Adroll to Snowflake: 2 Easy Ways to Replicate Data

So, you’re an Adroll user, right? It’s nice to talk to someone who prioritizes retargeting their customers in a unified platform. Your focus on growing revenue and acquiring customers optimally is commendable. 

At times, there would be a need to move your marketing data from Adroll to a data warehouse. That’s where you come in. You take the responsibility of replicating data from Adroll to a centralized repository. By doing this, the analysts and key stakeholders can take super-fast business-critical decisions.

Give a high-five! We’ve prepared a simple and straightforward guide without beating around the bush. Leap forward and read the 2 simple methods for performing the data replication from Adroll to Snowflake.

How to Replicate Data From Adroll to Snowflake?

To replicate data from Adroll to Snowflake, you can do either of the following:

• Either use CSV files or 
• A no-code automated solution. 

We’ll cover replication via CSV files next.

Replicate Data from Adroll to Snowflake Using CSV Files

Follow along to replicate data from Adroll to Snowflake in CSV format:

Step 1: Export CSV Files from Adroll 

• Go to the Campaign Reports tab in Adroll.
• Open the Adroll report from which you want to export data.
• Click on the “Export” button in the top-right corner. Then, choose the “CSV” format.

Step 2: Launch the Snowflake Load Data Wizard

• From the Snowflake dashboard, click on Databases.
• Select a particular database by clicking on its link.
• Click the Tables tab.
• You should see a list of table names. Click a table name to reveal the table details page.
• Next, click the Load Table button.

This will launch the Load Data Wizard. The wizard provides a convenient way of loading data into a Snowflake table from flat files (e.g. CSV, TSV, etc.) using PUT and COPY commands behind the scenes.

Step 3: Load the CSV Files

• Select a warehouse from the dropdown list. Snowflake will use this warehouse to load data into the table.
• Click Next.
• Select the Load files from your computer option.
• Click the Select Files button.
• Select the CSV files you exported from AdRoll.
• After selecting the files, click on the Open button.
• Finally, click on the Next button.

This will launch a dropdown list that will allow you to describe the format of your files.

Step 4: Create a File Format

• Click the plus (+) symbol next to the dropdown list.
• Fill in the fields to match the format of your CSV files.
• After filling the fields, click on the Finish button.
• Select your named file format from the dropdown list.
• Click the Next button.

Step 5: Select the Load Options

In this section, you will specify how Snowflake should behave if errors in the data files are encountered. The supported values are CONTINUE, SKIP_FILE, and ABORT_STATEMENT.

Step 6: Load the Data

• Click on the Load button to load your CSV files into your Snowflake table.
• Click the OK button to close the data wizard.

The above 5-step guide replicates data from Adroll to Snowflake effectively. It is optimal for the following scenarios:

• Less Amount of Data: This method is appropriate for you when the number of reports is less. Even the number of rows in each report is not huge.

• One-Time Data Replication: This method suits your requirements if your business teams need the data only once in a while.
• Limited Data Transformation Options: Manually transforming data in CSV files is difficult & time-consuming. Hence, it is ideal if the data in your spreadsheets is clean, standardized, and present in an analysis-ready form. 
• Dedicated Personnel: If your organization has dedicated people who have to perform the manual downloading and uploading of CSV files, then accomplishing this task is not much of a headache.

However, when the frequency of replicating data from Adroll increases, this process becomes highly monotonous. It adds to your misery when you have to transform the raw data every single time. With the increase in data sources, you would have to spend a significant portion of your engineering bandwidth creating new data connectors. Just imagine — building custom connectors for each source, transforming & processing the data, tracking the data flow individually, and fixing issues. Doesn’t it sound exhausting?

How about you focus on more productive tasks than repeatedly writing custom ETL scripts, downloading, cleaning, and uploading CSV files? This sounds good, right?

In that case, you can… 

Replicate Data from Adroll to Snowflake Using an Automated ETL Tool

An automated tool is an efficient and economical choice that takes away a massive chunk of repetitive work. It has the following benefits:

• It allows you to focus on core engineering objectives. Your business teams can jump on to reporting without any delays or data dependency on you.
• Your support team can effortlessly filter, aggregate, and segment data from Adroll.
• Without technical knowledge, your analysts can seamlessly standardize timezones, convert currencies, or simply aggregate campaign data for faster analysis. 
• An automated solution provides you with a list of native in-built connectors. No need to build custom ETL connectors for every source you require data from.

Why not explore an automated data pipeline solution? For instance, here’s how Hevo, a cloud-based ETL solution makes the data replication from Adroll to Snowflake ridiculously easy: 

Step 1: Configure Adroll as your Source

• Fill in the required attributes required for configuring Adroll as your source.

Step 2: Configure Snowflake as your Destination

Now, you need to configure Snowflake as the destination.

All Done to Setup Your ETL Pipeline

After implementing the 2 simple steps, Hevo will take care of building the pipeline for replicating data from Adroll to Snowflake based on the inputs given by you while configuring the source and the destination.

The pipeline will automatically replicate new and updated data from Adroll to Snowflake every 1 hr (by default). However, you can also adjust the data replication frequency as per your requirements.

Data Pipeline Frequency

Default Pipeline Frequency	Minimum Pipeline Frequency	Maximum Pipeline Frequency	Custom Frequency Range (Hrs)
1 Hr	1 Hr	48 Hrs	1-48

For in-depth knowledge of how a pipeline is built & managed in Hevo, you can also visit the official documentation for Adroll as a source and Snowflake as a destination.

You don’t need to worry about security and data loss. Hevo’s fault-tolerant architecture will stand as a solution to numerous problems. It will enrich your data and transform it into an analysis-ready form without having to write a single line of code.

Here’s what makes Hevo stand out:

• Fully Managed: You don’t need to dedicate time to building your pipelines. With Hevo’s dashboard, you can monitor all the processes in your pipeline, thus giving you complete control over it.
• Data Transformation: Hevo provides a simple interface to cleanse, modify, and transform your data through drag-and-drop features and Python scripts. It can accommodate multiple use cases with its pre-load and post-load transformation capabilities.
• Faster Insight Generation: Hevo offers near real-time data replication, giving you access to real-time insight generation and faster decision-making. 
• Schema Management: With Hevo’s auto schema mapping feature, all your mappings will be automatically detected and managed to the destination schema.
• Scalable Infrastructure: With the increased number of sources and volume of data, Hevo can automatically scale horizontally, handling millions of records per minute with minimal latency.
• Transparent pricing: You can select your pricing plan based on your requirements. Different plans are clearly put together on its website, along with all the features it supports. You can adjust your credit limits and spend notifications for any increased data flow.
• Live Support: The support team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.

You can take our 14-day free trial to experience a better way to manage data pipelines.

Get started for Free with Hevo!

What Can You Achieve by Migrating Your Data from Adroll to Snowflake?

Here’s a little something for the data analyst on your team. We’ve mentioned a few core insights you could get by replicating data from Adroll to Snowflake. Does your use case make the list?

• How are Paid Sessions and Goal Conversion Rate varying with Marketing Spend and Cash in-flow?
• How to identify your most valuable customer segments?
• What is the Marketing Behavioural profile of the Product’s Top Users?

Summing It Up 

Exporting & uploading CSV files is the go-to solution for you when your data & financial analysts require fresh data from Adroll only once in a while. But with an increase in frequency, redundancy will also increase. To channel your time into productive tasks, you can opt-in for an automated solution that will help accommodate regular data replication needs. This would be genuinely helpful to marketing teams as they would need regular updates about advertising expenses, support costs of campaigns, site activity, etc.

Even better, your marketing teams would now get immediate access to data from multiple channels and thus deep-dive to explore better market opportunities.

So, take a step forward. And Hevo will help you build an automated no-code data pipeline in a hassle-free manner. Its 150+ plug-and-play native integrations will help you replicate data smoothly from multiple tools to a destination of your choice. Its intuitive UI will help you smoothly navigate through its interface. And with its pre-load transformation capabilities, you don’t even need to worry about manually finding errors and cleaning & standardizing them.

With a no-code data pipeline solution at your service, companies will spend less time calling APIs, referencing data, building pipelines, and more time gaining insights from their data.

Skeptical? Why not try Hevo for free and take the decision all by yourself? Using Hevo’s 14-day free trial feature, you can build a data pipeline from Adroll to Snowflake and try out the experience.

Here’s a short video that will guide you through the process of building a data pipeline with Hevo.

We’ll see you again the next time you want to replicate data from yet another connector to your destination. That is… if you haven’t switched to a no-code automated ETL tool already.

We hope you have found the appropriate answer to the query you were searching for. Happy to help!