# Google Analytics MCF ## Pipeline Concepts Before setting up the pipeline, learn about pipeline concepts [here](https://docs.sprinkledata.com/product/ingesting-your-data/pipelines) ## Step by Step Guide ### STEP-1: Configure Connection To learn about Connection, refer[ here](https://docs.sprinkledata.com/product/ingesting-your-data/pipelines) * 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](https://docs.sprinkledata.com/product/ingesting-your-data/pipelines) * 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](https://docs.sprinkledata.com/product/ingesting-your-data/pipelines). 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\_\\_\ * *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](https://docs.sprinkledata.com/product/ingesting-your-data/pipelines/databases/features/destination-create-table-clause) on how to use this field. * Create ### STEP-4: Run and schedule Ingestion In the **Ingestion Jobs** tab**:** * 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. * **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 checking**.** * **Retry Sleep Time (In milliseconds) :**Given 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. ### 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