Forms are an important part of any organization. Forms help in collecting information and gaining insights. There are many tools that are available in the market that help in creating forms for information gathering and Typeform is one of them. Typeform allows for the creation of structured forms that help in mining information. It provides an easy-to-use platform that is web-based.

BigQuery is a leading data warehouse solution from the house of Google. It is a highly reliable, scalable, and stable solution for storing and processing large amounts of data. By sending data from Typeform to BigQuery you can access the form’s data efficiently.

This article provides a comprehensive overview of Bigquery, and Typeform along with a step-by-step guide to sending data from Typeform to Bigquery.

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Key Features of Typeform

  • Many design templates with drag and drop functionality.
  • Unrestricted forms and surveys.
  • Hidden fields
  • 128-bit SSL encryption.
  • Allows data export
  • Offers free API
  • Integration with other applications.
  • Can be used on mobile or desktop.

Use Cases for Typeform

  • Get visitors to your website to sign up for a program or newsletter.
  • Collecting billing information for an online store.
  • Creating trivia quizzes on your site to engage and inform visitors to the site.
  • Collecting marketing information through surveys.
  • Creating application forms to automate the recruitment process.

What is Google BigQuery?

Typeform to bigquery: bigquery logo | Hevo data
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BigQuery is a robust data warehouse that is exceptionally fast and reliable in handling heavy loads. It was launched by Google and hence has good connectivity with the other google platform tools. It employs a serverless model, which makes it cost-effective and allows pricing based on users’ usage. It also has an integrated query engine that helps in performing analytics and since a serverless architecture is employed it enables it to process terabytes of data in seconds.

A recent study shows that BigQuery is cheaper by about 25%-35% when compared to its rivals for the same amount of workloads and the total cost of ownership. The serverless approach enables it to manage the infrastructure with flexibility. It helps in gaining insights by the use of standard SQL queries.

Google Bigquery’s use of column-based architecture, helps it in processing large amounts of data without any significant performance drop processing data. The columnar storage helps in processing relevant columns resulting in faster response times and use of resources better. This also helps in benefiting analytical tools to generate insights. 

Key Features of Google BigQuery

Typeform to bigquery: bigquery architecture logo | Hevo data
Image Source: miro.medium.com

Here are a few key features of Google BigQuery:

  • Serverless Services: Usually when When setting up a data warehouse on-premises, enterprises need to set up all the aspects ranging from technical requirements, server hardware, and others. There is also required management to maintain the system. BigQuery helps in eradicating all these issues. Being a serverless platform the tasks are distributed on parallel systems. It also focuses on server provisioning rather than infrastructural requirements. 
  • SQL and Programming Language Support: BigQuery supports standard SQL to query data. It has also support for python, c#, Java, PHP, and many more that can be used to create applications.
  • Tree Architecture: The tree architecture is employed by Google BigQuery. This allows it to be distributed among thousands of computers and acts as a tree structure. The incoming query is processed by the root node and then forwarded to the mixer which acts as the branches of the trees. These queries are transferred to leaf nodes and work in parallel to each other. The results are accumulated and sent back to the root node. This increases the processing speeds for multiple queries.
  • Multiple Data Types: BigQuers supports all data types ranging from simple to complexes like boolean, integer, float, double, strings, and many more. 
  • Security: BigQuery auto-encrypts the data when the data transfer takes place. It also has the provision to isolate tasks to enable multi-user activities. It has the provision for IAM (Access management) permissions that allow altering access privileges. It shares it security certifications with other google applications in the ecosystem. 

Steps to Transfer Data from Typeform to BigQuery               

Sending data from Typeform to BigQuery requires extracting data from Typeform and loading data into BigQuery.                        

Step 1: Getting Data from Typeform

Typeform has APIs that enable the extraction of information from the platform. This extracted data is loaded from Typeform to Bigquery.

Use the following command to get a form response

GET https://api.typeform.com/forms/{form_id}/responses.

Sample Typeform Data

Here’s an example of the kind of response you might see with a query for Typeform to Bigquery.

{
  "total_items": 4,
  "page_count": 1,
  "items": [
    {
      "landing_id": "21085286190ffad1248d17c4135ee56f",
      "token": "21085286190ffad1248d17c4135ee56f",
      "landed_at": "2018-09-14T22:33:59Z",
      "submitted_at": "2018-09-14T22:38:22Z",
      "metadata": {
        "user_agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_12_6) AppleWebKit/603.3.8 (KHTML, like Gecko) Version/10.1.2 Safari/603.3.8",
        "platform": "other",
        "referer": "https://user_id.typeform.com/to/lR6F4j",
        "network_id": "responsdent_network_id",
        "browser": "default"
      },
      "answers": [
        {
          "field": {
            "id": "hVONkQcnSNRj",
            "type": "dropdown",
            "ref": "my_custom_dropdown_reference"
          },
          "type": "text",
          "text": "Job opportunities"
        },
        {
          "field": {
            "id": "RUqkXSeXBXSd",
            "type": "yes_no",
            "ref": "my_custom_yes_no_reference"
          },
          "type": "boolean",
          "boolean": false
        },
        {
          "field": {
            "id": "gFFf3xAkJKsr",
            "type": "legal",
            "ref": "my_custom_legal_reference"
          },
          "type": "boolean",
          "boolean": true
        },
        {
          "field": {
            "id": "JwWggjAKtOkA",
            "type": "short_text",
            "ref": "my_custom_short_text_reference"
          },
          "type": "text",
          "text": "Lian"
        },
        {
          "field": {
            "id": "SMEUb7VJz92Q",
            "type": "email",
            "ref": "my_custom_email_reference"
          },
          "type": "email",
          "email": "lian1078@other.com"
        },
        {
          "field": {
            "id": "pn48RmPazVdM",
            "type": "number",
            "ref": "my_custom_number_reference"
          },
          "type": "number",
          "number": 1
        },
        {
          "field": {
            "id": "Q7M2XAwY04dW",
            "type": "number",
            "ref": "my_custom_number2_reference"
          },
          "type": "number",
          "number": 1
        },
        {
          "field": {
            "id": "WOTdC00F8A3h",
            "type": "rating",
            "ref": "my_custom_rating_reference"
          },
          "type": "number",
          "number": 3
        },
        {
          "field": {
            "id": "DlXFaesGBpoF",
            "type": "long_text",
            "ref": "my_custom_long_text_reference"
          },
          "type": "text",
          "text": "It's a big, busy city. Typeform to Bigquery I moved here for a job, but I like it, so I am planning to stay. Typeform to Bigquery I have made good friends here."
        },
        {
          "field": {
            "id": "NRsxU591jIW9",
            "type": "opinion_scale",
            "ref": "my_custom_opinion_scale_reference"
          },
          "type": "number",
          "number": 1
        },
        {
          "field": {
            "id": "PNe8ZKBK8C2Q",
            "type": "picture_choice",
            "ref": "my_custom_picture_choice_reference"
          },
          "type": "choices",
          "choices": {
            "labels": [
              "New York",
              "Tokyo"
            ]
          }
        },
        {
          "field": {
            "id": "KoJxDM3c6x8h",
            "type": "date",
            "ref": "my_custom_date_reference"
          },
          "type": "date",
          "date": "2012-03-20T00:00:00Z"
        },
        {
          "field": {
            "id": "ceIXxpbP3t2q",
            "type": "multiple_choice",
            "ref": "my_custom_multiple_choice_reference"
          },
          "type": "choice",
          "choice": {
            "label": "A friend's experience in Sydney"
          }
        },
        {
          "field": {
            "id": "k6TP9oLGgHjl",
            "type": "multiple_choice",
            "ref": "my_custom_multiple_choice2_reference"
          },
          "type": "choice",
          "choice": {
            "label": "Tokyo"
          }
        }
      ],
      "hidden": {},
      "calculated": {
        "score": 2
      }
    },
    {
      "landing_id": "610fc266478b41e4927945e20fe54ad2",
      "token": "610fc266478b41e4927945e20fe54ad2",
      "landed_at": "2018-09-14T22:27:38Z",
      "submitted_at": "2018-09-14T22:33:56Z",
      "metadata": {
        "user_agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/59.0.3071.115 Safari/537.36",
        "platform": "other",
        "referer": "https://user_id.typeform.com/to/lR6F4j",
        "network_id": "responsdent_network_id",
        "browser": "default"
      },
      "answers": [
        {
          "field": {
            "id": "k6TP9oLGgHjl",
            "type": "multiple_choice",
            "ref": "my_custom_multiple_choice2_reference"
          },
          "type": "choice",
          "choice": {
            "label": "New York"
          }
        },
        {
          "field": {
            "id": "X4BgU2f1K6tG",
            "type": "file_upload",
            "ref": "my_custom_file_upload_reference"
          },
          "type": "file_url",
          "file_url": "https://admin.typeform.com/form/lT9Z2j/field/X4BgU2f1K6tG/results/afd8258fd453-aerial_view_rural_city_latvia_valmiera_urban_district_48132860.jpg/download"
        },
        {
          "field": {
            "id": "ceIXxpbP3t2q",
            "type": "multiple_choice",
            "ref": "my_custom_multiple_choice_reference"
          },
          "type": "choice",
          "choice": {
            "label": "Other"
          }
        },
        {
          "field": {
            "id": "hVONkQcnSNRj",
            "type": "dropdown",
            "ref": "my_custom_dropdown_reference"
          },
          "type": "text",
          "text": "Cost of living"
        },
        {
          "field": {
            "id": "JwWggjAKtOkA",
            "type": "short_text",
            "ref": "my_custom_short_text_reference"
          },
          "type": "text",
          "text": "Sarah"
        },
        {
          "field": {
            "id": "RUqkXSeXBXSd",
            "type": "yes_no",
            "ref": "my_custom_yes_no_reference"
          },
          "type": "boolean",
          "boolean": true
        },
        {
          "field": {
            "id": "Fep7sEoBsnvC",
            "type": "long_text",
            "ref": "my_custom_long_text_reference"
          },
          "type": "text",
          "text": "I read a magazine Typeform to Bigquery article about traveling to Sydney"
        },
        {
          "field": {
            "id": "gFFf3xAkJKsr",
            "type": "legal",
            "ref": "my_custom_legal_reference"
          },
          "type": "boolean",
          "boolean": true
        },
        {
          "field": {
            "id": "BFcpoPU5yJPM",
            "type": "short_text",
            "ref": "my_custom_short_text_reference"
          },
          "type": "text",
          "text": "San Francisco"
        },
        {
          "field": {
            "id": "SMEUb7VJz92Q",
            "type": "email",
            "ref": "my_custom_rmail_reference"
          },
          "type": "email",
          "email": "sarahbsmith@example.com"
        },
        {
          "field": {
            "id": "pn48RmPazVdM",
            "type": "number",
            "ref": "my_custom_number_reference"
          },
          "type": "number",
          "number": 1
        },
        {
          "field": {
            "id": "WOTdC00F8A3h",
            "type": "rating",
            "ref": "my_custom_rating_reference"
          },
          "type": "number",
          "number": 3
        },
        {
          "field": {
            "id": "Q7M2XAwY04dW",
            "type": "number",
            "ref": "my_custom_number2_reference"
          },
          "type": "number",
          "number": 3
        },
        {
          "field": {
            "id": "DlXFaesGBpoF",
            "type": "long_text",
            "ref": "my_custom_long_text_reference"
          },
          "type": "text",
          "text": "It's a rural area Typeform to Bigquery. Very quiet. There are a lot of farms...farming is the major Typeform to Bigquery industry here."
        },
        {
          "field": {
            "id": "NRsxU591jIW9",
            "type": "opinion_scale",
            "ref": "my_custom_opinion_scale_reference"
          },
          "type": "number",
          "number": 1
        },
        {
          "field": {
            "id": "KoJxDM3c6x8h",
            "type": "date",
            "ref": "my_custom_date_reference"
          },
          "type": "date",
          "date": "2016-05-13T00:00:00Z"
        },
        {
          "field": {
            "id": "PNe8ZKBK8C2Q",
            "type": "picture_choice",
            "ref": "my_custom_picture_choice_reference"
          },
          "type": "choices",
          "choices": {
            "labels": [
              "London",
              "New York"
            ]
          }
        }
      ],
      "hidden": {},
      "calculated": {
        "score": 4
      }
    },
    {
      "landing_id": "9ba5db11ec6c63d22f08aade805bd363",
      "token": "9ba5db11ec6c63d22f08aade805bd363",
      "landed_at": "2018-09-14T22:24:49Z",
      "submitted_at": "2018-09-14T22:27:34Z",
      "metadata": {
        "user_agent": "Mozilla/5.0 (iPhone; CPU iPhone OS 10_2_1 like Mac OS X) AppleWebKit/602.4.6 (KHTML, like Gecko) Version/10.0 Mobile/14D27 Safari/602.1",
        "platform": "other",
        "referer": "https://user_id.typeform.com/to/lR6F4j",
        "network_id": "responsdent_network_id",
        "browser": "default"
      },
      "answers": [
        {
          "field": {
            "id": "RUqkXSeXBXSd",
            "type": "yes_no",
            "ref": "my_custom_yes_no_reference"
          },
          "type": "boolean",
          "boolean": false
        },
        {
          "field": {
            "id": "gFFf3xAkJKsr",
            "type": "legal",
            "ref": "my_custom_legal_reference"
          },
          "type": "boolean",
          "boolean": true
        },
        {
          "field": {
            "id": "JwWggjAKtOkA",
            "type": "short_text",
            "ref": "my_custom_short_text_reference"
          },
          "type": "text",
          "text": "Paolo"
        },
        {
          "field": {
            "id": "pn48RmPazVdM",
            "type": "number",
            "ref": "my_custom_number_reference"
          },
          "type": "number",
          "number": 5
        },
        {
          "field": {
            "id": "Q7M2XAwY04dW",
            "type": "number",
            "ref": "my_custom_number2_reference"
          },
          "type": "number",
          "number": 5
        },
        {
          "field": {
            "id": "PNe8ZKBK8C2Q",
            "type": "picture_choice Typeform to Bigquery",
            "ref": "my_custom_picture_choice_reference"
          },
          "type": "choices",
          "choices": {
            "labels": [
              "Barcelona",
              "Sydney"
            ]
          }
        },
        {
          "field": {
            "id": "WOTdC00F8A3h",
            "type": "rating",
            "ref": "my_custom_rating_reference"
          },
          "type": "number",
          "number": 5
        },
        {
          "field": {
            "id": "DlXFaesGBpoF",
            "type": "long_text",
            "ref": "my_custom_long_text_reference"
          },
          "type": "text",
          "text": "I live in a medium-sized European city Typeform to Bigquery. It's not too crowded, and the people are nice. I like the weather. It's also easy to travel to many beautiful and interesting Typeform to Bigquery vacation destinations from where I live."
        },
        {
          "field": {
            "id": "NRsxU591jIW9",
            "type": "opinion_scale",
            "ref": "my_custom_opinion_scale_reference"
          },
          "type": "number",
          "number": 4
        },
        {
          "field": {
            "id": "KoJxDM3c6x8h",
            "type": "date",
            "ref": "my_custom_date_reference"
          },
          "type": "date",
          "date": "1999-08-01T00:00:00Z"
        },
        {
          "field": {
            "id": "k6TP9oLGgHjl",
            "type": "multiple_choice",
            "ref": "my_custom_multiple_choice_reference"
          },
          "type": "choice",
          "choice": {
            "label": "Barcelona"
          }
        }
      ],
      "hidden": {},
      "calculated": {
        "score": 10
      }
    },
    {
      "landing_id": "5fcb3f9c162e1fcdaadff4405b741080",
      "token": "5fcb3f9c162e1fcdaadff4405b741080",
      "landed_at": "2018-09-15T09:09:30Z",
      "submitted_at": "0001-01-01T00:00:00Z",
      "metadata": {
        "user_agent": "Mozilla/5.0 (Linux; Android 4.1.2; GT-N7000 Build/JZO54K) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/55.0.2883.91 Mobile Safari/537.36",
        "platform": "other",
        "referer": "https://user_id.typeform.com/to/lR6F4j",
        "network_id": "responsdent_network_id",
        "browser": "default"
      },
      "answers": null,
      "hidden": {},
      "calculated": {
        "score": 0
      }
    }
  ]
}

Step 2: Preparing the Typeform Data   

If there are no predefined structural schemas to store data when transferring it from Typeform to Bigquery you need to create one before retrieval. The schema can be made by defining the data type for each column of retrieved data for Typeform to Bigquery

Some of the objects that are retrieved for Typeform to Bigquery are in form of lists and require the creation of additional tables to maintain the cardinality.                   

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Step 3: Load Data into BigQuery

The bq command-line tool will be used to load data into bigquery for Typeform to Bigquery. The command-line tool helps in uploading datasets and following the correct schema for the information transfer from Typeform to Bigquery. 

You learn more about bq command line by clicking here.

Step 4: Updating the Data

After the data is transferred from Typeform to BigQuery, now you need to build a script that constantly identifies updates, and moves these updates into the BigQuery database we created earlier for the Typeform to Bigquery information transfer.                                   

Conclusion

Forms are becoming an ever-popular solution to gather information and generate insights that help businesses and individual vendors. Typeform is a feature-rich solution that makes the process of making easier and enables the creation of forms that are interactive but at the same time easy to use. You would require a storage solution to store the data from these forms. Google BigQuery is a popular solution that is highly stable and moving data from Typeform to BigQuery helps in gaining the insights. This article provides a step-by-step guide to moving data from Typeform to BigQuery.

There are various trusted sources that companies use as it provides many benefits, but, transferring data from it into a data warehouse like BigQuery is a hectic task. The Automated data pipeline helps in solving this issue and this is where Hevo comes into the picture. Hevo Data is a No-code Data Pipeline and has awesome 100+ pre-built Integrations that you can choose from.

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Share your experience of learning about the Typeform to Bigquery in the comments section below.

mm
Former Research Analyst, Hevo Data

Arsalan is a data science enthusiast with a keen interest towards data analysis and architecture and is interested in writing highly technical content. He has experience writing around 100 articles on various topics related to data industry.

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