- 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?
- 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 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
Pinterest Ads
Pinterest Ads is Pinterest’s advertising platform for Business Accounts. It enables users to retrieve statistics about their ads, ad accounts, ad groups, and campaigns running on Pinterest.
Hevo uses the Pinterest APIs to replicate your Pinterest Ads data into the desired Destination database or data warehouse for scalable analysis. For this, you must authorize Hevo to access data from your Pinterest Ads account.
Pinterest Ads uses the following concepts to capture user interaction with your ads:
-
Conversion: Conversion is the process of a user interacting with your ad that subsequently leads to a action defined based on your ad goals. For example, signup, checkout, or an add to cart event.
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Attribution: Attribution is the process of linking a current user action to a previous interaction with the ad. For example, a purchase made today may be attributable to an add-to-cart event a week ago, or a sign-up may be attributable to an earlier ad-click. The respective attribution window, then, defines the duration for which you want to capture the attributions. For example, you may generate a conversion report for checkouts attributable to ad-clicks in the past 20 days.
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Ad-Action: Ad-action is the interaction or engagement of the user with the Pins such as clicks, reactions, or comments.
Prerequisites
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An active Pinterest Business account from which the data is to be ingested.
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A Pinterest user with Admin privileges, to access the data from the Pinterest Ads account.
-
You are assigned the Team Administrator, Team Collaborator, or Pipeline Administrator role in Hevo to create the Pipeline.
Configuring Pinterest Ads as a Source
Perform the following steps to configure Pinterest Ads as the Source in your Pipeline:
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Click PIPELINES in the Navigation Bar.
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Click + CREATE in the Pipelines List View.
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In the Select Source Type page, select Pinterest Ads.
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In the Configure your Pinterest Ads account page, click + ADD PINTEREST ADS ACCOUNT.
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Sign in using your Pinterest Business account.
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Click Continue to authorize Hevo to access your Pinterest Ads data.
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In the Configure your Pinterest Ads Source page, specify the following:
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Pipeline Name: A unique name for the Pipeline, not exceeding 255 characters.
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Select Accounts: The Pinterest Ads account(s) whose data you want to ingest. You can select multiple Ad accounts.
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Historical Sync Duration: The duration for which the existing data in the Source must be ingested. Default duration: 6 Months.
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Breakdowns: The granularity of time that you want in your report data. For example, you can break down the number of clicks by Week or Month.
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Advanced Settings:
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Attribution Windows: The number of days between a user’s responses on an ad. You can specify either one or both of the following:
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Click Attribution Window: The number of days between a person clicking your ad and taking an action such as checking out an item.
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Engagement Attribution Window: The number of days between a person engaging with your ad and taking an action such as adding the item to the cart.
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View Attribution Window: The number of days between a person viewing your ad and taking an action such as visiting a page.
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-
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Conversion Report Time: The factor based on which you want to generate a conversion report. Default value: Time of Ad Action. You can select either of the following:
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Time of Ad Action: Displays the conversion report as per the time at which a user action such as engagement with Pins, clicks, reactions, or comments occurred.
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Time of Conversion: Displays the conversion report as per the time at which a conversion event, such as sign-up or add to cart occurred.
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-
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Click TEST & CONTINUE.
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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 | 1 Hr | 24 Hrs | 1-48 |
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.
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Historical Data: In the first run of the Pipeline, Hevo ingests historical data for all the objects on the basis of the historical sync duration selected at the time of creating the Pipeline and loads it to the Destination. Default duration: 6 Months.
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Incremental Data: Once the historical load is complete, all new and updated records are synchronized with your Destination as per the ingestion frequency.
- For objects, Hevo performs full load to capture any data changes.
- For reports, Hevo incrementally fetches data as per the Pipeline frequency.
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Refresher Data: Hevo refreshes the report data once every 24 hours.
Schema and Primary Keys
Hevo uses the following schema to upload the records in the Destination:
Data Model
Hevo fetches both objects and reports from your specified ads account. Reports provide metrics around your users, their interaction related details, and the performance of your Ads.
Objects
The following is the list of tables (objects) that are created at the Destination when you run the Pipeline:
Object | Description |
---|---|
Ads | Contains the details of the ads per ad account. |
Ad Accounts | Contains the details of the Pinterest Ads accounts. |
Ad Groups | Contains the details of the ad groups per ad account. |
Boards | Contains the details of the boards per ad account. |
Campaign | Contains the details of the ad campaigns available in the specified ad account. |
Pins | Contains the details of the pins per ad account. |
Reports
The following reports are replicated as tables in the Destination when you run the Pipeline:
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Ad Report
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Ad Account Report
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Ad Campaign Report
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Ad Group Report
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. |
May-10-2022 | 1.88 | New document. |