Amazon Redshift Salesforce Integration: 2 Easy Methods

on CRMs, Data Driven Strategies, Data Extraction, Data Integration • June 23rd, 2021 • Write for Hevo

The data stored in Data Warehouses is primarily used for Analytical workloads by Business Intelligence and Data Analysis tools such as Microsoft Power BI, Tableau, etc. However, businesses have now started recognizing how this data can further be leveraged for Operational Analytics. Operational Analytics is crucial for day-to-day decision-making in an organization to improve the efficiency and effectiveness of its internal operations.

Operational Analytics is empowered when businesses implement a Reverse ETL process between Data Warehouses and their operational tools. Along with using data to identify long-term trends and influence long-term strategy, Operational Analytics helps form the strategy to improve a business’s day-to-day operations. Operational Analytics allows decision-makers to ensure that every decision made is an excellent strategic choice and backed by real-time data. This entire process, however, cannot be implemented without Reverse ETL.

Sending real-time data to Software-as-a-Service (SaaS) systems can help make sure that there is a consistent view of the customer across all systems. For example, pushing data to Salesforce from a Data Warehouse or a Business Intelligence tool means all teams have access to an up-to-date list of each customer’s Lifetime Value, Product Qualified Lead (PQL) and Marketing Qualified Lead (MQL) information, Customer Health, Propensity Score, ARR/MRR, Funnel Stages, etc.

Looker Salesforce
Image Source: https://fivetran.com/blog/reverse-etl-making-the-data-warehouse-actionable

This article will help you understand how you can easily set up Amazon Redshift Salesforce Integration to implement Operational Analytics in your business.

Table of Contents

Introduction to Amazon Redshift

Amazon Redshift Logo
Image Source: https://www.pinterest.se/amp/pin/268456827773302870/

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 with efficient and targeted Data Compression Encoding schemes.

Introduction to Salesforce

Salesforce Logo
Image Source: https://en.wikipedia.org/wiki/File:Salesforce.com_logo.svg

Salesforce is a Cloud-based Software-as-a-Service (SaaS) company. It provides a robust Customer Relationship Management (CRM) tool along with a suite of Enterprise applications focused on Marketing Automation, Customer Service, Analytics, Application Development, etc. Salesforce became the preferred tools for a large number of businesses because of the following reasons:

  • Easy Setup: A traditional Customer Relationship Management (CRM) software can take up to a year to install and deploy. In contrast, Salesforce can be easily set up within a few weeks.
  • Ease of Use: Salesforce wins in the easy-to-use category. Businesses usually spend more time putting it to use and less time understanding how it works.
  • Effective: Since the software is easy to use and can be customized by businesses to meet their requirements, customers find the tool very effective.

More information about Salesforce can be found here.

Understanding the Key Features of Salesforce

The key features of Salesforce are as follows:

  • Account Management: Salesforce allows businesses to have a holistic view of their customers. This means that they have access to activity history, customer communications, key contacts, internal account discussions, etc., at all times.
  • Content Management: Businesses can easily manage all their Social Media or any other content they wish to publish using Salesforce. It also allows them to derive insights from popular Social Media websites such as Twitter, Facebook, LinkedIn, etc.
  • Opportunity Management: With Salesforce, businesses can get a complete view of their deals with Opportunity Management. It allows businesses to review their products, competition, quotes, etc., along with all necessary information for every sale.
  • Lead Management: Salesforce gives businesses the ability to track their leads and continually optimize their campaigns across all channels. This allows them to make smarter data-backed decisions about where and how to invest their Marketing budget.
  • Sales Data and Forecasting: Using Salesforce, businesses get an easy access to the necessary Sales data at the right time, allowing them to connect with potential customers easily, thereby increasing Sales and Marketing productivity with the latest and the most accurate data. It also gives businesses the ability to get a real-time view of your Sales team’s forecasts.
  • Reports and Dashboards: Salesforce dashboards offer a real-time picture of the performance of your business at a glance. It allows businesses to view detailed reports that anyone can create and access those reports and dashboards seamlessly from any location.
  • Workflow and Approvals: Using Salesforce Visual Workflow, businesses can rapidly design and automate all business processes with the drag-and-drop functionality. This can be used to drive success with flexible approval processes for expenses, customer discounts, trial periods, etc.
  • Files Sync and Share: Salesforce gives businesses the ability to share files easily, have a discussion about it with the entire team, and track their content in real-time. Users can also find whatever they’re looking for with its quick search option, share it securely with other team members, and even subscribe to receive alerts when any changes are made.

Ways to Set up Amazon Redshift Salesforce Integration

Method 1: Manual Amazon Redshift Salesforce Integration

This method involves setting up Amazon Redshift Salesforce Integration manually by extracting data from Amazon Redshift as CSV files and then importing them into Salesforce.

Method 2: Amazon Redshift Salesforce Integration using Hevo Activate

Hevo Activate provides a hassle-free solution and helps you directly set up Amazon Redshift Salesforce Integration without any intervention in an effortless manner for free. Hevo Activate 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. Hevo’s pre-built integration with various data sources such as Amazon Redshift, Snowflake, Salesforce, HubSpot, etc., will take full charge of the data transfer process, allowing you to focus on key business activities.

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Methods to Set up Amazon Redshift Salesforce Integration

Users can set up Amazon Redshift Salesforce Integration by implementing one of the following methods:

Redshift Salesforce Integration Method 1: Manual Amazon Redshift Salesforce Integration

Users can manually export Amazon Redshift data as CSV files to set up Amazon Redshift Salesforce Integration by implementing the following steps:

  • Step 1: Log in to your AWS account and open the Amazon S3 Console.
  • Step 2: Click on Create Bucket.
  • Step 3: Enter a suitable Bucket Name as per your requirements. It is, however, important to understand that Amazon S3 Buckets need to have unique names globally, so it should be named accordingly. Enter a suitable region, uncheck Block all Public Access and click Create Bucket.
Create Amazon S3 Bucket
Image Source: https://interworks.com/blog/2020/04/22/creating-and-sharing-an-aws-s3-bucket/
  • Step 4: Copy the URL of this bucket and save it in a secure location.
  • Step 5: Connect to your Amazon Redshift Cluster from which you wish to export the data using a SQL Client such as SQL Workbench/J, Aginity Pro, Jetbrains DataGrip, etc.
  • Step 6: You can leverage the UNLOAD query to export the data from the Amazon Redshift Cluster and load it into Amazon S3. The syntax for the UNLOAD query is as follows:
UNLOAD ('select-statement')
TO 's3://object-path/name-prefix'
authorization
[ option [ ... ] ]
where option is
{ [ FORMAT [ AS ] ] CSV | PARQUET
| PARTITION BY ( column_name [, ... ] ) [ INCLUDE ]
| MANIFEST [ VERBOSE ] 
| HEADER           
| DELIMITER [ AS ] 'delimiter-char' 
| FIXEDWIDTH [ AS ] 'fixedwidth-spec'   
| ENCRYPTED [ AUTO ]
| BZIP2  
| GZIP 
| ZSTD
| ADDQUOTES 
| NULL [ AS ] 'null-string'
| ESCAPE
| ALLOWOVERWRITE
| CLEANPATH
| PARALLEL [ { ON | TRUE } | { OFF | FALSE } ]
| MAXFILESIZE [AS] max-size [ MB | GB ] 
| REGION [AS] 'aws-region' }

An example of the UNLOAD command is as follows:

Amazon Redshift UNLOAD query
Image Source: https://www.sqlshack.com/export-data-from-aws-redshift-to-aws-s3/

A query similar to one in the above example has to be executed by making changes to the S3 Bucket URL and the IAM ARN for Amazon Redshift. The IAM Role assigned to the Redshift Cluster should have Amazon S3 read and write policies.

  • Step 7: You can now download the exported data in the Amazon S3 Bucket.
Amazon S3 Bucket
Image Source: https://www.sqlshack.com/export-data-from-aws-redshift-to-aws-s3/
  • Step 8: Open your Salesforce account, search Data Import Wizard in the Quick Box and open the application.
  • Step 9: Click Launch Wizard.
  • Step 10: If you wish to import contacts, accounts, person accounts, leads, articles, or solutions, click Standard Objects. If you wish to import custom objects, click Custom Objects.
Salesforce Data Import Wizard
Image Source: https://www.greytrix.com/blogs/salesforce/2016/07/04/import-data-using-data-import-wizard-in-salesforce-2/
  • Step 11: Specify whether you want to add new Salesforce records, update existing records, or add and update records simultaneously.
  • Step 12: Upload the CSV file that was exported from Amazon Redshift by dragging it to the upload section of the page.
  • Step 13: Since the data was exported as CSV, ensure that comma is selected as the value separator and click Next.
  • Step 14: The Salesforce Data Import Wizard will now try to match as many attributes as it can automatically. The remaining ones will have to be mapped manually. Click the Map button present on the left of each unmapped field. In the Map Your Field box, you can search and choose up to ten attributes to map with and click Map. If you wish to change any automatically mapped attributes, click the Change button present on the left of the appropriate attribute, delete the Salesforce mapping, choose the Salesforce attribute you want to map it to, then click Map. Once the attributes have been mapped as per requirement, click Next.
Salesforce Import Mapping
Image Source: https://www.greytrix.com/blogs/salesforce/2016/07/04/import-data-using-data-import-wizard-in-salesforce-2/
  • Step 15: A Review Page will now open, where a summary of all the import settings will be displayed along with the attribute mapping. If you do not wish to make any changes, click Start Import.
Review Import Settings
Image Source: https://www.greytrix.com/blogs/salesforce/2016/07/04/import-data-using-data-import-wizard-in-salesforce-2/

Once the import is complete, all necessary data will be present in Salesforce. This completes the process of manual Amazon Redshift Salesforce Integration.

Limitations of Manual Amazon Redshift Salesforce Integration

The limitations associated with the manual process for Amazon Redshift Salesforce Integration are as follows:

  • This manual Amazon Redshift Salesforce Integration method is error-prone and requires the engineering efforts of experienced Amazon Redshift and Salesforce developers.
  • The data imported in Salesforce is static. This means that any changes to the underlying CSV files or new data in Amazon Redshift will not be automatically reflected in Salesforce. Hence, the process to integrate data has to be repeated every time the data is to be updated in Salesforce.
  • Repeating the Amazon Redshift Snowflake Integration method would lead to the creation of duplicate records in Salesforce, which will have to be manually dealt with.
  • Manual Amazon Redshift Salesforce Integration can only be considered a good idea for smaller datasets. It is not scalable for CSV files with a high volume of data, and cannot handle any changes in the data structure. More information about Salesforce Import limits can be found here.

Redshift Salesforce Integration Method 2: Amazon Redshift Salesforce Integration using Hevo Activate

Hevo Logo

Hevo Activate helps you directly transfer data from Snowflake, Amazon Redshift, etc., and various other sources to CRMs such as Salesforce, HubSpot, various SaaS applications, and a lot more, in a completely hassle-free & automated manner. Hevo Activate 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 Activate takes care of all your data preprocessing needs 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. 

Check out what makes Hevo Activate amazing:

  • Real-time Data Transfer: Hevo Activate, with its strong Integration with various sources, allows you to transfer data quickly & efficiently. This ensures efficient utilization of bandwidth on both ends.
  • Data Transformation: It provides a simple interface to perfect, modify, and enrich the data you want to transfer. 
  • Secure: Hevo Activate has a fault-tolerant architecture that ensures that the data is handled in a secure, consistent manner with zero data loss.
  • Tremendous Connector Availability: Hevo Activate houses a large variety of connectors and lets you bring in data from numerous Data Warehouses and load it into Marketing & SaaS applications, such as Salesforce, HubSpot, Zendesk, Intercom, etc. in an integrated and analysis-ready form.
  • Simplicity: Using Hevo Activate is easy and intuitive, ensuring that your data is exported in just a few clicks. 
  • Completely Managed Platform: Hevo Activate is fully managed. You need not invest time and effort to maintain or monitor the infrastructure involved in executing codes.
  • Live Support: The Hevo Activate team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.
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Conclusion

This article provided you with a simplified guide on how you can set up Amazon Redshift Salesforce Integration manually or automatically using Hevo Activate. There are, however, certain limitations associated with the manual method.

If those limitations are not a concern to your operations, then the manual Amazon Redshift Salesforce Integration method can be implemented, but if they are, you can consider using automated platforms like Hevo Activate. It helps you directly transfer data from a source of your choice, such as Snowflake, Amazon Redshift, etc., to any SaaS application, CRMs like Salesforce, etc., in a fully automated and secure manner without having to write the code repeatedly for free. It will make your life easier and make data migration hassle-free. It is user-friendly, reliable, and secure. 

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