Custom
Custom Report enables a user to create a user specific report. They can choose the Dimensions such as city, browser, etc and Metrics such as sessions, pageviews, bounce rate etc for displaying. A user must specify at least one dimension and one metric of their choosing for the custom report to be generated.
You can read more about this here
Configuring the Credentials
Select the account credentials which has access to relevant Google Analytics data from the dropdown menu & Click Next
Data Pipelines Details
- Data Pipeline
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Select Custom from the dropdown
- Account
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Select one or more accounts from the drop-down for Analytics, and the topmost level of organization.
All accounts which your credentials have access to should be available here. If they are not, please check the credentials selected / configured by you. While you can add multiple accounts, the table size may become too large and so it is advisable to add one account per pipeline and use Union queries in the data warehouse to join the data for consumption |
- Property
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An account can have one or more properties such as Website, mobile application, blog, etc. Select the desired Property as per the requirement.
- Views
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Views are the access point for reports. They enable a defined view of a visitor data from a property. You can give users access to a view so that the user will be able to view reports based on that view’s data. A property can contain one or more views. Select the desired views for the selected Account.
Setting Parameters
See the list of supported metrics/dimensions here.
Parameter | Description | Values |
---|---|---|
Delete or Append |
Required This refers to the manner in which data will get updated in the data warehouse, with 'Delete' selected, the data will be upserted (only new records or records with changes) and with 'Append' selected, all data fetched will be inserted. Selecting 'Replace' will ensure the table is dropped and recreated with fresh data on each run. Recommended to use "Delete" option unless there is a specific requirement. |
{Delete, Append, Replace} Default Value: Delete |
No of Days |
Required Number of days for which you wish to get the data in each run. |
Integer value (Recommended value 2) |
DimensionFilter |
Optional A valid dimension filter in JSON format. Please check Batch get parameters |
JSON value |
MetricFilter |
Optional A valid metrics filter in JSON format. Please check Batch get parameters |
JSON value |
Segments |
Optional A segment helps you to narrow down the aggregated data Google Analytics shows, into data you want to see and need, to answer a specific question you have. You can select more than one segment. |
Multiple selection values |
Custom SegmentIds |
Optional The Custom SegmentId field can be used in the Data Export API segment parameter. |
Multiple selection values |
Please note that not all metrics and dimensions are compatible with each other. Learn more about this here |
Datapipeline Scheduling
Scheduling specifies the frequency with which data will get updated in the data warehouse. You can choose between Manual Run, Normal Scheduling or Advance Scheduling.
- Manual Run
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If scheduling is not required, you can use the toggle to run the pipeline manually.
- Normal Scheduling
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Use the dropdown to select an interval-based hourly, monthly, weekly, or daily frequency.
- Advance Scheduling
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Set schedules fine-grained at the level of Months, Days, Hours, and Minutes.
Detailed explanation on scheduling of pipelines can be found here
Dataset & Name
- Dataset Name
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Key in the Dataset Name(also serves as the table name in your data warehouse).Keep in mind, that the name should be unique across the account and the data source. Special characters (except underscore _) and blank spaces are not allowed. It is best to follow a consistent naming scheme for future search to locate the tables.
- Dataset Description
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Enter a short description (optional) describing the dataset being fetched by this particular pipeline.
- Notifications
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Choose the events for which you’d like to be notified: whether "ERROR ONLY" or "ERROR AND SUCCESS".
Once you have finished click on Finish to save it. Read more about naming and saving your pipelines including the option to save them as templates here
Still have Questions?
We’ll be happy to help you with any questions you might have! Send us an email at info@datachannel.co.
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