How to load data from Apple Search Ads to Databricks Lakehouse

Learn how to use Airbyte to synchronize your Apple Search Ads data into Databricks Lakehouse within minutes.

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Set up a Apple Search Ads connector in Airbyte

Connect to Apple Search Ads or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up Databricks Lakehouse for your extracted Apple Search Ads data

Select Databricks Lakehouse where you want to import data from your Apple Search Ads source to. You can also choose other cloud data warehouses, databases, data lakes, vector databases, or any other supported Airbyte destinations.

Configure the Apple Search Ads to Databricks Lakehouse in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.

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TL;DR

set up Apple Search Ads as a source connector (using Auth, or usually an API key)
set up Databricks Lakehouse as a destination connector
define which data you want to transfer and how frequently

You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

This tutorial’s purpose is to show you how.

What is Apple Search Ads

Apple Search Ads is a platform that allows businesses to promote their apps in the App Store by displaying ads to users who are searching for specific keywords. Advertisers can target their ads based on factors such as location, device type, and demographics. The platform uses a pay-per-tap model, meaning advertisers only pay when a user taps on their ad. Apple Search Ads also provides detailed analytics and insights to help advertisers optimize their campaigns and improve their return on investment. Overall, Apple Search Ads is a powerful tool for app developers and businesses looking to increase their visibility and downloads in the App Store.

What is Databricks Lakehouse

Databricks is an American enterprise software company founded by the creators of Apache Spark. Databricks combines data warehouses and data lakes into a lakehouse architecture.

Integrate Apple Search Ads with Databricks Lakehouse in minutes

Try for free now

Prerequisites

A Apple Search Ads account to transfer your customer data automatically from.
A Databricks Lakehouse account.
An active Airbyte Cloud account, or you can also choose to use Airbyte Open Source locally. You can follow the instructions to set up Airbyte on your system using docker-compose.

Airbyte is an open-source data integration platform that consolidates and streamlines the process of extracting and loading data from multiple data sources to data warehouses. It offers pre-built connectors, including Apple Search Ads and Databricks Lakehouse, for seamless data migration.

When using Airbyte to move data from Apple Search Ads to Databricks Lakehouse, it extracts data from Apple Search Ads using the source connector, converts it into a format Databricks Lakehouse can ingest using the provided schema, and then loads it into Databricks Lakehouse via the destination connector. This allows businesses to leverage their Apple Search Ads data for advanced analytics and insights within Databricks Lakehouse, simplifying the ETL process and saving significant time and resources.

Step 1: Set up Apple Search Ads as a source connector

1. Go to the Airbyte website and sign up for an account.
2. Once you have signed up, click on the "Sources" tab on the left-hand side of the screen.
3. Scroll down until you find the "Apple Search Ads" source connector and click on it.
4. Click on the "Create a new connection" button.
5. Enter your Apple Search Ads credentials, including your Apple ID and password.
6. Choose the account you want to connect to and select the campaigns you want to sync.
7. Click on the "Test" button to ensure that the connection is working properly.
8. If the test is successful, click on the "Save & Sync" button to start syncing your data.
9. You can choose to schedule regular syncs or manually sync your data whenever you want.
10. Once your data is synced, you can use Airbyte's data integration and transformation tools to analyze and visualize your Apple Search Ads data.

Step 2: Set up Databricks Lakehouse as a destination connector

1. First, navigate to the Airbyte website and log in to your account.
2. Once you are logged in, click on the "Destinations" tab on the left-hand side of the screen.
3. Scroll down until you find the "Databricks Lakehouse" connector and click on it.
4. You will be prompted to enter your Databricks Lakehouse credentials, including your account name, personal access token, and workspace ID.
5. Once you have entered your credentials, click on the "Test" button to ensure that the connection is successful.
6. If the test is successful, click on the "Save" button to save your Databricks Lakehouse destination connector settings.
7. You can now use the Databricks Lakehouse connector to transfer data from your source connectors to your Databricks Lakehouse destination.
8. To set up a data transfer, navigate to the "Sources" tab and select the source connector that you want to use.
9. Follow the prompts to enter your source connector credentials and configure your data transfer settings.
10. Once you have configured your source connector, select the Databricks Lakehouse connector as your destination and follow the prompts to configure your data transfer settings.
11. Click on the "Run" button to initiate the data transfer.

Step 3: Set up a connection to sync your Apple Search Ads data to Databricks Lakehouse

Once you've successfully connected Apple Search Ads as a data source and Databricks Lakehouse as a destination in Airbyte, you can set up a data pipeline between them with the following steps:

Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
Choose your source: Select Apple Search Ads from the dropdown list of your configured sources.
Select your destination: Choose Databricks Lakehouse from the dropdown list of your configured destinations.
Configure your sync: Define the frequency of your data syncs based on your business needs. Airbyte allows both manual and automatic scheduling for your data refreshes.
Select the data to sync: Choose the specific Apple Search Ads objects you want to import data from towards Databricks Lakehouse. You can sync all data or select specific tables and fields.
Select the sync mode for your streams: Choose between full refreshes or incremental syncs (with deduplication if you want), and this for all streams or at the stream level. Incremental is only available for streams that have a primary cursor.
Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from Apple Search Ads to Databricks Lakehouse according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your Databricks Lakehouse data warehouse is always up-to-date with your Apple Search Ads data.

Use Cases to transfer your Apple Search Ads data to Databricks Lakehouse

Integrating data from Apple Search Ads to Databricks Lakehouse provides several benefits. Here are a few use cases:

Advanced Analytics: Databricks Lakehouse’s powerful data processing capabilities enable you to perform complex queries and data analysis on your Apple Search Ads data, extracting insights that wouldn't be possible within Apple Search Ads alone.
Data Consolidation: If you're using multiple other sources along with Apple Search Ads, syncing to Databricks Lakehouse allows you to centralize your data for a holistic view of your operations, and to set up a change data capture process so you never have any discrepancies in your data again.
Historical Data Analysis: Apple Search Ads has limits on historical data. Syncing data to Databricks Lakehouse allows for long-term data retention and analysis of historical trends over time.
Data Security and Compliance: Databricks Lakehouse provides robust data security features. Syncing Apple Search Ads data to Databricks Lakehouse ensures your data is secured and allows for advanced data governance and compliance management.
Scalability: Databricks Lakehouse can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding Apple Search Ads data.
Data Science and Machine Learning: By having Apple Search Ads data in Databricks Lakehouse, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
Reporting and Visualization: While Apple Search Ads provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to Databricks Lakehouse, providing more advanced business intelligence options. If you have a Apple Search Ads table that needs to be converted to a Databricks Lakehouse table, Airbyte can do that automatically.

Wrapping Up

To summarize, this tutorial has shown you how to:

Configure a Apple Search Ads account as an Airbyte data source connector.
Configure Databricks Lakehouse as a data destination connector.
Create an Airbyte data pipeline that will automatically be moving data directly from Apple Search Ads to Databricks Lakehouse after you set a schedule

With Airbyte, creating data pipelines take minutes, and the data integration possibilities are endless. Airbyte supports the largest catalog of API tools, databases, and files, among other sources. Airbyte's connectors are open-source, so you can add any custom objects to the connector, or even build a new connector from scratch without any local dev environment or any data engineer within 10 minutes with the no-code connector builder.

We look forward to seeing you make use of it! We invite you to join the conversation on our community Slack Channel, or sign up for our newsletter. You should also check out other Airbyte tutorials, and Airbyte’s content hub!

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Sync with Airbyte

Step 1: Set up Apple Search Ads as a source connector

Step 2: Set up Databricks Lakehouse as a destination connector

Step 3: Set up a connection to sync your Apple Search Ads data to Databricks Lakehouse

Once you've successfully connected Apple Search Ads as a data source and Databricks Lakehouse as a destination in Airbyte, you can set up a data pipeline between them with the following steps:

Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
Choose your source: Select Apple Search Ads from the dropdown list of your configured sources.
Select your destination: Choose Databricks Lakehouse from the dropdown list of your configured destinations.
Configure your sync: Define the frequency of your data syncs based on your business needs. Airbyte allows both manual and automatic scheduling for your data refreshes.
Select the data to sync: Choose the specific Apple Search Ads objects you want to import data from towards Databricks Lakehouse. You can sync all data or select specific tables and fields.
Select the sync mode for your streams: Choose between full refreshes or incremental syncs (with deduplication if you want), and this for all streams or at the stream level. Incremental is only available for streams that have a primary cursor.
Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from Apple Search Ads to Databricks Lakehouse according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your Databricks Lakehouse data warehouse is always up-to-date with your Apple Search Ads data.

How to Sync Apple Search Ads to Databricks Lakehouse Manually

Step 1:

Step 2:

Step 3:

Step 4:

Step 5:

Step 6:

Step 7:

Step 8:

FAQs

What is ETL?

ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.

What is Apple Search Ads?

What data can you extract from Apple Search Ads?

Apple Search Ads API provides access to a wide range of data related to app advertising campaigns. The following are the categories of data that can be accessed through the API:
1. Campaign data: This includes information about the campaigns such as campaign name, status, budget, start and end dates, and target audience.
2. Ad group data: This includes information about the ad groups such as ad group name, status, bid amount, and target keywords.
3. Keyword data: This includes information about the keywords such as keyword text, match type, status, and performance metrics.
4. Creative data: This includes information about the ad creatives such as ad type, ad format, ad group, and performance metrics.
5. Performance data: This includes information about the performance of the campaigns, ad groups, keywords, and creatives such as impressions, clicks, conversions, and cost.
6. Attribution data: This includes information about the attribution of the app installs to the advertising campaigns such as source, medium, and campaign name.
7. Audience data: This includes information about the target audience such as demographics, interests, and behaviors.

How do I transfer data from Apple Search Ads?

This can be done by building a data pipeline manually, usually a Python script (you can leverage a tool as Apache Airflow for this). This process can take more than a full week of development. Or it can be done in minutes on Airbyte in three easy steps:
1. Set up Apple Search Ads to Databricks Lakehouse as a source connector (using Auth, or usually an API key)
2. Choose a destination (more than 50 available destination databases, data warehouses or lakes) to sync data too and set it up as a destination connector
3. Define which data you want to transfer from Apple Search Ads to Databricks Lakehouse and how frequently
You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

What is ELT?

ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.

Difference between ETL and ELT?

ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.

Back to all tutorials

Warehouses and Lakes

Marketing Analytics

How to load data from Apple Search Ads to Databricks Lakehouse

Learn how to use Airbyte to synchronize your Apple Search Ads data into Databricks Lakehouse within minutes.

Try Airbyte Cloud free

Deploy Airbyte Open Source

TL;DR

What is Apple Search Ads

What is Databricks Lakehouse

Prerequisites

Step 1: Setup Apple Search Ads

Step 2: Setup Databricks Lakehouse

Step 3: Setup a connection Use Cases Wrapping Up

Example H2

Example H3

Sync data between Apple Search Ads and Databricks Lakehouse

Get your data syncing in minutes

Try Airbyte free

TL;DR

set up Apple Search Ads as a source connector (using Auth, or usually an API key)
set up Databricks Lakehouse as a destination connector
define which data you want to transfer and how frequently

You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

This tutorial’s purpose is to show you how.

What is Apple Search Ads

What is Databricks Lakehouse

Databricks is an American enterprise software company founded by the creators of Apache Spark. Databricks combines data warehouses and data lakes into a lakehouse architecture.

Integrate Apple Search Ads with Databricks Lakehouse in minutes

Try for free now

Prerequisites

A Apple Search Ads account to transfer your customer data automatically from.
A Databricks Lakehouse account.
An active Airbyte Cloud account, or you can also choose to use Airbyte Open Source locally. You can follow the instructions to set up Airbyte on your system using docker-compose.

Step 1: Set up Apple Search Ads as a source connector

Step 2: Set up Databricks Lakehouse as a destination connector

Step 3: Set up a connection to sync your Apple Search Ads data to Databricks Lakehouse

Once you've successfully connected Apple Search Ads as a data source and Databricks Lakehouse as a destination in Airbyte, you can set up a data pipeline between them with the following steps:

Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
Choose your source: Select Apple Search Ads from the dropdown list of your configured sources.
Select your destination: Choose Databricks Lakehouse from the dropdown list of your configured destinations.
Configure your sync: Define the frequency of your data syncs based on your business needs. Airbyte allows both manual and automatic scheduling for your data refreshes.
Select the data to sync: Choose the specific Apple Search Ads objects you want to import data from towards Databricks Lakehouse. You can sync all data or select specific tables and fields.
Select the sync mode for your streams: Choose between full refreshes or incremental syncs (with deduplication if you want), and this for all streams or at the stream level. Incremental is only available for streams that have a primary cursor.
Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from Apple Search Ads to Databricks Lakehouse according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your Databricks Lakehouse data warehouse is always up-to-date with your Apple Search Ads data.

Use Cases to transfer your Apple Search Ads data to Databricks Lakehouse

Integrating data from Apple Search Ads to Databricks Lakehouse provides several benefits. Here are a few use cases:

Advanced Analytics: Databricks Lakehouse’s powerful data processing capabilities enable you to perform complex queries and data analysis on your Apple Search Ads data, extracting insights that wouldn't be possible within Apple Search Ads alone.
Data Consolidation: If you're using multiple other sources along with Apple Search Ads, syncing to Databricks Lakehouse allows you to centralize your data for a holistic view of your operations, and to set up a change data capture process so you never have any discrepancies in your data again.
Historical Data Analysis: Apple Search Ads has limits on historical data. Syncing data to Databricks Lakehouse allows for long-term data retention and analysis of historical trends over time.
Data Security and Compliance: Databricks Lakehouse provides robust data security features. Syncing Apple Search Ads data to Databricks Lakehouse ensures your data is secured and allows for advanced data governance and compliance management.
Scalability: Databricks Lakehouse can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding Apple Search Ads data.
Data Science and Machine Learning: By having Apple Search Ads data in Databricks Lakehouse, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
Reporting and Visualization: While Apple Search Ads provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to Databricks Lakehouse, providing more advanced business intelligence options. If you have a Apple Search Ads table that needs to be converted to a Databricks Lakehouse table, Airbyte can do that automatically.