As businesses strive to create more effective marketing campaigns, many are turning to social media platforms like Facebook to reach their target audiences. While Facebook provides a wealth of data about its users, analyzing this data can be difficult and time-consuming. Keeping tabs on your Facebook page becomes essential to see whether your posts perform well or if followers engage with your content.
By integrating Facebook Page Insights with BigQuery, companies can access and analyze all the data that Page Insights collects in a single place. This allows businesses to quickly and easily identify trends in their Page’s data and decide how to improve their marketing efforts.
In this blog, you’ll learn about the features of Facebook Page Insights and BigQuery. You’ll also learn how to integrate Facebook Page Insights to BigQuery.
Why Integrate Facebook Page Insights to BigQuery?
The integration of Facebook Page Insights to Bigquery will guarantee improved business intelligence for Facebook advertising campaigns. Faster access to accurate data will enable you to make quick business decisions. Improve your data’s control for trend visualization in real-time. As a result of Facebook Page Insights to BigQuery Integration, you will save money on Facebook Page Insights and increase ROI.
Methods to Integrate Facebook Page Insights to BigQuery
The following are the two methods for connecting Facebook Page Insights to BigQuery.
Method 1: Using an Automated Data Pipeline Platform to Set Up Facebook Page Insights to BigQuery
Hevo provides an Automated No-code Data Pipeline that helps you move your Facebook Page Insights to BigQuery. Hevo is fully-managed and completely automates the process of not only loading data from your 150+ data sources (including 40+ free sources)but also enriching the data and transforming it into an analysis-ready form without having to write a single line of code. Its fault-tolerant architecture ensures that the data is handled securely and consistently with zero data loss.
Using Hevo, you can connect Facebook Page Insights to BigQuery in the following 2 steps:
- Step 1: Configure Facebook Page Insights as the Source in your Pipeline by following the steps below:
- Step 1.1: In the Asset Palette, select PIPELINES.
- Step 1.2: In the Pipelines List View, click + CREATE.
- Step 1.3: Select Facebook Page Insights on the Select Source Type page.
- Step 1.4: Click + ADD FACEBOOK PAGES ACCOUNT on the Configure your Facebook Pages Account page.
- Step 1.5: To continue as Company Name>, log into your Facebook Pages account and click Continue.
- Step 1.6: Click Next after choosing one or more pages whose data you want to copy.
- Step 1.7: Enable all of the permissions and click Done to approve Hevo.
- Step 1.8: In the Confirmation dialogue, click OK.
- Step 1.9: Enter the following information on the Configure your Facebook Pages Source page:
- Pipeline Name: A name for the Pipeline that is unique.
- Pages: Choose one or more pages whose information you want to copy
- Historical Sync Duration: The amount of time that the historical data must be ingested.
- Step 1.91: TEST & CONTINUE is the button to click.
- Step 1.92: Set up the Destination and configure the data ingestion.
- Step 2: To set up Google BigQuery as a destination in Hevo, follow these steps:
- Step 2.1: In the Asset Palette, select DESTINATIONS.
- Step 2.2: In the Destinations List View, click + CREATE.
- Step 2.3: Select Google BigQuery from the Add Destination page.
- Step 2.4: Choose the BigQuery connection authentication method on the Configure your Google BigQuery Account page.
- Step 2.5: Choose one of these:
- Using a Service Account to connect:
- Service Account Key file, please attach.
- Note that Hevo only accepts key files in JSON format.
- Go to CONFIGURE GOOGLE BIGQUERY ACCOUNT and click it.
- Using a user account to connect:
- To add a Google BigQuery account, click +.
- Become a user with BigQuery Admin and Storage Admin permissions by logging in.
- To grant Hevo access to your data, click Allow.
- Step 2.6: Set the following parameters on the Configure your Google BigQuery page:
- Destination Name: A unique name for your Destination.
- Project ID: The BigQuery Project ID that you were able to retrieve in Step 2 above and for which you had permitted the previous steps.
- Dataset ID: Name of the dataset that you want to sync your data to, as retrieved in Step 3 above.
- GCS Bucket: To upload files to BigQuery, they must first be staged in the cloud storage bucket that was retrieved in Step 4 above.
- Enable Streaming Inserts: Enable this option to load data via a job according to a defined Pipeline schedule rather than streaming it to your BigQuery Destination as it comes in from the Source. To learn more, go to Near Real-time Data Loading Using Streaming. The setting cannot be changed later.
- Sanitize Table/Column Names: Activate this option to replace the spaces and non-alphanumeric characters in between the table and column names with underscores ( ). Name Sanitization is written.
- Step 2.5: Click Test Connection to test connectivity with the Amazon Redshift warehouse.
- Step 2.6: Once the test is successful, click SAVE DESTINATION.
Method 2: Using Custom Code to Move Data from Facebook Page Insights to BigQuery
This method of Facebook Page Insights to BigQuery Integration requires technical knowledge. Page Insights feature of Facebook includes information about the number of people who have seen a Page’s posts, the number of people who have liked a Page’s posts, and the number of people who have shared a Page’s posts. BigQuery is a data analysis platform from Google that allows businesses to analyze large datasets.
By integrating Facebook Page Insights to BigQuery, teams can quickly combine their marketing, CRM, and social media data. Businesses will also be able to calculate the ROI for each campaign with Facebook Page Insights to BigQuery integration. Combine customer relationship management and sales data to calculate the ROI of your campaigns.
Steps to integrate Facebook Page Insights to BigQuery:
Export Facebook Page Insights
- Click Pages in the left menu in your News Feed.
- Go to your Page.
- Click Insights in the left menu.
- Choose from Page, Post, and Video data.
- Click Export Data in the top right.
- Go to Layout and select Make New Custom Layout for custom reports.
- Enter a sheet name and then click Add.
- Select the information you’d like to add to your sheet.
- When you’ve finished selecting your custom data, click Apply.
- Select a data type, file format, and date range.
- Click Export Data again.
Using manual scripts and custom code to move data into the warehouse is cumbersome. Changing API endpoints and limits, ad-hoc data preparation, and inconsistent schema makes maintaining such a system a nightmare. Hevo’s reliable no-code data pipeline platform enables you to set up zero-maintenance data pipelines that just work.
- Wide Range of Connectors: Instantly connect and read data from 150+ sources including SaaS apps and databases, and precisely control pipeline schedules down to the minute.
- In-built Transformations: Format your data on the fly with Hevo’s preload transformations using either the drag-and-drop interface or our nifty python interface. Generate analysis-ready data in your warehouse using Hevo’s Postload Transformation.
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Importing Data to Google BigQuery
There are 2 ways to load data from Facebook Page Insights to BigQuery: batch loading and streaming. Batch loading allows you to load the source data into a table in a single batch operation. With streaming, you can frequently send smaller batches of data in real-time, so the data is instantly available for querying.
You will create a load job to load the CSV files in Google BigQuery. The source data can have formats such as Avro, JSON, ORC, Parquet, etc.
Before you can start the load job, you’ll have to give the following IAM permissions:
You’ll also have to include these permissions in the predefined IAM roles:
roles/bigquery.admin (includes the bigquery.jobs.create permission)
bigquery.user (includes the bigquery.jobs.create permission)
bigquery.jobUser (includes the bigquery.jobs.create permission)
Follow these steps to load CSV data:
- Go to the BigQuery page in Google Cloud Console.
- Select a dataset from the Resource section.
- Click Create Table in the Dataset Info section.
- On the Create Table page, select Upload in the Source section.
- Browse the file from your local files.
- Click Open.
- Select your file’s format in the File Format section.
- On the Create Table page, Go to the Destination section.
- Enter an appropriate dataset name.
- Next, enter the name of the table you’re creating in BigQuery.
- Enter schema definition in the Schema section.
- Click Create Table.
By integrating Facebook Page Insights to BigQuery, businesses can gain quick and easy access to the data they need to make informed decisions about their marketing efforts. However, manually downloading and uploading reports to BigQuery through load data jobs is time-consuming. It also doesn’t allow users to see reports and insights in real-time. Alternatively, you can use a low/no-code platform like Hevo to access Facebook Page Insights in real-time in Google BigQuery.
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