- Introduction
- Getting Started
- Creating an Account in Hevo
- Subscribing to Hevo via AWS Marketplace
-
Connection Options
- Connecting Through SSH
- Connecting Through Reverse SSH Tunnel
- Connecting Through VPN
- Connecting Through Mongo PrivateLink
- Connecting Through AWS Transit Gateway
- Connecting Through AWS VPC Endpoint
- Connecting Through AWS VPC Peering
- Using Google Account Authentication
- How Hevo Authenticates Sources and Destinations using OAuth
- Reauthorizing an OAuth Account
- Familiarizing with the UI
- Creating your First Pipeline
- Data Loss Prevention and Recovery
- Data Ingestion
- Data Loading
- Loading Data in a Database Destination
- Loading Data to a Data Warehouse
- Optimizing Data Loading for a Destination Warehouse
- Deduplicating Data in a Data Warehouse Destination
- 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
- Pipeline Jobs
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Transformations
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Python Code-Based Transformations
- Supported Python Modules and Functions
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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
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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
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Drag and Drop Transformations
- Special Keywords
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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
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Python Code-Based Transformations
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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
- Audit Tables
- Activity Log
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Pipeline FAQs
- 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 change the Destination post-Pipeline creation?
- 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 see the historical load progress?
- Why is my Historical Load Progress still at 0%?
- Why is historical data not getting ingested?
- How do I set a field as a primary key?
- How do I ensure that records are loaded only once?
- Events Usage
- Sources
- Free Sources
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Databases and File Systems
- Data Warehouses
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Databases
- Connecting to a Local Database
- Amazon DocumentDB
- Amazon DynamoDB
- Elasticsearch
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MongoDB
- Generic MongoDB
- MongoDB Atlas
- Support for Multiple Data Types for the _id Field
- Example - Merge Collections Feature
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Troubleshooting MongoDB
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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
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Errors During Pipeline Creation
- SQL Server
-
MySQL
- Amazon Aurora MySQL
- Amazon RDS MySQL
- Azure MySQL
- Generic MySQL
- Google Cloud 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
- Generic PostgreSQL
- Google Cloud PostgreSQL
- Heroku PostgreSQL
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Troubleshooting PostgreSQL
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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
- Finance & Accounting Analytics
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Marketing Analytics
- ActiveCampaign
- AdRoll
- Amazon Ads
- Apple Search Ads
- AppsFlyer
- CleverTap
- Criteo
- Drip
- Facebook Ads
- Facebook Page Insights
- Firebase Analytics
- Freshsales
- Google Ads
- Google Analytics
- Google Analytics 4
- Google Analytics 360
- Google Play Console
- Google Search Console
- HubSpot
- Instagram Business
- Klaviyo v2
- Lemlist
- LinkedIn Ads
- Mailchimp
- Mailshake
- Marketo
- Microsoft Ads
- 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
- Destinations
- Familiarizing with the Destinations UI
- Cloud Storage-Based
- Databases
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Data Warehouses
- Amazon Redshift
- Amazon Redshift Serverless
- Azure Synapse Analytics
- Databricks
- Firebolt
- Google BigQuery
- Hevo Managed Google BigQuery
- Snowflake
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Destination FAQs
- 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?
- 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?
- How do I filter out specific fields before loading data?
- Transform
- Alerts
- Account Management
- Activate
- Glossary
Releases- Release 2.30 (Oct 21-Nov 18, 2024)
- Release 2.29 (Sep 30-Oct 22, 2024)
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2024 Releases
- Release 2.28 (Sep 02-30, 2024)
- Release 2.27 (Aug 05-Sep 02, 2024)
- Release 2.26 (Jul 08-Aug 05, 2024)
- Release 2.25 (Jun 10-Jul 08, 2024)
- Release 2.24 (May 06-Jun 10, 2024)
- Release 2.23 (Apr 08-May 06, 2024)
- Release 2.22 (Mar 11-Apr 08, 2024)
- Release 2.21 (Feb 12-Mar 11, 2024)
- Release 2.20 (Jan 15-Feb 12, 2024)
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2023 Releases
- Release 2.19 (Dec 04, 2023-Jan 15, 2024)
- Release Version 2.18
- Release Version 2.17
- Release Version 2.16 (with breaking changes)
- Release Version 2.15 (with breaking changes)
- Release Version 2.14
- 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
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2022 Releases
- 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)
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2021 Releases
- 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)
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2020 Releases
- 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)
- Early Access New
- Upcoming Features
LinkedIn Ads
The LinkedIn Ads API will soon be upgraded to the latest version (012024), which contains new and enhanced capabilities. This upgrade includes object changes that may impact your existing Pipelines created with this Source.
Please stay tuned for further communication about the enhancement and its release date.
LinkedIn Ads enable you to display sponsored content in the LinkedIn feed of professionals you want to reach by way of single image ads, video ads, and carousel ads. You can target your most valuable audiences using accurate, profile-based first-party data.
You can use Hevo Pipelines to replicate data from your LinkedIn reports to the desired Destination database or data warehouses for scalable analysis.
Prerequisites
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An active LinkedIn account with access to at least one advertiser profile exists.
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You have Admin access to the company’s LinkedIn page.
Note: You can create a Pipeline without Admin access too. However, it will not be able to access data from a few objects such as Page Stats, Follower Stats, Share Stats, and Video Ads.
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You are assigned the Team Administrator, Team Collaborator, or Pipeline Administrator role in Hevo to create the Pipeline.
Configuring LinkedIn Ads as a Source
Perform the following steps to configure LinkedIn Ads as the Source in your Pipeline:
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Click PIPELINES in the Navigation Bar.
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Click + CREATE PIPELINE in the Pipelines List View.
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On the Select Source Type page, select LinkedIn Ads.
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On the Configure your LinkedIn Ads Account page, do one of the following:
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Select a previously configured account and click CONTINUE.
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Click + ADD LINKEDIN ADS ACCOUNT and perform the following steps to configure an account:
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Specify the credentials of your LinkedIn account that has access to at least one advertiser profile and click Sign In.
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Click Allow to authorize Hevo to access your advertiser profile.
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On the Configure your LinkedIn 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: Select the advertiser profiles from which you want to replicate the reports’ data.
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Historical Sync Duration: The duration for which you want to ingest the existing data from the Source. Default duration: 6 Months.
Note: If you select All Available Data, Hevo ingests all the data available in your LinkedIn Ads account since January 01, 1970. Refer to the section, Limitations, to know about the objects from which Hevo fetches data for a limited period.
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Click TEST & CONTINUE.
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Proceed to configuring the data ingestion and setting up the Destination.
Data Replication
For Teams Created | Default Ingestion Frequency | Minimum Ingestion Frequency | Maximum Ingestion Frequency | Custom Frequency Range (in Hrs) |
---|---|---|---|---|
Before Release 2.21 | 1 Hr | 1 Hr | 48 Hrs | 1-48 |
After Release 2.21 | 6 Hrs | 30 Mins | 24 Hrs | 1-24 |
Note: The custom frequency must be set in hours as an integer value. For example, 1, 2, or 3 but not 1.5 or 1.75.
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Historical Data: Hevo ingests the historical data for Ad Analytics and Stats objects on the basis of the historical sync duration selected at the time of creating the Pipeline. Refer to the section, Limitations, to know about the objects from which Hevo fetches data for a limited period.
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Incremental Data: Once the historical load is complete, all new and updated records for the Ad Analytics and Stats object are ingested as per the ingestion frequency. The remaining objects are ingested in Full Load mode.
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Data Refresh: Data for the last 30 days is refreshed on a rolling basis for Ad Analytics objects. Data for Stats objects is refreshed for the past two days to include attributed data for the past days.
Schema and Primary Keys
Hevo uses the following schema to upload the records to the Destination database:
Note: Starting from Release 2.21, Hevo supports LinkedIn API version 012024, which contains new and enhanced reporting capabilities. These new capabilities include new fields such as approximate_member_reach
in the Campaign and Creative tables, and conversion_method
in the Conversions table.
Data Model
The following is the list of tables (objects) that are created at the Destination when you run the Pipeline:
Object | Description |
---|---|
Account | Contains details of the advertising campaigns created and managed for your company. |
Account User | Contains details of the account members who have access to the ad account in LinkedIn Campaign Manager, along with their roles. |
Campaigns | Contains details of the criteria used to achieve an advertising objective. |
Campaign Group | Contains details of the campaigns associated with the LinkedIn Ads account, along with their budget, criteria, and other settings. |
Creatives | Contains details of the content, such as images, text, and videos, required for displaying an ad on the LinkedIn platform. Note: - Hevo does not store the original content details, such as the raw text or images, associated with the ad. - For Pipelines created from June 19, 2023 onwards, Hevo uses the versioned Creatives API instead of the unversioned adCreativesV2 API to ingest data from this object. |
Conversions | Contains details of the performance of the ongoing ad campaigns within your LinkedIn Ads account, along with their corresponding conversion metrics. |
Ad Analytics by Campaign | Contains details of the analytics, such as views, conversions, and clicks for ad campaigns, aggregated on a daily basis. |
Ad Analytics by Creative | Contains details of the analytics, such as views, conversions, and clicks for ad creatives, aggregated on a daily basis. |
Page Stats | Contains details of the view and click statistics related to your company’s LinkedIn page(s). |
Follower Stats | Contains details of the statistics associated to the followers on your company’s LinkedIn page(s). |
Share Stats | Contains details of the statistics associated to sharing on your company’s LinkedIn page(s). It might include shares made by other pages, visitors, or the company itself. |
Video Ads | Contains details of the ads listed on your company’s LinkedIn page(s) in the video format. |
Additional Information
Read the detailed Hevo documentation for the following related topics:
Limitations
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LinkedIn restricts the amount of data that can be fetched from certain objects. As a result, with the All Available Data option, Hevo ingests historical data for a limited period from them. The following table lists the time and the affected objects:
Time Objects Up to six months - Ad Analytics by Campaign
- Ad Analytics by CreativeUp to one year - Page Stats
- Follower Stats
- View Stats
Revision History
Refer to the following table for the list of key updates made to this page:
Date | Release | Description of Change |
---|---|---|
Mar-05-2024 | 2.21 | Updated the ingestion frequency table in the Data Replication section. |
Sep-22-2023 | NA | Removed the banner from the top of the page about migration to versioned APIs. |
Jul-25-2023 | NA | Updated section, Data Model for better clarity. |
Jun-19-2023 | 2.14 | - Added a banner at the top of the page to mention about migration to versioned APIs. - Updated section, Data Model to add information about versioned APIs. |
Feb-20-2023 | NA | Updated section, Configuring LinkedIn Ads as a Source to update the information about historical sync duration. |
Jul-11-2022 | NA | Updated the ERD table in the Schema and Primary Keys section. |
Oct-25-2021 | NA | Added the Pipeline frequency information in the Data Replication section. |
Jul-26-2021 | NA | Added a note in the Overview section about Hevo providing a fully-managed Google BigQuery Destination for Pipelines created with this Source. |