Facebook Ads to Redshift Simplified: 2 Easy Methods
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Your organization must be spending many dollars to market and acquire customers through Facebook Ads. Given the importance and cost-share, this medium occupies, moving all important data to a robust warehouse such as Redshift becomes a business requirement for better analysis, market insight, and growth. This post talks about moving your data from Facebook Ads to the Redshift in an efficient and reliable manner.
Prerequisites
- An active Facebook account.
- An active Amazon Redshift account.
Understanding Facebook Ads and Redshift
Facebook is the world’s biggest online social media giant with over 2 billion users around the world, making it one of the leading advertisement channels in the world. Studies have shown that Facebook accounts for over half of the advertising spends in the US. Facebook ads target users based on multiple factors like activity, demographic information, device information, advertising, and marketing partner-supplied information, etc.
Amazon Redshift is a simple, cost-effective and yet very fast and easily scalable cloud data warehouse solution capable of analyzing petabyte-level data. Redshift provides new and deeper insights into the customer response behavior, marketing, and overall business by merging and analyzing the Facebook data as well as data from other sources simultaneously. You can read more on the features of Redshift here.
Data can be moved from Facebook Ads to Redshift in either of two ways:
Method 1: Write custom ETL scripts to load data
The manual method calls for you to write a custom ETL script yourself. So, you will have to write the script to extract the data from Facebook Ads, transform the data (i.e select and remove whatever is not needed) and then load it to Redshift. This method would you to invest a considerable amount of engineering resources
Method 2: Use a fully managed Data Integration Platform like LIKE.TG Data
Using an easy-to-use Data Integration Platform like LIKE.TG helps you move data from Facebook Ads to Redshift within a couple of minutes and for free. There’s no need to write any code as LIKE.TG offers a graphical interface to move data. LIKE.TG is a fully managed solution, which means there is zero monitoring and maintenance needed from your end.
Get Started with LIKE.TG for freeMethods to Load Data from Facebook Ads to Redshift
Majorly there are 2 methods through which you can load your data from Facebook Ads to Redshift:
- Method 1: Moving your data from Facebook Ads to Redshift using Custom Scripts
- Method 2: Moving your data from Facebook Ads to Redshift using LIKE.TG
Method 1: Moving your data from Facebook Ads to Redshift using Custom Scripts
The fundamental idea is simple – fetch the data from Facebook Ads, transform the data so that Redshift can understand it, and finally load the data into Redshift. Following are the steps involved if you chose to move data manually:
- To fetch the data you have to use the Facebook Ads Insight API and write scripts for it. Look into the API documentation to find out all the endpoints available and access it. These Endpoints (impressions, clickthrough rates, CPC, etc.) are broken out by time period. The endpoints will return a JSON output. Once you receive the output then you need to extract only the fields that matter to you.
- To get newly updated data as it appears in Facebook Ads on a regular basis, you also need to set up cron jobs. For this, you need to identify the auto-incrementing key fields that your written script can use to bookmark its progression through the data
- Next, to map Facebook ad’s JSON files, you need to identify all the columns you want to insert and then set up a table in Redshift matching this schema. Next, you would have to write a script to insert this data into Redshift. Datatype compatibility between the two platforms is another area you need to be careful about. For each field in the Insights API’s response, you have to decide on the appropriate data type in the redshift table.
- In the case of a small amount of data, building an insert operation seems natural. However, keep in mind that Redshift is not optimized for row-by-row updates. So for large data, it is always recommended to use an intermediary like Amazon S3 (AWS) and then copy the data to Redshift. In this case, you are required to –
- Create a bucket for your data
- Write an HTTP PUT for your AWS REST API using Postman, Python, or Curl
- Once the bucket is in place, you can then send your data to S3
- Then use a COPY command to load data from S3 to Redshift
- Additionally, you need to put in place proper frequent monitoring to detect any change in the Facebook Ad schema and update the script in case of any change in the source data structure.
LIKE.TG ">Method 2: Moving your data from Facebook Ads to Redshift using LIKE.TG
LIKE.TG Data, a No-code Data Pipeline helps to Load Data from any data source such as Databases, SaaS applications, Cloud Storage, SDKs, and Streaming Services and simplifies the ETL process. It supports 100+ data sources(including 40+ free sources) including Facebook Ads, etc.,for free and is a 3-step process by just selecting the data source, providing valid credentials, and choosing the destination. LIKE.TG loads the data onto the desired Data Warehouse, enriches the data, and transforms it into an analysis-ready form without writing a single line of code.
Its completely automated pipeline offers data to be delivered in real-time without any loss from source to destination. Its fault-tolerant and scalable architecture ensure that the data is handled in a secure, consistent manner with zero data loss and supports different forms of data. The solutions provided are consistent and work with different Business Intelligence (BI) tools as well.
LIKE.TG can move data from Facebook Ads to Redshift seamlessly in 2 simple steps:
Step 1: Configuring the Source
- Navigate to the Asset Palette and click on Pipelines.
- Now, click on the +CREATE button and select Facebook Ads as the source for data migration.
- In the Configure your Facebook Ads page, click on ADD FACEBOOK ADS ACCOUNT.
- Login to your Facebook account and click on Done to authorize LIKE.TG to access your Facebook Ads data.
- In the Configure your Facebook Ads Source page, fill all the required fields
Step 2: Configuring the Destination
- Once you have configured the source, it’s time to manage the destination. navigate to the Asset Palette and click on Destination.
- Click on the +CREATE button and select Amazon Redshift as the destination.
- In the Configure your Amazon Redshift Destination page, specify all the necessary details.
LIKE.TG will now take care of all the heavy-weight lifting to move data from Google Ads to Redshift.
Get Started with LIKE.TG for freeAdvantages of Using LIKE.TG
Listed below are the advantages of using LIKE.TG Data over any other Data Pipeline platform:
- Secure: LIKE.TG has a fault-tolerant architecture that ensures that the data is handled in a secure, consistent manner with zero data loss.
- Schema Management: LIKE.TG takes away the tedious task of schema management & automatically detects the schema of incoming data and maps it to the destination schema.
- Minimal Learning: LIKE.TG , with its simple and interactive UI, is extremely simple for new customers to work on and perform operations.
- LIKE.TG Is Built To Scale: As the number of sources and the volume of your data grows, LIKE.TG scales horizontally, handling millions of records per minute with very little latency.
- Incremental Data Load: LIKE.TG allows the transfer of data that has been modified in real-time. This ensures efficient utilization of bandwidth on both ends.
- Live Support: The LIKE.TG team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.
- Live Monitoring: LIKE.TG allows you to monitor the data flow and check where your data is at a particular point in time.
Limitations of Using the Custom Code Method to Move Data
On the surface, implementing a custom solution to move data from Facebook Ads to Redshift may seem like a more viable solution. However, you must be aware of the limitations of this approach as well.
- Since you are writing it yourself, you have to maintain it too. If Facebook updates its API or the API sends a field with a datatype which your code doesn’t recognize, then you will have to modify your script likewise. Script modification is also needed even if slightly different information is needed by users.
- You also need a data validation system in place to ensure all the data is being updated accurately.
- The process is time-consuming and you might want to put your time to better use if a better less time-consuming process is available.
- Though maintaining in this way is very much possible, this requires plenty of engineering resources which is not suited for today’s agile work environment.
Conclusion
The article introduced you to Facebook Ads and Amazon Redshift. It provided 2 methods that you can use for loading data from Facebook Ads to Redshift. The 1st method includes Manual Integration while the 2nd method uses LIKE.TG Data.
Visit our Website to Explore LIKE.TGWith the complexity involves in Manual Integration, businesses are leaning more towards Automated and Continous Integration. This is not only hassle-free but also easy to operate and does not require any technical proficiency. In such a case, LIKE.TG Data is the right choice for you! It will help simplify the Marketing Analysis. LIKE.TG Data supports platforms like Facebook Ads, etc., for free.
Want to take LIKE.TG for a spin? Sign Up for a 14-day free trial and experience the feature-rich LIKE.TG suite first hand. You can also have a look at our unbeatable pricing that will help you choose the right plan for your business needs!
What are your thoughts on moving data from Facebook Ads to Redshift? Let us know in the comments.
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