# Google Analytics MCF

## Pipeline Concepts

Before setting up the pipeline, learn about pipeline concepts [here](/product/ingesting-your-data/pipelines.md)

## Step by Step Guide

### STEP-1: Configure Connection

To learn about Connection, refer[ here](/product/ingesting-your-data/pipelines.md)

* Log into Sprinkle application
* Navigate to Ingest -> Connections Tab -> New Connection -> 
* Select Google Analytics MCF
* Provide all the mandatory details
  * *Name*: Name to identify this connection
  * Connect to Google
  * *Advance Settings*: Refer [here](#advanced-connection-settings)
* After pressing Connect to Google, you will see authorise screen to allow permissions required for sprinkle to read data. Press Allow
* Test Connection
* Create

### STEP-2: Configure pipeline

To learn about datasource, refer [here](/product/ingesting-your-data/pipelines.md)

* Navigate to Ingest -> Pipeline Tab -> Add -> 
* Select Google Analytics MCF
* Provide the name -> Create
* **Connection Tab**: 
  * From the drop-down, select the name of connection created in STEP-2
  * Update

### STEP-3: Create Dataset

**Datasets Tab**: To learn about Dataset, refer [here](/product/ingesting-your-data/pipelines.md). Add Dataset for each report/dataset that you want to integrate, providing following details

* *Account Id* (Required) : GA Account
* *View Id* (Required) : Select Project/View available in this account
* Metrics (Required) : Select upto 10 metrics
* Dimensions (Optional) : Select upto 7 dimensions to aggregate your metrics on
* *Start Date* (Required) : Pull the data from this date: Format is YYYY-MM-DD
* *Destination Schema* (Required) : Data warehouse schema where the table will be ingested into
* *Destination Table name* (Required) : It is the table name to be created on the warehouse. If not given, sprinkle will create like ds\_\<datasourcename>\_\<tablename>
* *Destination Create Table Clause*: Provide additional clauses to warehouse-create table queries such as clustering, partitioning, and more, useful for optimizing DML statements. [Learn more](/product/ingesting-your-data/pipelines/databases/features/destination-create-table-clause.md) on how to use this field.
* Create

### STEP-4: Run and schedule Ingestion

In the **Ingestion Jobs** ta&#x62;**:**

* Trigger the Job, using Run button
* To schedule, enable Auto-Run. Change the frequency if required

### Advanced Connection Settings

* **API Read Timeout (In seconds) :**  Maximum time of inactivity between two data packets when waiting for the server's response. The default value is 30 seconds.
* **API Connection Timeout (In seconds) :** Time period within which a connection between a client and a server must be established.&#x20;
* **Retry Limit :** Number of retries allowed when an API call fails. For example if an API call fails and retry limit is 5 then it will check 5 times for that API call and if it succeeded then it will stop checkin&#x67;**.**
* **Retry Sleep Time (In milliseconds) :**&#x47;iven time, after which retry should happen in case an API call fails.
* **Incremental Batch Size (In days) :** No. of days in one batch for which data is being downloaded during incremental ingestion.
* **Version :** It gives information about the version of Google Analytics MCF API being used.
* **Max Records :** Field sets the max limit on the number of records that can be downloaded during each API call.&#x20;

### Dataset Fields

All the datasets can have following fields.

* mcf\_firstImpressionConversions
* mcf\_firstImpressionValue
* mcf\_impressionAssistedConversions
* mcf\_impressionAssistedValue
* mcf\_totalConversions
* mcf\_totalConversionValue
* mcf\_assistedConversions
* mcf\_assistedValue
* mcf\_firstInteractionConversions
* mcf\_firstInteractionValue
* mcf\_lastInteractionConversions
* mcf\_lastInteractionValue
* event\_date


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