-
PROMOTED_TWEET_POSTAL_CODES_REPORT
-
PROMOTED_TWEET_REGIONS_REPORT
-
PROMOTED_TWEET_SIMILAR_TO_FOLLOWERS_OF_USER_REPORT
-
PROMOTED_TWEET_TV_SHOWS_REPORT
Additional Information
Read the detailed Hevo documentation for the following related topics:
Source Considerations
-
From version 10 of Twitter Ads API, only advertising-enabled accounts are visible in the Ads Accounts drop-down while configuring Twitter Ads as a Source in Hevo. Any existing Pipelines created with accounts not enabled for advertising are not affected. However, if you want to continue using the non-advertiser accounts, you must enable them for advertising. Read Ads Account creation for the steps.
-
Some fields in the LINE_ITEMS object have been either renamed or deprecated. The field
bid_type
has been renamed tobid_strategy
. The fieldsautomatically_select_bid
andtracking_tags
have been deprecated. As a result, from Release 1.81 onwards, these fields contain null values in the Destination table. The new field,bid_strategy
is automatically mapped if Auto Mapping is enabled.
Limitations
None.
See Also
Revision History
Refer to the following table for the list of key updates made to this page:
Date | Release | Description of Change |
---|---|---|
Dec-07-2022 | NA | Updated section, Data Replication to reorganize the content for better understanding and coherence. |
Feb-07-2022 | 1.81 | - Reorganized the content in the Data Replication section. - Segregated the reports content based on their type in sections, Schema and Primary Keys and Data Model. - Added section, Source Considerations. |
Jan-03-2022 | 1.79 | Added information about reverse historical load in the Data Replication section. |
Oct-25-2021 | NA | Added the Pipeline frequency information in the Data Replication section. |