- About Hevo
- Hevo Features
- Hevo System Architecture
- Core Concepts
- Free Trials
- Regulatory Compliance
- Hevo Support
- General FAQs
- Getting Started
- Creating an Account in Hevo
- Connection Options
- Familiarizing with the UI
- Creating your First Pipeline
- Data Loss Prevention and Recovery
- Data Ingestion
- Types of Data Synchronization
- Ingestion Modes and Query Modes for Database Sources
- Ingestion and Loading Frequency
- Ingestion Frequency and Data Synchronization
- Data Ingestion Statuses
- Deferred Data Ingestion
- Handling of Primary Keys
- Handling of Updates
- Handling of Deletes
- Hevo-generated Metadata
- 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
- Data Flow in a Pipeline
- Familiarizing with the Pipelines UI
Working with Pipelines
- Best Practices for Creating Database Pipelines
- Creating a Pipeline
- Connectivity Check for RDBMS Sources
- Scheduling a Pipeline
- Modifying a Pipeline
- Prioritizing a Pipeline
- Viewing Pipeline Progress
- Pausing and Deleting a Pipeline
- Log-based Pipelines
- Troubleshooting Data Replication Errors
- Managing Objects in Pipelines
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
- 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
- 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
- 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
- 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
- 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
- Free Sources
Databases and File Systems
- Data Warehouses
- Connecting to a Local Database
- Amazon DocumentDB
- Amazon DynamoDB
- Generic MongoDB
- MongoDB Atlas
- Support for Multiple Data Types for the _id Field
- Example - Merge Collections Feature
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
- Amazon RDS SQL Server
- Azure SQL Server
- Google Cloud SQL Server
- Generic SQL Server
- Troubleshooting SQL Server
- SQL Server FAQs
- Amazon Aurora MySQL
- Amazon RDS MySQL
- Azure MySQL
- Google Cloud MySQL
- Generic MySQL
- MariaDB 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
- Amazon Aurora PostgreSQL
- Amazon RDS PostgreSQL
- Azure PostgreSQL
- Google Cloud PostgreSQL
- Generic PostgreSQL
- Heroku 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
- Amazon S3
- Azure Blob Storage
- FTP / SFTP
- Google Cloud Storage (GCS)
- Google Drive
- Google Sheets
- Android SDK
- 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?
- Jira Cloud
- Finance & Accounting Analytics
- Apple Search Ads
- Facebook Ads
- Facebook Page Insights
- Firebase Analytics
- Google Campaign Manager
- Google Ads
- Google Analytics
- Google Analytics 4
- Google Analytics 360
- Google Play Console
- Google Search Console
- Instagram Business
- LinkedIn Ads
- Microsoft Advertising
- Pinterest Ads
- SendGrid Webhook
- Salesforce Marketing Cloud
- Snapchat Ads
- TikTok Ads
- Twitter Ads
- YouTube Analytics
- Product Analytics
Sales & Support Analytics
- Help Scout
- Hub Planner
- Toggl Track
- 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?
- Familiarizing with the Destinations UI
- Amazon Aurora MySQL
- SQL Server
- Connecting to a Local Database
- Limitations of using MySQL as a Destination
- Structure of Data in the Amazon Redshift Data Warehouse
- Loading Data to an Amazon Redshift Data Warehouse
- Troubleshooting Amazon Redshift Destination
- Amazon Redshift FAQs
- Azure Synapse Analytics
- Clustering in BigQuery
- Partitioning in BigQuery
- Loading Data to a Google BigQuery Data Warehouse
- Near Real-time Data Loading using Streaming
- Troubleshooting Google BigQuery
- Google BigQuery FAQs
- Hevo Managed Google BigQuery
- Structure of Data in the Snowflake Data Warehouse
- Loading Data to a Snowflake Data Warehouse
- Troubleshooting Snowflake
- Snowflake FAQs
- Amazon Redshift
- 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?
- dbt™ Models
- Familiarizing with the Models UI
- Types of Models
- Key Features
- Working with SQL Models
- Previewing a Model
- Viewing the Query History
- Legacy Models
- Models FAQs
- Account Management
- Personal Settings
- Team Settings
- Pricing Plans
- Time-based Events Buffer
- Setting up Pricing Plans, Billing, and Payments
- On-Demand Purchases
- Billing Alerts
- Viewing Billing History
- Billing Notifications
- 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 Concepts
- Familiarizing with the Activate UI
- Working with Activate
- Activate Warehouses
- Activate Targets
- 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
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. With LinkedIn Ads, you can target your most valuable audiences using accurate, profile-based first-party data.
You can use Hevo Pipelines to replicate your LinkedIn reports to the desired Destination database or data warehouses for scalable analysis.
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.
An active LinkedIn account with access to at least one advertiser profile.
Adminaccess to the organization’s LinkedIn page.
Note: You can create a Pipeline without
Adminaccess too. However, you will not be able to access certain objects such as
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:
Click PIPELINES in the Navigation Bar.
Click + CREATE in the Pipelines List View.
In the Select Source Type page, select LinkedIn Ads.
In the Configure your LinkedIn Ads Account page, click ADD LINKEDIN ADS ACCOUNT.
Provide credentials for your LinkedIn account which has access to at least one advertiser profile, and click Sign In.
Click Allow to authorize Hevo to access your advertiser profile to read reporting data.
In the Configure your LinkedIn Ads Source page, specify the following:
Pipeline Name: A unique name for the Pipeline.
Select Accounts: Select the advertiser profiles for replicating the reports data.
Historical Sync Duration: The duration for which the existing data in the Source must be ingested. 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.
Click TEST & CONTINUE.
Proceed to configuring the data ingestion and setting up the Destination.
|Default Pipeline Frequency||Minimum Pipeline Frequency||Maximum Pipeline Frequency||Custom Frequency Range (Hrs)|
|1 Hr||1 Hr||48 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.
Historical Data: Hevo ingests the historical data for
statsobjects on the basis of the historical sync duration selected at the time of creating the Pipeline. See Limitations.
Incremental Data: Once the historical data ingestion is complete, every subsequent run of the Pipeline fetches the entire data for the objects you select. All objects apart from
statsare loaded from scratch on every run.
Data Refresh: Data for the last 30 days is refreshed on a rolling basis for
ad_analyticsobjects. Data for
statsobjects 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 in the Destination database:
The following is the list of tables (objects) that are created at the Destination when you run the Pipeline:
|Account||Individual ad accounts listed under an advertiser.|
|Account User||Details for all the ad account members, who have permissions to the ad account in LinkedIn Campaign Manager, along with details of their roles.|
|Campaign||Details of all campaigns such as ID, account, campaign group, name, type, and status fields.|
|Campaign Group||Details about the campaign group, such as status, budget, and performance schedules across multiple related campaigns.|
|Creative||All activity related information of all ad creatives.
Note: Hevo does not store raw information of the creative such as the text or images.
|Conversion||Conversion tracking Events for all LinkedIn Ad campaigns.|
|Ad Analytics by Campaign||Daily ad-level aggregated analytical data containing details of all views, conversions, and click-level data of various types of ad campaigns.|
|Ad Analytics by Creative||Daily ad creative-level aggregated analytical data containing details of all views, conversions, and click-level data of various types of ad campaigns.|
|Page Stats||Daily page statistics for all LinkedIn pages listed under the organisation.|
|Follower Stats||Daily follower statistics for all LinkedIn pages listed under the organisation.|
|Share Stats||Daily share statistics for all LinkedIn pages listed under the organisation. Shared statistics could be for shares done by the organisation’s page itself, or by visitors or other pages.|
|Video Ads||Details of video ads for all LinkedIn pages listed under the organisation.|
Read the detailed Hevo documentation for the following related topics:
All available datawill fetch data up to 6 months for
Ad Analytics by Campaignand
Ad Analytics by Creativeand up to one year for
View statisticsdue to limits enforced by LinkedIn.
Refer to the following table for the list of key updates made to this page:
|Date||Release||Description of Change|
|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.|