- 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
-
Transformations
-
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
-
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
- Audit Tables
- Activity Log
-
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
-
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
- 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
-
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
- Finance & Accounting Analytics
-
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
-
Data Warehouses
- Amazon Redshift
- Amazon Redshift Serverless
- Azure Synapse Analytics
- Databricks
- Firebolt
- Google BigQuery
- Hevo Managed Google BigQuery
- Snowflake
-
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 2.31 (Nov 18-Dec 16, 2024)
- Release 2.30 (Oct 21-Nov 18, 2024)
-
2024 Releases
- Release 2.29 (Sep 30-Oct 22, 2024)
- 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)
-
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
-
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)
-
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)
-
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
Google Analytics
Effective July 1, 2023, Google Analytics (GA) will stop processing data. As a result, your GA Pipelines will not replicate data. To avoid any data loss, we recommend that you create a Pipeline with Google Analytics 4 as the Source.
Hevo replicates data from your Google Analytics account to your data warehouse using Google’s Reporting API. We recommend that you go through the Google Analytics Query Explorer before creating a Pipeline to ensure you configure it the way you require. Read Core Reporting API - Common Queries to know more about the common queries associated with Google’s Reporting API.
For all Pipelines created after Release 2.01, Hevo allows you to ingest a combination of prebuilt and custom reports during and post-Pipeline creation, according to your requirements. Refer to section, Configuring Google Analytics as a Source to know how you can ingest these reports.
Prerequisites
-
An active Google Analytics account from which data is to be ingested exists. Contact the administrator of your Google Analytics account if you do not have access.
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You are assigned the Team Administrator, Team Collaborator, or Pipeline Administrator role in Hevo to create the Pipeline.
Adding Users to your Google Analytics Account (Optional)
Note: You can add other users to your Google Analytics account only if you have the Administrator role.
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Sign in to your Google Analytics account.
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In the left navigation pane, click Admin, and navigate to the column, such as Account, Property, or View, to which you want to add a user. For example, if you want to add a user to a property, navigate to the Property column.
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From the drop-down of the column, select the name of the account, property, or view, as appropriate, and click Access Management. For example, if you want to add a user to a property, in the Property column, select a property name, such as Hevo Docs from the drop-down, and click Property Access Management.
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In the selected Access management screen, click the Plus ( ) icon, and then click Add users.
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In the Add roles and data restrictions screen:
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Specify the email addresses of the users you want to add.
Note: Only users with an existing Google account can be added.
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(Optional) Select the Notify new users by email check box, to inform the users.
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Select the role you want to assign. The users should be granted at least the Viewer role.
-
-
Click Add.
You have successfully added users to your Google Analytics account.
Providing Hevo Access to your Google Analytics Account
Hevo needs permission to view your reports and other reporting entity details. You can read more about these permissions here.
Configuring Google Analytics as a Source
Perform the following steps to configure Google Analytics as the Source in Hevo:
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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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In the Select Source Type page, select Google Analytics.
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In the Configure your Google Analytics 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 GOOGLE ANALYTICS ACCOUNT and perform the following steps to configure an account:
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Select your linked Google account.
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Click Allow to provide Hevo
read
access to your analytics data.
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-
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In the Configure your Google Analytics Source page, specify the following:
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Pipeline Name: A unique name for your Pipeline, not exceeding 255 characters.
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Report: Select one of the following report types to ingest data from your Google Analytics reports:
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Prebuilt Reports: Hevo provides you with a few reports, that it creates using a valid combination of metrics and dimensions. You can use these reports according to your requirements, to replicate data from that report to your desired Destination quickly and efficiently. Refer to section, Prebuilt Reports for steps to configure this.
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Custom Reports: Hevo allows you to create your own reports by choosing a combination of metrics and dimensions according to your requirements. Then, the data from these reports is replicated to your desired Destination. Refer to section, Custom Reports for steps to configure this.
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Historical Sync Duration: The duration for which you want to ingest the existing data from the Source. Default duration: 90 days.
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Advanced Options: The segments that you can apply to the reports to filter the data from these reports, and ingest only the required data. Read Segments to know more about segments and how you can use them in Google Analytics.
-
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Click TEST & CONTINUE.
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Proceed to configuring the data ingestion and setting up the Destination.
Prebuilt Reports
Hevo provides you with a few prebuilt reports for ease of configuration that you can use according to your requirements. It automatically identifies the metrics and dimensions based on the Google Analytics report that you select for replicating data to your desired Destination.
To configure prebuilt reports, specify the following:
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Report Name: A unique name for your report, not exceeding 30 characters.
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GA Account Name: The Google Analytics (GA) account from which you want to replicate the data. One Google account can contain multiple Analytics accounts.
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Property Name: The website, application, or entity for which user analytics data is to be read.
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View Name: The view on which reports must be accessed. Read Hierarchy of organizations, accounts, users, properties, and views to understand the Analytics account hierarchy.
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Prebuilt Report Name: The report whose data you want to replicate to the Destination.
The Metrics and Dimensions for a prebuilt report are automatically configured by Hevo. Read Google Analytics Reports, Metrics, and Dimensions to know more about the various reports created by Hevo.
Note: You cannot modify these metrics and dimensions. You must select Custom Reports if you want to select metrics and dimensions according to your requirements.
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Advanced Options: The metric or dimension filter clauses that you can apply to the reports to filter the data from these reports, and ingest only the required data. Read Google Analytics Filters to know more about metric and dimension filter clauses in Google Analytics.
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ADD ANOTHER REPORT (Optional): Use this option to add another prebuilt report or create another custom report whose data you want to replicate to the Destination.
Custom Reports
Hevo allows you to create your own reports by choosing a valid combination of metrics and dimensions. You can manually select these metrics and dimensions in Hevo to replicate the data from these reports to your desired Destination.
To configure custom reports, specify the following:
-
Report Name: A unique name for your report, not exceeding 30 characters.
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GA Account Name: The Google Analytics (GA) account from which you want to replicate the data. One Google account can contain multiple Analytics accounts.
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Property Name: The website, application, or entity for which user analytics data is to be read.
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View Name: The view on which reports must be accessed. Read Hierarchy of organizations, accounts, users, properties, and views to understand the Analytics account hierarchy.
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Metrics: The various parameters that enable you to quantitatively measure the data present in the view you selected above. For example, for a view named Website, the metrics can include number of viewers, new signups, number of clicks, and so on. Read Metrics to know about how metrics are calculated.
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Dimensions: The attributes or characteristics of your data based on the Metrics you selected above. For example, for a view Website, and the metric number of viewers, the dimensions can include past 7-day views, 14-day views, and so on. Read Dimensions to know about valid dimension-metric combinations.
Note: Only the dimensions compatible with the metric selected above are available for selection. Refer to section, Source Considerations.
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Advanced Options: The metric or dimension filter clauses that you can apply to the reports to filter the data from these reports, and ingest only the required data. Read Google Analytics Filters to know more about metric and dimension filter clauses in Google Analytics.
-
ADD ANOTHER REPORT (Optional): Use this option to add another prebuilt report or create another custom report whose data you want to replicate to the Destination.
Data replication
Default Pipeline Frequency | Minimum Pipeline Frequency | Maximum Pipeline Frequency | Custom Frequency Range (Hrs) |
---|---|---|---|
1 Hr | 15 Mins | 24 Hrs | 1-24 |
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.
Schema Mapping Considerations
During ingestion of the report data, the following additional columns are created in the Destination database along with metrics
and dimension
:
-
__hevo_id
: Represents a unique ID of each unique Event present in the Source data. Hevo derives this from the primary key columns of your Google Analytics data. -
__hevo_report_date
: Represents the date on which a report is fetched by Hevo.
Additional Information
Read the detailed Hevo documentation for the following related topics:
Source Considerations
-
Hevo is subject to the limits and quotas set on the Core Reporting API. Therefore, ingestion may be deferred due to these limits.
-
You can only select the dimensions that are compatible with the metric you select. Incompatible metrics are greyed out based on the selected dimensions.
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Even for compatible metric/dimension combinations, an error may be displayed stating that the selected metrics and dimensions cannot be queried together, or that the selected metrics/dimensions are restricted. If the metric/dimension set belongs to Google Adwords, Google Analytics 360, or Google Adsense, this may be due to lack of permissions on the selected view.
For information on valid metric/dimension combinations, refer to Dimensions and Metrics Explorer.
For information on different types of errors, refer to Google Analytics Core Reporting API Changelog.
Revision History
Refer to the following table for the list of key updates made to this page:
Date | Release | Description of Change |
---|---|---|
Nov-08-2022 | 2.01 | Updated the page to mention about adding multiple reports while creating a Pipeline. |
Oct-25-2022 | 2.00 | Added the section, Adding Users to your Google Analytics Account with steps to provide access to the Google Ads account. |
Jul-12-2022 | 1.92 | - Added sections, Prebuilt Reports and Custom Reports. - Updated section, Configuring Google Analytics as a Source. |
Mar-07-2022 | 1.83 | Updated sections, Configuring Google Analytics as a Source and Schema Mapping Considerations to add support for Segments. |
Jan-03-2022 | 1.79 | Added information about reverse historical load in the Data Replication section. |
Oct-25-2021 | NA | Added the Pipeline frequency information in the Data Replication section. |
Mar-09-2021 | 1.58 | Added section Schema Mapping Considerations. |