Accounting is an essential component of any business. Instead of hiring an expensive account team, SMBs usually opt for accounting software that can handle a large volume of data accurately. Accounting software, such as QuickBooks, provides information about a company’s overall financial performance.
Hence, Having a Cloud data pipeline that is highly automated and can easily replicate data from QuickBooks to Redshift. It enables faster data migration without the need for coding or maintenance.
It keeps track of business transactions and manages the general ledger as well as accounts receivable and payable. You can also keep track of your cash flow, revenue, and expenses. The GST ready feature facilitates GST reconciliation and monitoring. QuickBooks is designed to help you optimize your business and increase profits.
However, eCommerce businesses use a variety of apps and tools to manage various processes and verticals. As a result, companies must tally data from QuickBooks and other apps such as customer support platforms, websites, payment gateways, and CRMs. Continue reading to learn more about this topic and how it can benefit your use case.
What is Quickbooks?
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QuickBooks is a leading account management tool that specializes in bookkeeping, payroll management, inventory management, accounting, and a variety of other financial tasks associated with a business. It has tens of thousands of users worldwide, ranging from small businesses to large enterprises. QuickBooks was developed by Intuit, a California-based company. Its main goal was to automate traditional business operations in order to save time and make tasks like bookkeeping and paperwork easier.
Quickbooks allows for the creation of custom reports based on the needs of the company. This tool also assists in the creation of highly accurate profit and loss statements. This data is useful in determining whether a company is profitable at a given point in time. These statements can also be used to tailor the user’s requirements and preferences in order to determine the unique business information.
Quickbooks allow you to visualize enterprise data such as sales data, customer information, product information, project status, and geographic information. This tool also assists in retrieving GST information and calculating taxes. This allows you to avoid any tax-filing issues. QuickBooks tracks payments and expenses when bank and credit card information is entered.
Key Features of Quickbooks
Here are the features of Quickbooks:
- Accounting Statements: Quickbooks allows users to create custom reports, making it easier to track the company’s progress. It stores and manages all information in a single location, making it easily accessible when needed. Accounting reports simplify the tax filing process.
- Access for Multiple Users: Quickbooks allows you to grant your employees different levels of access to QuickBooks Online. This enables effective collaboration among the organization’s various teams.
- Management of Payments and Cash Flow: Quickbooks has its own online payment system, which allows clients to make payments more quickly when an invoice or statement is provided. This also allows for faster bill payments to partner banks.
- Banking Online: When a bank account is linked to QuickBooks, the bank transactions are uploaded and classified. This eliminates the need for data inputs for bank statements.
- Support: QuickBooks has a large support base, and its support team responds to all inquiries and offers free assistance. It even offers guides, video lectures, and seminars to help you improve your QuickBooks knowledge.
What is Amazon Redshift?
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Amazon Redshift is a petabyte-scale Data warehouse solution powered by Amazon Web Services. It is also used for large database migrations because it simplifies data management.
Amazon Redshift’s architecture is based on Massively Parallel Processing (MPP). Amazon Redshift Databases are based on Column-Oriented Databases and are designed to connect to SQL-based clients and BI tools. This enables users to have constant access to data (structured and unstructured) and aids in the execution of Complex Analytic queries. Amazon Redshift also supports standard ODBC and JDBC connections.
Amazon Redshift is a fully-managed Data Warehouse, users can automate administrative tasks to focus on Data Optimization and Data-driven Business decisions rather than performing repetitive tasks. The Client Application and the Data Warehouse Cluster must be able to communicate with one another in a reliable manner.
Each Cluster in an Amazon Redshift Data Warehouse has its own set of computing resources and runs its own Amazon Redshift Engine with at least one Database.
Key Features of Amazon Redshift
Here are some features of Amazon Redshift:
- An Ecosystem of Integrated Analytics: The built-in ecosystem services of AWS make End-to-End Analytics workflow management easier while avoiding compliance and operational stumbling blocks. Some well-known examples include AWS Lake Formation, AWS Glue, AWS EMR, AWS DMS, AWS Schema Conversion Tool, and others.
- SageMaker Help: It allows users to build and train Amazon SageMaker models for Predictive Analytics using data from your Amazon Redshift Warehouse, making it a must-have for today’s Data Professionals.
- For Maximum Performance, Use ML: Amazon Redshift has robust Machine Learning (ML) capabilities that enable high throughput and speed. Its sophisticated algorithms predict incoming inquiries based on specific factions, allowing important jobs to be prioritized.
How to Connect Quickbooks to Redshift?
You can set up Quickbooks Redshift and transfer data from Quickbooks to Redshift in a variety of ways to perform insightful analysis. You can accomplish this using either of the two methods listed below:
Method 1: Using Hevo Data’s No-code Data Pipeline to Connect Quickbooks to Redshift
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Hevo provides an Automated No-code Data Pipeline that helps you move your Quickbooks data swiftly to Redshift. Hevo is fully-managed and completely automates the process of not only loading data from your desired source 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 in a secure, consistent manner with zero data loss.
Manually mapping fields from source to destination, as mentioned in the previous method, is a time-consuming process. Hevo has a feature called Automapping that can help you avoid this hassle. When you enable Automapping, Hevo will automatically create a table in the destination and map it to the source.
It provides a consistent & reliable solution to manage data in real-time and always have analysis-ready data in your desired destination. It allows you to focus on key business needs and perform insightful analysis using BI tools.
You just need to follow a simple process to connect Quickbooks to Redshift using Hevo:
Step 1: Configure the Source
- Login to your Hevo account using the appropriate credentials.
- Navigate to the Asset Palette and click on the Pipelines option.
- Click on the +Create button to create a new pipeline and search for Quickbooks.
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Step 2: Set up Amazon Redshift as a Destination
Perform the following steps to configure Amazon Redshift as a Destination in Hevo:
- Click DESTINATIONS in the Asset Palette.
- Click + CREATE in the Destinations List View.
- On the Add Destination page, select Amazon Redshift.
- In the Configure your Amazon Redshift Destination page, specify the following:
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You can easily connect Quickbooks to Redshift using Hevo by following the steps outlined above!
Here are more reasons to try Hevo:
- Smooth Schema Management: Hevo takes away the tedious task of schema management & automatically detects the schema of incoming data and maps it to your schema in the desired Data Warehouse.
- Exceptional Data Transformations: Best-in-class & Native Support for Complex Data Transformation at fingertips. Code & No-code Fexibilty designed for everyone.
- Quick Setup: Hevo with its automated features, can be set up in minimal time. Moreover, with its simple and interactive UI, it is extremely easy for new customers to work on and perform operations.
- Built To Scale: As the number of sources and the volume of your data grows, Hevo scales horizontally, handling millions of records per minute with very little latency.
- Live Support: The Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.
Try Hevo to easily connect Quickbooks to Redshift!
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Method 2: Manually Connecting Quickbooks to Redshift
To get started, follow these steps to connect Quickbooks to Redshift:
Step 1: Access Data On QuickBooks
The first step in loading your QuickBooks data into any data warehouse solution is to gain access to it and begin extracting it using the available web API.
QuickBooks has a very rich and well-defined API, which reflects the product’s extensive development. The API is organized around the following major resource groups.
Report resources include all of the reports available in QuickBooks from within the application. They have a different data model than the rest of the resources, and when extracting data from the API, you must account for these differences.
The remaining resources include almost every entity defined by QuickBooks, each with its own data model that is serialized in JSON.
Step 2: Prepare Your Data from Quickbooks to Redshift
After you’ve accessed the QuickBooks data, you’ll need to transform it based on two key factors:
- The limitations of the database into which the data will be loaded
- The type of analysis you intend to conduct
Each system has its own restrictions on the data types and data structures that it can support. If you want to push data into Google BigQuery, for example, you can send nested data like JSON directly. However, when dealing with tabular data stores such as Microsoft SQL Server, this is not an option. Instead, you must flatten any data before inserting it into the database.
You must also select the appropriate data types. Again, depending on the system to which you will send data and any data types exposed by the API, you must make the appropriate choices. These decisions are significant because they can limit the expressivity of your queries and limit what your analysts can do directly from the database.
Step 3: Transform Your Quickbooks Data For Amazon Redshift
Amazon Redshift is based on industry-standard SQL and includes features for managing very large data sets and performing high-performance analysis. As a result, in order to load any data, you must adhere to its data model, which is a typical relational database model. Any information extracted from a data source should be organized into tables and columns. Whereas the table can be thought of as a map to the resource you want to store and the columns as the attributes of that resource.
Because data is most likely coming in a representation like JSON, which supports a much narrower range of data types, you must be very careful about what data you feed into Redshift and ensure that your types have been mapped into one of the datatypes.
Step 4: Load Quickbooks Data Into Amazon Redshift
To upload data to Amazon S3, you’ll need to use the AWS REST API; as we’ve seen before, APIs play an important role in both data extraction and data loading in our data warehouse. The first task is to create a bucket, which you do by executing an HTTP PUT on the Amazon AWS REST API endpoints for S3.
After you’ve created your bucket, you can begin sending data to Amazon S3 via the same AWS REST API, but this time using the endpoints for Object operations. As with the Bucket, you can either directly access the HTTP endpoints or use your preferred library.
So far, we’ve only scratched the surface of what Quickbooks to Redshift can do and how to load data into it. Things can become even more complicated if you want to integrate data from multiple sources.
Limitations of Manually Connecting Quickbooks to Redshift
Here are some limitations of Manually Connecting Quickbooks to Redshift:
- Building Data Pipeline: Building an in-house data pipeline necessitates a significant amount of experience, time, and manpower, as well as a high risk of error.
- Time-Consuming: You must Extract Data using QuickBooks APIs and then properly connect it to the Amazon Redshift Data Warehouse.
- Hard Coding: Analysts must write code and manage infrastructure, but they cannot access their Amazon ads data in a matter of hours.
Benefits of Connecting Quickbooks to Redshift
Here is the list of benefits of connecting Quickbooks to Amazon Redshift:
- A visit record is created and converted into a format compatible with Amazon Redshift and Quickbooks software (Contact record -> Activity log).
- When a sale is made, a Customer Record and Sales Order are created automatically.
- Visitor behavior is monitored and recorded in order to create user profiles for personalized displays, marketing messages, recommendations, and content curation.
- Sales orders and quotes are routed to the appropriate departments for review, fulfillment, and shipping.
- Shipping information is converted into readable formats and sent to the eCommerce store.
Conclusion
This article taught you how to connect Quickbooks to Redshift in a seamless manner. It also provided in-depth knowledge about the concepts behind every step to help you understand and implement them efficiently.
However, migrating complex data from a diverse set of data sources like Quickbooks, CRMs, Project management Tools, Streaming Services, and Marketing Platforms to Amazon Redshift can seem to be quite challenging. This is where a simpler alternative like Hevo can save your day!
Hevo Data is a No-Code Data Pipeline that offers a faster way to move data from 100+ Data Sources such as Quickbooks to a destination of your choice such as Amazon Redshift. Hevo is fully automated and hence does not require you to code.
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Share with us your experience of learning about the methods used for connecting Quickbooks to Redshift in the comments below.
Davor is a data analyst at heart with a passion for data, software architecture, and writing technical content. He has experience writing more than 100 articles on data integration and infrastructure.