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Connecting to Google Cloud Storage

Overview

Google cloud Storage enables you to store, access, and maintain data so that you do not need to own and operate data centers, moving expenses from a capital expenditure model to operational. You can use SkyPoint's built-in connector for importing data from Google Cloud Storage.

This document will guide you through the process of connecting Google Cloud Storage to SkyPoint Modern Data Stack Platform.

Prerequisite

You will need the following details to configure and import data using Google Cloud Storage:

  • Access key ID and Secret access key
  • Project ID
  • Service URL
  • Service account JSON file
  • Google cloud bucket.

Permissions required for Service account

You can control the access to the resources in your Google Cloud project with the help of IAM (Identity and Access Management). The resources comprise of Cloud Storage buckets and objects that are stored within buckets, along with other Google Cloud entities such as Compute Engine instances.

Permissions allow principals to perform specific actions on buckets or objects in Cloud storage. There are two options to prepare the Google cloud permissions and storage:

  • Option 1: Using the Transfer Appliance Cloud Setup Application
  • Option 2: Configuring Google Cloud permissions and Cloud Storage step-by-step.
note

You need to create the JSON file and Permissions by logging into Google Cloud Console. You can refer to the Setting up Google Cloud Storage document to learn more.

Import data using Google Cloud Storage connector

Follow the below steps to create a new dataflow for the Google Cloud Storage import connector:

  1. Go to Dataflow > Imports.
  2. Click New dataflow.

The Set dataflow name page appears.

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  1. In the Set dataflow name page, type dataflow name in the Name text area.
  2. Click Next.

The Choose connector page appears.

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To add Google Cloud Storage connector

  1. In the Choose connector page, select Google Cloud Storage connector.
note

You can use the Search feature too to find the connector. Also, the Google Cloud Storage connector can be found under Cloud category.

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  1. Enter Display Name for your dataflow in the text area.
  2. Enter Description for your dataflow in the text area.
  3. Click Next.

The Connect to Google Cloud Storage page appears.

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To configure Google Cloud Storage

Follow the below steps to configure the connection to Google Cloud Storage:

  1. Enter your credentials such as Access key ID, Secret access key, Project ID, and Service URL to configure with Google Cloud Storage.
  2. Click Choose file to upload the JSON file.
  3. Click the Folder icon in the Google cloud bucket text area.

Once you select the cloud bucket, the Table Details columns appear.

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  1. Enter the Table Details to process the data.
ItemDescription
PurposeOption to assign a purpose (Data or Metadata) for each table.
Data
Loads customer data.
Metadata
Loads Metadata.
File NameDisplays the name of the file that you imported.
Table NameDisplays the imported table name.
Datetime formatDisplays a number of Datetime Formats and Skypoint's Modern Data Stack Platform is set to automatically detect them.
DelimiterDisplays available separators for the variables in the imported data.
First Row as HeaderCheck the box for the system to automatically collect the data according to the Header Contents.
Advanced SettingsSelect the options to fine tune the Import process with minute details.
  1. Click the Advanced settings for your desired file name.

The Advanced settings pop-up appears.

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ItemDescription
Compression typeMethod that is used for compressing the details from source, Azure Data Lake Storage Gen2.
Row delimiterA separator that identifies the boundaries of the flow of a data stream. In case, a different separator is used in it, the information requires change for more accuracy in data ingestion.
EncodingAs the data comes in data stream, there is a type of encoding used for deciphering it. The default encoding is UTF-8.
Escape characterIt is a particular case of metacharacters that is given an identification of start or end. You can manually select it from the drop-down list.
Quote characterYou can select one of the advanced Quote characters mentioned in the drop-down list.
  1. Click Save on the Advanced settings pop-up to save the advanced settings.
  2. Click Save.

Run, edit, and delete the imported data

Once you save the connector, the Google Cloud Storage connector gets displayed in the list of tables created in the Dataflow page.

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ItemDescription
NameDisplays the name of the imported Dataflow.
TypeDisplays connector type symbol.
StatusIndicates whether the data is imported successfully.
Tables CountDisplays the number of tables.
Created DateDisplays date of creation.
Last refresh typeDisplays the refresh value. You can see the value is Full or Incremental after the last refresh of data.
Updated DateDisplays last modified date.
Last RefreshDisplays the latest refresh date. This date will get updated whenever you refresh the data.
Group byOption to view the items in a specific Group (For example, name, type, status).
  • Select the horizontal ellipsis in the Actions column and do the following:
If you want toThen
Modify the DataflowSelect Edit and modify the Dataflow. Click Save to apply your changes.
Execute the DataflowSelect Run.
Bring the data to its previous stateSelect Rollback.
Delete the DataflowSelect Remove and then click the Delete button. All tables in the data source get deleted.
See the run history of the DataflowSelect Run history.

Next step

After completing the data import, start the Master Data Management (MDM) - Stitch process to develop a unified view of your customers.