Connect SurveyMonkey to Snowflake: 2 Easy Steps

on Data Integration, Data Warehouses, Snowflake, SurveyMonkey, Tutorials • June 24th, 2022 • Write for Hevo

SurveyMonkey to Snowflake - FI | Hevo Data

Today, digitally empowered companies are more data-hungry than ever. The data collected from consumers, market studies, etc., help businesses in finding insights that help them understand the customer demands and grievances better than ever. One of the proven ways to gain deeper insights is through surveys. Businesses can use survey platforms like SurveyMonkey to collect feedback from survey responses and share insights in order to enhance their customers’ experiences, products, and company operations. 

While SurveyMonkey’s analytical features can help with a basic understanding of customer expectations and criticism, connecting it with a scalable data warehouse like Snowflake can enable accessing analysis-ready data in real-time. Connecting SurveyMonkey to Snowflake can empower users to accomplish everything from basic reporting to complicated ad-hoc queries with the help of SurveyMonkey data and a high-performing cloud data warehouse like Snowflake. 

In this article, you will learn about SurveyMonkey and Snowflake, as well as their features. Further, you will go through the basic steps to connect SurveyMonkey to Snowflake.

Table of contents

What is SurveyMonkey?

SurveyMonkey to Snowflake: SurveyMonkey Logo | Hevo Data
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SurveyMonkey is a digital questionnaire platform that specializes in providing quick-access templates for a wide range of purposes like customer reviews, feedback on a course, etc. It assists enterprises in collecting data about individuals through free online surveys and transforming that data into business insights.

Users can also create their own questionnaires that align with their business requirements using SurveyMonkey. It can be used to design quizzes and polls in addition to surveys. SurveyMonkey can even combine with data collecting tools such as web links, e-mail, and social media. Once your audience has completed the survey, SurveyMonkey can assist with data analysis. This is accomplished through its analytics capabilities, which can separate data automatically based on key differentiators and give insights into customer behavior.

Key Features of SurveyMonkey

Some of the main features of SurveyMonkey are listed below:

  • Drag-and-drop builder: SurveyMonkey’s drag-and-drop builder makes the entire process of creating a customer survey a breeze. Building a survey takes only a few minutes since the builder is simple to use and speeds up the process.
  • Answer randomization: This is a valuable function that is found in the settings section. The feature comes in handy for things like flipping answers, which is uncommon in survey software. This helps reduce the primacy effect bias, which occurs when individuals choose responses towards the top of the list since it flips the choices for each respondent.
  • Embed NPS questions: Net Promoter Score is one of the greatest customer satisfaction surveys on the market for determining how loyal your customers are or predicting the likelihood of someone leaving you for a rival. Users can send NPS questions at frequent touchpoints using SurveyMonkey.
  • Skip logic: It is a premium tool that allows you to direct respondents to a different page/section of the survey or to a specific topic on that page based on the response to a question.
  • Multilingual surveys: If you run a business that has an international user base, you’re in a tough spot if your online survey solution doesn’t handle multilingual surveys as not everyone speaks English.

    Hence, offering survey questions to your users in a language they understand becomes a necessary asset in ensuring user satisfaction. SurveyMonkey is available in a variety of languages and can be accessed from any device.

What is Snowflake?

SurveyMonkey to Snowflake: Snowflake Logo | Hevo Data
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Snowflake is a cloud-based data warehouse solution that supports ANSI SQL. It has a unique intuitive design that allows users to easily create tables and begin querying data without the need for administrative or DBA assistance.

Snowflake allows you to run an infinite number of concurrent workloads against the same single copy of data without interfering with other users’ performance. Its off-the-shelf deployability and self-service architecture make it excellent for startups looking for cloud data warehousing solutions. Snowflake is also scalable, meaning users can scale up or down their processing demands according to business needs.

Key Features of Snowflake

Some of the main features of Snowflake are listed below:

  • High-Performance: By leveraging a schema on reading data type called VARIANT, Snowflake’s design enables the storing of both structured and semi-structured data in the same location. Snowflake parses the data as it is loaded, extracting the properties and storing them in a columnar manner.

    This enables Snowflake to quickly access JSON, AVRO, ORC, and Parquet semi-structured data files, giving you a complete picture of your business and consumers and allowing you to get deeper, more illuminating insights. In addition to offering support for semi-structured data, Snowflake has announced support for unstructured data, and it has been in public preview since September 2021. This update allows enterprises to manage and analyze all of their data — structured, semi-structured, and unstructured across clouds.
  • Virtual Compute Warehouse: Snowflake processes all of your queries using “virtual warehouses.” Each virtual warehouse is an MPP compute cluster made up of multiple compute nodes that Snowflake obtains from a cloud provider.

    Depending on your needs and workload, you can create several virtual warehouses of various sizes. Separate virtual computing warehouses, for example, could be used for designing and testing workloads. Each virtual warehouse has its own compute cluster, with no other virtual warehouses sharing computer resources. As a consequence, the performance of one virtual warehouse has no bearing on the performance of others.
  • Zero Cloning: In a standard RDBMS system, when you copy a table from one database to another, the table is copied along with the data, which means the data is replicated twice, thus occupying more storage space.

    Snowflake’s zero-copy feature allows you to clone any database or table almost instantly without having to make a new copy. It accomplishes this by keeping track of changes to the clone in its metadata store while still referring to the same data files in the backend. Zero-copy cloning has the advantage of allowing you to produce many independent clones of the same data without incurring any additional expenditures.
  • Agnostic Cloud Provider: Snowflake is a cloud-independent platform. It’s a managed data warehouse solution that works across all three cloud providers: AWS, Azure, and Google Cloud Platform, with the same end-user experience. Customers can seamlessly integrate Snowflake into their existing cloud infrastructure and deploy it in required areas.
  • Scalability: The computation and storage resources are separated in Snowflake’s multi-cluster shared data architecture. This approach allows customers to scale up resources when big volumes of data need to be loaded quickly and scale back down when the operation is complete, all without disrupting service.

    Customers can begin with a modest virtual warehouse and then scale up or down as needed. Snowflake has included auto-scaling and auto-suspend features to ensure minimal administration. Snowflake’s auto-scaling feature allows it to automatically start and terminate clusters during resource-intensive processes. Auto-suspend, on the other hand, brings the virtual warehouse to a halt after a certain time of inactivity. 

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Why Connect SurveyMonkey to Snowflake?

SurveyMonkey allows users to add questionnaires and forms on websites, E-Mails, and other places that help companies to gather more information related to their customers, feedback, etc. These forms allow companies to collect valuable user information from heterogeneous sources and create an E-Mail list.

Connecting SurveyMonkey to Snowflake allow companies to load their valuable data related to product feedback, customer queries, user information, etc. Once all your data from SurveyMonkey gets loaded to Snowflake, users can merge this data with other existing data and analyze it for better use. Also, users can load this data further to other SaaS applications for marketing purposes.

Steps to Connect SurveyMonkey to Snowflake

Now that you have understood about Snowflake and SurveyMonkey. In this section, you will go through the steps to connect SurveyMonkey to Snowflake. Here, we shall first export our data from SurveyMonkey to our system and then transfer the files from our system to Snowflake through its web interface. The following steps to connect SurveyMonkey to Snowflake are listed below:

Step 1: Exporting Data from SurveyMonkey

To export your survey results, follow these steps:

  • Navigate to the part of your survey and click Analyze Results.
SurveyMonkey to Snowflake: Opening Survey Results | Hevo Data
Image Source: Self
  • At the top of the page, select Save As.
SurveyMonkey to Snowflake: Saving File | Hevo Data
Image Source: Self
  • Select Export File from the menu.
  • Choose between two export options: All Summary Data and All Responses Data.
SurveyMonkey to Snowflake: Exporting SurveyMonkey File | Hevo Data
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  • Select XLS as your export format, then click Export to download the file to your computer.

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Step 2: Importing data via the Snowflake Web interface

The following steps to connect SurveyMonkey to Snowflake are applicable if you have followed the above steps and exported data from SurveyMonkey to your local system and are trying to access them via the Web Interface of Snowflake.

Starting Load Data

SurveyMonkey to Snowflake: Loading Data | Hevo Data
Image Source: Self
  • Click on Data > Databases on the Snowflake Web homepage.
  • To see the items contained in a database, click on the link for that database.
  • Click on the table by either choosing the row and then loading or by clicking the load button after selecting the table name.
  • The wizard for loading data appears. The wizard will populate the table you specified with data.

Choosing Preferred Warehouse

  • Because Snowflake stores data in warehouses, select the one you want from the list. 
  • After that, click the Next button.

Loading Files

  • Click Load files from your computer and then click the Select Files button.
  • Click the Open button after selecting one or more local data files.
  • Then hit the Next button.

Selecting File Format

For Existing File Format:

  • Select an existing file format, then click Next.

For A New File Format:

  • Next to the dropdown list, click the plus (+) icon.
  • To match the format of your data files, fill in the fields on the screen. 
  • Click the Finish button.
  • From the dropdown list, choose your new named file format.
  • Click the Next button.

Configuring Load Options

  • Specify how SurveyMonkey to Snowflake connection should respond if the data files include errors.
  • Select the Load. Snowflake uses the warehouse you picked to import the data into your chosen table.
  • Then press the OK button. The data loading wizard closes.

That’s it! You have connected SurveyMonkey to Snowflake.

Advantages to Connect SurveyMonkey to Snowflake

Some of the main advantages of connecting SurveyMonkey to Snowflake are listed below:

  • Connecting SurveyMonkey to Snowflake allow companies to replicate their data from SurveyMonkey to Snowflake Data Warehouse.
  • Connecting SurveyMonkey to Snowflake enables marketers to gather audiences and outreach them via importing data from Snowflake to other marketing platforms.
  • Connecting SurveyMonkey to Snowflake enhances data enrichment capabilities allowing companies to analyze and understand their subscriber’s demands.

Conclusion

In this article, you learned about an easy and intuitive way to connect SurveyMonkey to Snowflake. Connecting SurveyMonkey to Snowflake can allow users to profit from the cloud-agnostic and data security features. In addition, the scalability and zero cloning functionalities, when paired with the advanced SQL features of Snowflake, can even help with the analytical processing of the data collected from surveys of SurveyMonkey.

However, connecting SurveyMonkey to Snowflake is a manual and thus time-consuming process, it will be beneficial to switch to using ETL pipeline tools like Hevo Data for efficient and real-time data migration.

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Share your experience of learning about Connecting SurveyMonkey to Snowflake in the comments section below!

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