- 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
- Activity Log
- 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
- Pipeline Objects
Python Code-Based Transformations
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
- Examples of Python Code-based Transformations
- Transformation Methods in the Event Class
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
- Troubleshooting Failed Events in a Pipeline
- Mismatch in Events Count in Source and Destination
- 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
- File Log
- 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
- 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?
- Why am I unable to modify my OAuth Source connection settings?
- 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?
- Which file formats are supported by file storage-based Sources?
- 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 create a Destination through API?
- 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?
- When will I be charged for my subscription?
- 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?
- What are the payment methods available in Hevo?
- Can you explain the pricing plans in Hevo?
- Where do I get invoices for payments?
- Is my billing information removed upon account deletion?
- 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 2.10
- 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 new and improved version of Google Analytics that allows you to analyze the interaction data from your websites and mobile applications using reports. Each of these websites and mobile applications is referred to as a GA 4 property and is associated with a unique tracking ID.
Hevo allows you to generate analytical reports based on the data stored in the GA 4 property. These reports are made up of:
Metrics: These are statistical parameters that you measure for websites and mobile applications.
Dimensions: These are attributes in a report for which you want to see the statistics.
Optionally, you can create pivot reports that are generated by applying an aggregation on top of selected dimensions and metrics in the parent report. You can create only one pivot report per parent report.
Hevo uses the Google Analytics Data API (GA 4) to replicate your GA 4 data into the desired Destination system 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 Google Analytics 4 account. Or, a Firebase account linked to Google Analytics 4.
Configuring the Google Analytics 4 Property (Optional)
If you are an existing user of Firebase or Google Analytics, you must configure the GA 4 property in your respective Firebase or Google Analytics account before configuring GA 4 as a Source in Hevo.
To configure a GA 4 property in your existing Firebase account, read this.
To configure a GA 4 property in your existing Google Analytics account, read this.
If you are a new user without an existing Firebase or Google Analytics account, skip to Configuring Google Analytics 4 as a Source.
Configuring Google Analytics 4 as a Source
Perform the following steps to configure GA 4 as the Source in Hevo:
Click PIPELINES in the Asset Palette.
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, click Add Account.
Select your linked Google account and click Allow to provide Hevo read 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.
Account Name: The authorized Google account to which the analytics accounts are connected.
Property Name: The website, application, or entity associated with the account for which user analytics data is to be read.
Historical Sync Duration: The duration for which past data must be ingested. Default: 6 Months.
Report Name: A unique name for your report, not exceeding 30 characters.
Dimensions: Select all the dimensions you need in your report.
Metrics: Select all the metrics you need in your report.
Pivot Report (Optional): A report generated by applying an aggregation on the selected dimension and metrics. This option is disabled by default.
Pivot Dimensions: Select a subset of the dimensions selected in the parent report.
Pivot Metrics: Select a subset of the metrics selected in the parent report.
Pivot Aggregation Function: Select the functions you want to apply in the pivot report. For example, SUM, MINIMUM, MAXIMUM, COUNT.
ADD ANOTHER REPORT (Optional): Use this option to create up to five reports and five pivot reports.
Note: You cannot modify any field post-Pipeline creation.
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||15 Mins||12 Hrs||1-12|
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: In the first run of the Pipeline, Hevo ingests historical data daily for all the reports based on the historical sync duration selected 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 fetches the incremental data for all the reports in one go and optimizes the number of API calls made to the Google Analytics 4 Data API.
Data Refresh: Hevo refreshes the data daily for the last three days.
Schema and Primary Keys
All the dimensions in a report are set as primary keys.
_pivotis added to the report name to represent pivot reports.
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.
Read the detailed Hevo documentation for the following related topics:
- To fetch data for the
userGender dimensions, Google Signals must be enabled and the data thresholds enforced by Google Analytics 4 must be met. For more information, read Activating Google signals and Data thresholds.
- Hevo does not support cohort dimensions and metrics.
Refer to the following table for the list of key updates made to this page:
|Date||Release||Description of Change|
|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.|