- About Hevo
- Hevo Features
- Hevo System Architecture
- Core Concepts
- Free Trials
- Regulatory Compliance
- Scheduling a Demo
- Hevo Support
- General FAQs
- Getting Started
- Creating an Account in Hevo
- Connecting Through SSH
- Connecting Through Reverse SSH Tunnel
- 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
- Types of Data Synchronization
- Ingestion Modes and Query Modes for Database Sources
- Ingestion and Loading Frequency
- 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
- 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
- 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
- QuickBooks Time
- Finance & Accounting Analytics
- Amazon Ads
- Apple Search Ads
- Facebook Ads
- Facebook Page Insights
- Firebase Analytics
- Google Ads
- Google Analytics
- Google Analytics 4
- Google Analytics 360
- Google Play Console
- Google Search Console
- Instagram Business
- LinkedIn Ads
- Microsoft Ads
- Pinterest Ads
- SendGrid Webhook
- Salesforce Marketing Cloud
- Snapchat Ads
- TikTok Ads
- Twitter Ads
- YouTube Analytics
- Product Analytics
Sales & Support Analytics
- Help Scout
- Hub Planner
- Salesforce Bulk API V2
- 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 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
- Structure of Data in the Google BigQuery Data Warehouse
- 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 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 2.18
- Release Version 2.17
- Release Version 2.16
- Release Version 2.15
- 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
- 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
Google Analytics 4
Google Analytics 4 (GA 4) is the latest version of Google Analytics. It allows in-depth assessment of user experiences across your websites and applications using reports. Each of these websites and apps is referred to as GA 4 property and has a unique tracking ID, which enables the monitoring and analysis of activities associated with the respective property.
Hevo uses the Google Analytics Data API (GA 4) to ingest your GA 4 account data. You must allow Hevo to access data from your Google account to do this.
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 Google Analytics 4 (GA 4) account from which data is to be ingested exists.
Configuring the Google Analytics 4 Property
If you are an existing user of Google Analytics, you must configure the GA 4 property in your Google Analytics account before configuring GA 4 as a Source in Hevo.
If you are a new user without an existing Google Analytics account, skip to Configuring Google Analytics 4 as a Source.
Note: Read Configuring the Google Analytics 4 Property for your Firebase Account (Optional) if you want to configure GA 4 property in your existing Firebase account.
Configuring Google Analytics 4 as a Source
Perform the following steps to configure GA 4 as the Source in Hevo:
Click PIPELINES in the Navigation Bar.
Click + CREATE in the Pipelines List View.
In the Select Source Type page, select Google Analytics 4 as the Source.
In the Configure your Google Analytics 4 Account page, do one of the following:
Select a previously configured account and click CONTINUE.
Click + ADD GOOGLE ANALYTICS 4 ACCOUNT and perform the following steps to configure an account:
Select your linked Google account.
Click Allow to grant Hevo access to your analytics data.
In the Configure your Google Analytics 4 Source page, specify the following:
Pipeline Name: A unique name for your Pipeline, not exceeding 255 characters.
Authorized Account (Non-editable): The email address that you selected earlier when connecting to your Google account.
GA4 Account Name: The GA 4 account from which you want to replicate the data. One Google account can contain multiple analytics accounts.
Property Name: The website or app from which you want Hevo to read the user data. This field appears once you select the GA4 Account Name from the drop-down.
Historical Sync Duration: The duration for which you want to ingest the existing data from the Source. Default duration: 6 Months.
Report Name: A unique name for your report, not exceeding 30 characters.
Dimensions: The attributes for which you want to see the data in your report. For example, in a Website property, the dimensions can include city, country, and device category. Read Analytics Dimensions and Metrics to know more about the dimensions available in GA 4.
Metrics: The numerical measurement of data as per the dimensions selected above. For example, in a Website property, the metrics can include the number of viewers, new sign-ups, and number of clicks. Read Analytics Dimensions and Metrics to know more about the metrics available in GA 4.
Pivot Report: If enabled, Hevo creates additional reports by rearranging the data with a subset of dimensions and metrics from the above report. Default setting: Disabled.
Pivot Dimensions: The subset of dimensions from the parent report for which you want to rearrange the data.
Pivot Metrics: The subset of metrics from the parent report for which you want to rearrange the data.
Pivot Aggregation Function: The aggregation function you want to use to rearrange the data.
Advanced Options: The conditions to filter the data from the above report based on your business requirement.
+ ADD ANOTHER REPORT: Use this option to add up to five reports.
Click TEST & CONTINUE.
Proceed to configuring the data ingestion and setting up the Destination.
|Default Ingestion Frequency||Minimum Ingestion Frequency||Maximum Ingestion Frequency||Custom Frequency Range (Hrs)|
|1 Hr||15 Mins||12 Hrs||1-12|
Note: The custom frequency must be set in hours, as an integer value. For example, 1, 2, and 3 but not 1.5 or 1.75.
Historical Data: The first run of the Pipeline ingests historical data for the selected reports on the basis of the historical sync duration specified at the time of creating the Pipeline and loads it to the Destination. Default duration: 6 Months.
Incremental Data: Once the historical data ingestion is complete, every subsequent run of the Pipeline fetches new and updated data for the reports.
Note: Hevo retrieves the incremental data for the reports in a single run of the Pipeline by creating batches of data rather than calling the API for each report separately. This is done to reduce the number of calls made to the GA 4 API.
Data Refresh: Hevo re-ingests the data daily for the past three days.
Schema and Primary Keys
Hevo uses the dimensions in a report as primary keys.
To represent pivot reports, Hevo adds the suffix
_pivotto the report name.
aggregation_functioncolumn in the pivot report contains sum, minimum, maximum, or count values.
For example, if you want to check the maximum page views for each page on your website daily, the count value represents the number of page views, and the maximum value represents the maximum page views.
To fetch data for the Interests, User Age, and Gender dimensions, you must:
Hevo does not support the ingestion of cohort dimensions and metrics.
Hevo might take more than 24 hours to fetch accurate data for some reports because of the GA 4 data freshness intervals. Therefore, data replication might not be accurate, leading to discrepancies in the Destination. To avoid this, you can add a clause and exclude dimensions with null values while configuring the Source.
Refer to the following table for the list of key updates made to this page:
|Date||Release||Description of Change|
|Aug-28-2023||NA||Updated the page as per the latest Hevo functionality.|
|Jul-12-2023||NA||Updated section, Limitations to add information about GA4 data freshness intervals.|
|Apr-25-2023||NA||Updated the page to move information about Firebase Analytics to the Firebase Analytics page.|
|Apr-04-2023||NA||Updated section, Configuring Google Analytics 4 as a Source for more clarity.|
|Sep-05-2022||NA||Updated section, Data Replication to reorganize the content for better understanding and coherence.|
|Oct-25-2021||NA||Added the Pipeline frequency information in the Data Replication section.|
|Jul-26-2021||NA||Added the section, Source Considerations.|