Quickbooks is an accounting software from Intuit Inc, designed to manage payroll, inventory, sales, and other accounting needs of small businesses. It is used by thousands of small businesses and has affordable pricing in addition to a broad range of accounting features.

Snowflake’s Data Cloud is built on a cutting-edge data platform that is delivered as Software-as-a-Service (SaaS). Snowflake provides Data Storage, Processing, and Analytic Solutions that are faster, easier to use, and more flexible than traditional options.

This article discusses the different methods to Connect Quickbooks to Snowflake extensively. In addition to that, it also describes Quickbooks and Snowflake briefly.

What is Quickbooks?

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Quickbooks is a fully-featured business and financial management suite that includes tools for Accounting, Inventory, Payroll, Tax Filing, Invoicing, Bank Account Tracking and Reconciliation, Expense Management, Budgeting, Payment Processing, and Management of Accounts receivable and payable.

Quickbooks has ready-to-use templates for generating graphs, business plans, invoices, and spreadsheets. It can also help company owners save time and effort by automating signatures on checks. In terms of connectivity with other tools, Quickbooks provides a lot of advantages. It comes with an intuitive user interface that guides users through all of the capabilities.

Key Features of Quickbooks

  • Quickbooks automates simple tasks thus saving time for bookkeeping and paperwork. 
  • Reports can be generated and customized easily, allowing you to see the health of your business.
  • Quickbooks is affordable regardless of the size of your business. Anybody can afford it – from a sole proprietorship to a $25 million corporation. Their PC Accounting software is unquestionably one of the best business bargains accessible.
  • In Quickbooks, all of your data is kept in one place and can be quickly retrieved as needed. Every transactional information and bank statement will be available for the accountant to review and verify, making the tax filing procedure simple and accurate.
  • Quickbooks can be customized according to one’s needs and choices, thus making them flexible and adaptable to a wide array of businesses. 
  • Quickbooks is a robust, reliable, and time-tested product. Quickbooks Accounting software is used by hundreds of thousands of small companies worldwide. A software package with such a large user base can’t go wrong.
  • Over 700 integrations are connected to Quickbooks ensuring that the processes and workflows are connected, thus facilitating business operations.
  • The Quickbooks Online Payment System allows you to get paid faster where you can email an invoice or statement, allowing your customer the option to pay you with a credit card or bank transfer. You can even check whether they have seen the invoice or not.
  • Quickbooks Payroll Service is integrated with Quickbooks, so all of your transactions are updated and you can view all important information while filing your taxes.
  • You can pay your bills online through Quickbooks. No envelopes, stamps, or paper checks are required once you set up your current bank account.

What is Snowflake?

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Snowflake is a fully managed SaaS (Software as a Service) that combines Data Warehousing, Data Lakes, Data Engineering, Data Science, Data Application Development, and Secure Sharing and Consumption of Real-time / Shared Data into a single platform. To meet the demanding needs of growing businesses, Snowflake includes out-of-the-box features such as Storage and Compute Separation, On-the-fly Scalable Compute, Data Sharing, Data Cloning, and third-party Tool Support.

Snowflake isn’t based on any existing database technology or “Big Data” software platforms like Hadoop. However, it combines a brand-new SQL query engine with cutting-edge Cloud Architecture. Snowflake also gives users all of the features and capabilities of an enterprise analytic database, plus a lot more.

Key Features of Snowflake

Here are some of the features of Snowflake as a Software as a Service (SaaS) solution:

  • Snowflake enables you to enhance your Analytics Pipeline by transitioning from nightly Batch Loads to Real-time Data Streams, allowing you to improve the quality and speed of your analytics. By enabling Secure, Concurrent, and Monitoring Access to your Data Warehouse across your organization, you can improve the quality of analytics at your company.
  • Snowflake uses the Caching Paradigm to deliver the results from the cache swiftly. To avoid re-generating the report when nothing has changed, Snowflake employs Persistent (within the session) Query results.
  • Snowflake allows you to get rid of silos and ensure access to meaningful insights across the enterprise, resulting in better Data-driven Decision-Making. This is a crucial first step toward bettering partner relationships, optimizing pricing, lowering operational expenses, increasing sales effectiveness, and more.
  • Snowflake allows you to better analyze Customer Behaviour and Product Usage. You can also use the whole scope of data to ensure Customer Satisfaction, drastically improve product offers, and foster Data Science innovation.
  • Snowflake allows you to create your own Data Exchange, which allows you to communicate live, controlled data securely. It also encourages you to improve data relationships throughout your business units, as well as with your partners and customers.

Why Integrate Quickbooks to Snowflake?

Quickbooks to Snowflake integration has many benefits. Quickbooks data can be used to improve inventory budget allocations, reduce payment defaulters, reduce losses from incorrect tax filing or tax claims, and optimize marketing budgets. Analyzing all the data produced by the various apps and tools in use is necessary to get a complete picture of the business. Separate data silos require that different sheets be downloaded from each of these numerous sources to create detailed reports.

Therefore, it is necessary to properly analyze all of the inventory data, customer feedback, customer behavior, and payment gateway data to create a comprehensive picture of the entire business. Decision-makers would then act to further optimize processes based on this understanding of the areas that needed improvement. Manually carrying out Quickbooks to Snowflake process would take a lot of time and effort, and the analysis would not be very precise. Consequently, businesses miss out on potential sales.

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Methods for Quickbooks to Snowflake Data Migration 

Method 1: Using Hevo to Set Up Quickbooks to Snowflake

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Hevo provides an Automated No-code Data Pipeline that helps you move your Quickbooks to Snowflake. Hevo is fully-managed and completely automates the process of not only loading data from your 150+ data sources(including 40+ free sources)but also enriching the data and transforming it into an analysis-ready form without having to write a single line of code. Its fault-tolerant architecture ensures that the data is handled securely and consistently with zero data loss.

Using Hevo, you can connect Quickbooks to Snowflake in the following 2 steps:

  • Step 1: Configure Quickbooks as the Source in your Pipeline by following these steps:
    • Step 1.1: For your Quickbooks instance, get authenticated access credentials.
    • Step 1.2: In the Asset Palette, select PIPELINES.
    • Step 1.3: In the Pipelines List View, click + CREATE.
    • Step 1.4: Select Quickbooks on the Select Source Type page.
    • Step 1.5: Click + ADD Quickbooks ONLINE ACCOUNT on the Configure your Quickbooks Online account page.
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  • Step 1.6: Use the registered email address or user ID to log into your account on the Sign In page.
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  • Step 1.7: Do the following on the Quickbooks App Store page:
    • Choose the business you want to ingest data from from the drop-down menu, then click Next. This is applicable if your account is linked to multiple businesses.
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  • To give Hevo access to the chosen company’s data, click Connect.
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  • Step 1.8: Enter the following information on the Configure your Quickbooks Online Source page:
    • Pipeline Name: A distinct name for the Pipeline that isn’t longer than 255 characters.
    • Authorized Account (Non-editable): The distinctive ID of the business you chose earlier when connecting your Quickbooks Online account is already pre-filled in this field.
    • Client Secret: The time frame during which historical data must be ingested. 6 Months is the default value.
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  • Step 1.9: Simply press TEST & CONTINUE.
  • Step 2: To set up Snowflake as a destination in Hevo, follow these steps:
    • Step 2.1: In the Asset Palette, select DESTINATIONS.
    • Step 2.2: In the Destinations List View, click + CREATE.
    • Step 2.3: Select Snowflake from the Add Destination page.
    • Step 2.4: Set the following parameters on the Configure your Snowflake Destination page:
      • Destination Name: A unique name for your Destination.
      • Snowflake Account URL: This is the account URL that you retrieved.
      • Database User: The Hevo user that you created in the database. In the Snowflake database, this user has a non-administrative role.
      • Database Password: The password of the user.
      • Database Name: The name of the Destination database where data will be loaded.
      • Database Schema: The name of the Destination database schema. Default value: public.
      • Warehouse: SQL queries and DML operations are performed in the Snowflake warehouse associated with your database.
quickbooks to snowflake: configure snowflake as destination
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  • Step 2.5: Click Test Connection to test connectivity with the Snowflake warehouse.
  • Step 2.6: Once the test is successful, click SAVE DESTINATION.
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Method 2: Using Custom Code to Move Data from Quickbooks to Snowflake

Access Your Data On Quickbooks

Accessing and extracting your Quickbooks to Snowflake data available through web API is the first step.

Due to the extensive development, the product has undergone, Quickbooks has a very robust and clear API. The API is built around the primary resource categories listed below.

  • Transaction resources.
  • Name list resources.
  • Report resources.
  • Supporting resources.

All of the reports that Quickbooks also provides from the application’s interface are contained in report resources. When extracting data from the API, you must take into account that they have a different data model from the other resources.

The remaining resources include practically every entity that Quickbooks could define, each with a unique data model serialized in JSON.

In addition to the aforementioned, you should bear in mind the following when working with an API, such as the one provided by Quickbooks:

  • Rate Limits: Each API has some rate restrictions that you must adhere to.
  • Authentication: Using an API key, you authenticate on Quickbooks.
  • Paging and Dealing with a Big Amount of Data: Platforms like Quickbooks often produce a lot of data because accounting and financial transactions involve a wide range of potential outcomes. It might be challenging to extract large amounts of data from an API, especially if you take into account and adhere to any rate limitations the API may have.

Transform And Prepare Your Data 

  • Transforming and Preparing data for Quickbooks to Snowflake integration is the next step. You must transform the data you have accessed from Quickbooks based on two main considerations:
    • The database’s restrictions that will be used
    • The kind of analysis you intend to conduct
  • Each system’s supported data types and data structures are subject to specific restrictions. You can send nested data, such as JSON, directly to Google BigQuery if you want to push data into it. However, this is not an option when working with tabular data stores like Microsoft SQL Server. Instead, before loading your data into a database, you will need to flatten it out.
  • Additionally, you must pick the appropriate data types. You will once again need to make the appropriate decisions based on the system to which you will send data and the data types that the API exposes to you. These decisions are crucial because they may restrict the expressiveness of your queries and the tasks that your analysts can perform directly from the database.
  • Many of the resources you can access in Quickbooks may need to flatten out and be pushed into multiple tables due to its extremely rich data model.
  • Additionally, Quickbooks has a unique collection of resources called reports. These resources have a tabular but nested format that resembles a sophisticated spreadsheet. You must redesign, parse, and transform these reports into a tabular form that can be stored in a database to make them compatible with a database data model.
  • In Snowflake DB, data is arranged in tables with a clear set of columns, each with a distinct data type.
  • Snowflake offers a wide range of data type support. Several semi-structured data types are also supported, which is important to note. With Snowflake, data can be loaded directly in JSON, Avro, ORC, Parquet, or XML formats. Similar to Google BigQuery, hierarchical data is treated as a first-class citizen.
  • One prominent common data type is also not supported by Snowflake. The data type LOB, or large object, is not supported. Use a BINARY or VARCHAR type as an alternative. These types, however, are not very useful in use cases involving data warehouses.
  • Creating a schema where you will map each API endpoint to a table is a typical approach for loading data from Quickbooks to Snowflake.
  • You should map each key for Quickbooks to Snowflake integration in the Quickbooks API endpoint response to a table column and make sure that the conversion to the appropriate Snowflake DB data type is made.
  • Naturally, you must make sure that your database tables are updated as the Quickbooks API’s data types could change. Automatic data type casting is not a thing.
  • You can proceed and begin inserting data into Snowflake DB once you have a comprehensive and clearly defined data model or schema for it.

Load Data From Quickbooks To Snowflake

Loading Data from Quickbooks to Snowflake is done using commands. Data files in JSON format are kept on a local file system or in Amazon S3 buckets. The COPY INTO command is typically used to bulk load data into Snowflake DB. Data is then copied into the data warehouse by using the Snowflake DB instance’s COPY INTO command.

Before using the COPY command, the files can be pushed from Quickbooks to Snowflake using the PUT command in a staging environment.

Another option is to directly upload data to a service like Amazon S3, where Snowflake can access the information directly.

Updating Your Quickbooks Data On Snowflake

You will need to update your older data on Snowflake DB because you will be creating more data on Quickbooks. This includes newly created records as well as updates to older records that have been made for any reason in Quickbooks.

Regularly checking Quickbooks for new data will require you to repeat the previous steps while, if necessary, updating the data that is already available. UPDATE statements are used to update an already existing row on a Snowflake DB table.

Finding and deleting any duplicate records from your database is another problem you need to deal with. Duplicate records may be added to your database due to errors in your data pipelines or because Quickbooks lacks a mechanism to identify new and updated records.

Generally speaking, ensuring the quality of data inserted into your database is a significant and challenging issue.

Conclusion

This article explains how to connect Quickbooks to Snowflake using various methods. It also gives an overview of Snowflake and Quickbooks.

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Hevo offers a No-code Data Pipeline that can automate your data transfer process, hence allowing you to focus on other aspects of your business like Analytics, Marketing, Customer Management, etc.

This platform allows you to transfer data from 150+ sources (including 40+ Free Sources) such as Quickbooks and Cloud-based Data Warehouses like Snowflake, Google BigQuery, etc. It will provide you with a hassle-free experience and make your work life much easier.

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Harshitha Balasankula
Former Marketing Content Analyst, Hevo Data

Harshita is a data analysis enthusiast with a keen interest for data, software architecture, and writing technical content. Her passion towards contributing to the field drives her in creating in-depth articles on diverse topics related to the data industry.

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