It is a common practice for most businesses today to rely on data-driven decision-making. Businesses collect a large volume of data and leverage it to perform an in-depth analysis of their customers and products, allowing them to plan future Growth, Product, and Marketing strategies accordingly.
A large number of businesses use platforms like Google Sheets to store their data. Although it is easy to perform simple analysis on Google Sheets, it is not possible to perform complex analysis on the platform. Businesses might also be looking to create a Single Source of Truth for all their data which might not be easy to do on Google Sheets. Hence, businesses feel the need to set up Google Sheets to Redshift Migration and this article will provide you with two easy methods that can help you do that.
Introduction to Google Sheets
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Google Sheets is a free Web-based Spreadsheet program provided by Google as a part of its Google Apps Suite. It allows multiple users to create, edit and collaborate on Spreadsheets in real-time. Google Sheets is a free and fully functional Spreadsheet program that is compatible with the most popular Spreadsheet formats. As a Cloud-based Software-as-a-Service (SaaS) utility, your files are accessible from anywhere via computer and mobile devices.
More information about Google Sheets can be found here.
Understanding the Key Features of Google Sheets
The key features of Google Sheets are as follows:
- Collaborative Editing: One of the most widely used features of Google Sheets is Collaborative Editing in real-time. This allows multiple people to work on a single sheet from different devices at any point in time. Google Sheets also houses a robust sidebar chat feature that gives collaborators the ability to discuss edits in real-time and make recommendations either through chat or its comment functionality. Collaborators can also choose to track changes using the Revision History feature.
- Offline Editing: Google Sheets allows users to edit files even if they are not connected to the Internet. On the desktop, users can install the Google Docs Offline extension on Google Chrome to enable offline editing for all applications within Google Docs.
- Integration with Google products: Google Sheets and other Google Docs applications can easily be integrated with other Google products such as Google Forms, Google Translate, Google Finance, etc.
Introduction to Amazon Redshift
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Amazon Redshift is a fully-managed petabyte-scale Cloud-based Data Warehouse, that was developed by Amazon. It was designed for the storage and analysis of petabyte-scale data. Amazon Redshift is built on a Column-oriented Architecture and designed to connect with numerous SQL-based clients, Business Intelligence, and Data Visualization tools and make data available to users in real-time. Based on PostgreSQL 8, Amazon Redshift delivers significantly enhanced performance and more efficient querying as compared to all other Data Warehouses. This helps teams make sound business analyses and decisions. More than 15,000 businesses now use Amazon Redshift globally, including large Enterprises such as Pfizer, McDonald’s, Facebook, etc.
More information on Amazon Redshift can be found here.
Understanding the Key Features of Amazon Redshift
The key features of Amazon Redshift are as follows:
- Massively Parallel Processing (MPP): Massively Parallel Processing is a distributed design approach in which the divide and conquer strategy is applied by several processors on large data jobs. A large processing job is broken down into smaller jobs which are then distributed among a cluster of Compute Nodes. These Nodes perform their computations parallelly rather than sequentially. As a result, there is a considerable reduction in the amount of time Redshift requires to complete a single, massive job.
- Fault Tolerance: Data Accessibility and Reliability are of paramount importance for any user of a database or a Data Warehouse. Amazon Redshift monitors its Clusters and Nodes around the clock. When any Node or Cluster fails, Amazon Redshift automatically replicates all data to healthy Nodes or Clusters.
- Redshift ML: Amazon Redshift houses a functionality called Redshift ML that gives data analysts and database developers the ability to create, train, and deploy Amazon SageMaker models using SQL seamlessly.
- Column-Oriented Design: Amazon Redshift is a Column-oriented Data Warehouse. This makes it a simple and cost-effective solution for businesses to analyze all their data using their existing Business Intelligence tools. Amazon Redshift achieves optimum query performance and efficient storage by leveraging Massively Parallel Processing (MPP), Columnar Data Storage, along efficient and targeted Data Compression Encoding schemes.
Methods to Set up Google Sheets to Redshift Migration
Businesses can set up Google Sheets to Redshift Migration by implementing one of the two following methods:
Method 1: Manual Google Sheets to Redshift Migration
Users can set up manual Google Sheets to Redshift Migration by implementing the following steps:
Step 1: Extracting Google Sheets Data as CSV
- Open the Google Sheets file you wish to load into Amazon Redshift.
- Click on File in the upper left corner.
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- Click on Download As and select Comma-Separated Values (.csv).
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- The data will then be exported to CSV and will be downloaded to your local system. The same process can be followed if you wish to import data from multiple Google Sheets to Redshift.
Step 2: Loading Data to Amazon Redshift
Users can load their Google Sheets data to Redshift by implementing the following steps:
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- Pick a suitable unique name for your AWS S3 Bucket, select a region as per requirement, and click on Create.
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- Open the AWS S3 Bucket that you just created, click on Create Folder, provide a suitable unique name for it, and click on Save.
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- Upload the Google Sheets CSV data exported previously to the newly created folder by clicking on Upload selecting the necessary files in the Upload Wizard.
- The data in Amazon S3 can be imported into Amazon Redshift Cluster using the COPY Command.
- Connect to the Cluster using a SQL Workbench tool of your choice and run the following query:
COPY table_name
FROM 's3://<your-bucket-name>/load/file_name.csv'
credentials 'aws_access_key_id=<Your-Access-Key-ID>'
CSV;
- If you wish to ignore the file header rows in the CSV files, then you may also specify that by running the following query:
COPY table_name
FROM 's3://<your-bucket-name>/load/file_name.csv'
credentials 'aws_access_key_id=<Your-Access-Key-ID>'
CSV
IGNOREHEADER 1;
Your data should now be accessible and queriable in your Amazon Redshift database.
Limitations of Manual Google Sheets to Redshift Migration
The limitations of setting up manual Google Sheets to Redshift Migration are as follows:
- Manual Google Sheets to Redshift Migration is a complex process that might be tough to perform for someone who does not have enough technical knowledge of Amazon Redshift.
- The process of exporting the data from Google Sheets and importing it into Amazon Redshift has to be done manually every time the data has to be updated in the Cluster.
- Every time the data is exported from Google Sheets, it will also include the data that was imported into Amazon Redshift previously. Hence, the existing records either have to be removed manually from the exported data before they are imported into Amazon Redshift, or duplicates have to be removed from Amazon Redshift once the data has been imported.
Method 2: Google Sheets to Redshift Migration Using Hevo Data
Hevo helps you directly transfer data from Google Sheets and various other sources to Amazon Redshift, Business Intelligence tools, Data Warehouses, or a destination of your choice in a completely hassle-free & automated manner. 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.
Hevo takes care of all your data preprocessing needs required to set up Google Sheets to Redshift Migration and lets you focus on key business activities and draw a much powerful insight on how to generate more leads, retain customers, and take your business to new heights of profitability. It provides a consistent & reliable solution to manage data in real-time and always have analysis-ready data in your desired destination.
Get Started with Hevo for free
The following steps can be implemented to set up Google Sheets to Redshift Migration using Hevo:
- Configure Source: Connect Hevo Data with Google Sheets by providing a unique name for your Pipeline, along with details about your authorized Google account and the list of Google Sheets files you wish to load data from.
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- Integrate Data: Complete Google Sheets to Redshift migration by providing information about your Redshift database and its credentials such as database name, username, and password, along with information about port number associated with your Redshift database. You’ll also need to need to provide the schema name for your database, and its cluster, along with a unique name for your destination.
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Let’s look at Some Salient Features of Hevo:
- Secure: Hevo has a fault-tolerant architecture that ensures that the data is handled in a secure, consistent manner with zero data loss.
- Schema Management: Hevo takes away the tedious task of schema management & automatically detects schema of incoming data and maps it to the destination schema.
- Minimal Learning: Hevo, with its simple and interactive UI, is extremely simple for new customers to work on and perform operations.
- Hevo Is 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.
- Incremental Data Load: Hevo allows the transfer of data that has been modified in real-time. This ensures efficient utilization of bandwidth on both ends.
- Live Support: The Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.
- Live Monitoring: Hevo allows you to monitor the data flow and check where your data is at a particular point in time.
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Conclusion
This article provided you with a step-by-step guide on how you can set up Google Sheets to Redshift Migration manually or using Hevo. However, there are certain limitations associated with the manual method. If those limitations are not a concern to your operations, then using it is the best option but if it is, then you should consider using automated Data Integration platforms like Hevo.
Hevo helps you directly transfer data from a source of your choice to a Data Warehouse, Business Intelligence, or desired destination in a fully automated and secure manner without having to write the code. It will make your life easier and make data migration hassle-free. It is User-Friendly, Reliable, and Secure.
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Want to take Hevo for a spin? Sign Up for a 14-day free trial and experience the feature-rich Hevo suite first hand.
Share your experience of connecting Google Sheets to Redshift in the comments section below!