Today, organizations rely on many technologies such as chatbots, social media platforms, emails, and more to communicate with customers. But, all these technologies lack the human touch that customers mostly want. As every customer interaction is different, a human touch becomes essential to address problems. Therefore, organizations use Front to build strong customer relations and provide human interaction.

Front enables teams in organizations to collect customer data from different channels and store it in one place. It also allows organizations to analyze their customer data with Front analytics. Organizations can then store the Front Analytics data in a data warehouse like Amazon Redshift, which can be further used with powerful BI tools to gain meaningful insights.

In this article, you will learn how to connect Front to Redshift in two methods and the limitations of connecting Front to Redshift. 

Prerequisites

  • Fundamental knowledge of AWS cloud

What is Front?

Front to Redshift: front logo
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Developed in 2013, Front is a communication hub that helps organizations strengthen customer relationships. It offers organizations to deliver an experience their customers can rave about. Front enables organizations to let clients be at the center of all operations for professional service teams, right from support to marketing and development.

It allows organizations to collect customer data from different channels such as emails, texts, social media, WhatsApp, calls, and more on one platform. This enables teams in organizations to collaborate and respond to their customers in real-time. Front also offers organizations automated workflows and analytics features, which can analyze data and provide a complete 360 view of all the customer data. As a result, organizations can get a complete idea of their customers, which would then help enhance the customer experience.

Front improves the customer experience by allowing organizations to send better and faster responses by assigning messages to the right person, tagging by a topic, and looping in teammates for quick help.

Key Features of Front

  • Automated integrations: Front consists of no-code automation and integration capabilities, which can replace the complexity of the manual integration processes. It contains a library of integration that allows you to connect Front to your favorite tools, CRM, chatbots, and more. These integrations are easy to use and can be done with a few clicks. Front includes plugin integrations for Salesforce, Hubspot, Shopify, Aircall, Forumbee, and more. Therefore, businesses can quickly transfer data for collaboration.
  • Win more Customers: As Front allows organizations to collect data from different sources such as emails, texts, calls, WhatsApp, and more, organizations quickly resolve customers’ issues, thereby keeping them happy.
  • Collaboration: Front allows organizations to access customer data across different channels in one place in the team inbox. It ensures that every user in a team can access every message. As a result, whenever there is any customer query in the team inbox, the team can immediately inform the intended team member to handle the message without any confusion.

What is Amazon Redshift?

Front to Redshift: redshift logo
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Developed in 2012, Amazon Redshift is a popular, fully scalable, and reliable data warehouse. Organizations can start using Amazon Redshift with a set of nodes called Amazon clusters. The Amazon clusters can be managed by Amazon Command Line Interface or Redshift Console. Amazon Redshift consists of a column-oriented database, which helps organizations in connecting SQL-based clients like BI tools for quick analysis. As Amazon Redshift is a fully scalable data warehouse, organizations need not worry about administrative tasks like memory management, resource allocation, configuration management, and more.

Amazon Redshift also allows organizations to manage clusters programmatically by using Amazon Redshift Query API or AWS Software Development Kit.

Key Features of Amazon Redshift

  • ANSI-SQL: Amazon Redshift is based on ANSI-SQL, which uses industry-standard ODBC and JDBC connections, enabling you to use your existing SQL clients and BI tools. You can seamlessly query files like CSV, JSON, ORC, Avro, Parquet, and more with ANSI-SQL.
  • AQUA (Advanced Query Accelerator): Amazon Redshift consists of a distributed and hardware-accelerated cache known as AQUA. It speeds up Amazon Redshift up to 10x compared to other enterprise cloud data warehouses.
  • Robust Security: Amazon Redshift enables users to secure data warehouses without an additional cost. With Amazon Redshift, users can configure firewalls to control network access with a specific data warehouse cluster. Amazon Redshift allows users to train the column and the row-level security control to ensure that they can only view the data with authorized access.
  • Result Caching: The result caching feature of Amazon Redshift can deliver a sub-second response time for repeated queries. When a query is executed in Amazon Redshift, it can search the cache to get any search results from the previous queries.
  • Fast Performance: Amazon Redshift offers fast performance due to its unique features such as massively parallel processing, columnar data storage, result caching, query optimizer, data compression, compiled code, and more.
Explore These Methods to Connect Front to Redshift

Front is a customer communication hub that surrounds every high-stakes conversation with capabilities for team collaboration and contextual data. This helps to ensure that responses are always quick, accurate, and extremely personalised. Also, Amazon Redshift is a data warehouse known for ingesting data instantaneously and performing almost real-time analysis. When integrated together, moving data from Front to Redshift could solve some of the biggest data problems for businesses. In this article, we have described two methods to achieve this:

Method 1: Connecting Front to Redshift using Hevo

Hevo Data, an Automated Data Pipeline, provides you a hassle-free solution to connect Front to Redshift within minutes with an easy-to-use no-code interface. Hevo is fully managed and completely automates the process of not only loading data from Xero but also enriching the data and transforming it into an analysis-ready form without having to write a single line of code.

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Method 2: Connecting Front to Redshift using CSV

This method would be time-consuming and somewhat tedious to implement. Users will have to write custom codes to enable two processes, exporting data from Front and importing data into Redshift through CSV Files. This method is suitable for users with a technical background.

Both the methods are explained below.

Methods of Connecting Front to Redshift

Two methods to connect Front to Redshift are explained below:

Method 1: Connecting Front to Redshift using Hevo

Front to Redshift: hevo banner
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Hevo provides Amazon Redshift as a Destination for loading/transferring data from any Source system, which also includes Front.

Configuring Front as a Source

To set up Front as the Source in your Pipeline in Front to Redshift Integration, follow these instructions:

  • Step 1: In the Asset Palette, choose PIPELINES.
  • Step 2: In the Pipelines List View, click + CREATE.
  • Step 3: Choose Front on the Select Source Type page.
  • Step 4: Enter the following information on the Configure your Front Source page to connect Front to Redshift:
Front to Redshift: config front as a source
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  • Pipeline Name: A unique name for your Pipeline, not exceeding 255 characters.
  • API Token: The API token that you created under your Front account in order to grant Hevo permission to read data.
  • Historical Sync Duration: The correlation of history Duration refers to the amount of time over which the previously collected data from the Source must be consumed. Default duration: 3 Months.
  • Step 5: Just hit the TEST & CONTINUE button.
  • Step 6: Configure the data ingestion and set up the Destination.

Configuring Amazon Redshift as a Destination

To set up Amazon Redshift as a destination in Hevo in Front to Redshift Integration, follow these steps:

  • Step 1: In the Asset Palette, select DESTINATIONS.
  • Step 2: In the Destinations List View, click + CREATE.
  • Step 3: Select Amazon Redshift from the Add Destination page.
  • Step 4: Set the following parameters on the Configure your Amazon Redshift Destination page:
Front to Redshift: config redshift as destination
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  • Destination Name: Give your destination a unique name.
  • Database Cluster Identifier: The IP address or DNS of the Amazon Redshift host is used as the database cluster identifier.
  • Database Port: The port on which your Amazon Redshift server listens for connections is known as the database port. 5439 is the default value.
  • Database User: In the Redshift database, a user with a non-administrative position.
  • Database Password: The user’s password.
  • Database Name: The name of the destination database into which the data will be loaded.
  • Database Schema: The Destination database schema’s name. The default setting is public.
  • Step 5: To test connectivity with the Amazon Redshift warehouse, click Test Connection.
  • Step 6: When the test is complete, select SAVE DESTINATION to connect Front to Redshift.

Check out what makes Hevo amazing:

  • Fully Managed: Hevo requires no management and maintenance as it is a fully automated platform.
  • Data Transformation: Hevo provides a simple interface to perfect, modify, and enrich the data you want to transfer.
  • Faster Insight Generation: Hevo offers near real-time data replication so you have access to real-time insight generation and faster decision making. 
  • Schema Management: Hevo can automatically detect the schema of the incoming data and map it to the destination schema.
  • Scalable Infrastructure: Hevo has in-built integrations for 100+ sources (with 40+ free sources) that can help you scale your data infrastructure as required.
  • Live Support: Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.
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Method 2: Connecting Front to Redshift using CSV

To connect Front to Redshift, you must export Front data and then import it to Amazon Redshift.

Step 1: Exporting Front data

The first step in Front to Redshift Integration is to export data from Front. It is assumed that you have signed in to Front. Front allows you to connect your workspace by using Gmail accounts. After setting your workspace, you can create shared inboxes, collaborate with your teams, add message templates and create rules in Front. 

Front Analytics contains seven dashboards for analyzing your team’s performance and increasing efficiency. You can create reports to filter specific channels, teammates, and more. Front allows you to export these reports into the csv files.

Follow the below steps to export Front report data to a csv file.

  • Step 1: Click on the three dots on the top right of the report view and select Export View Data.
Front to Redshift: step 1 export data
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  • Step 2: Select your export type in the Export field and click on Request export.
Front to Redshift: step 2 export data
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  • Step 3: At the bottom of the pop-up screen, you can see the prepared exports, which are ready to be downloaded. Click on the Download export arrow icon to save the export to your computer.
Front to Redshift: step 3 export data
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Front even allows you to export metric details to view all the conversations included in the specific metric in your report. Follow the below steps to export metric details. 

  • Step 1: Click on the metric in your report to pull up the metric details.
  • Step 2: Click on the export icon at the top list of conversations.
Front to Redshift: step 2 export metric data
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  • Step 3: Select your export type in the Export Field and then click on the Request export.
Front to Redshift: step 3 export metric data
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  • Step 4: You can see the prepared exports at the bottom of the pop-screen. Click on the Download export arrow icon to save the export.
Front to Redshift: step 4 export metric data
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Front also enables users to export data from individual charts and tables in your reports. The csv file can contain the same pre-calculated metrics you can see in the corresponding chart or table on your dashboard.

Click on the export icon at the top right of the table to download its data.

Front to Redshift: export data
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Step 2: Importing data to Amazon Redshift

The next step in Front to Redshift Integration is to import the data to Redshift. Using the COPY command, you can import data to Amazon Redshift from Amazon S3 buckets.

Amazon S3  consists of buckets that store documents such as documents, videos, photos, and more. You can have up to 100 buckets in your Amazon S3 account.

Front to Redshift: create bucket
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You can start by creating an Amazon S3 bucket to store your Front data. Follow the below steps for loading a csv file to Amazon Redshift.

  • Step 1: Please navigate to the csv file you want to import into the Amazon Redshift and load it to the Amazon S3 bucket. Zip the csv file.
  • Step 2: When the file is in the Amazon S3 bucket, you can use the COPY command to load it to the desired table.
COPY <schema-name>.<table-name> (<ordered-list-of-columns>) FROM '<manifest-file-s3-url>' 

CREDENTIALS'aws_access_key_id=<key>;aws_secret_access_key=<secret-key>' GZIP MANIFEST;

You must use the ‘csv’ keyword in the COPY command to make Amazon Redshift identify the file format in Front to Redshift Integration, as shown below.

COPY table_name (col1, col2, col3, col4)
FROM 's3://<your-bucket-name>/load/file_name.csv'
credentials 'aws_access_key_id=<Your-Access-Key-ID>;aws_secret_access_key=<Your-Secret-Access-Key>'
CSV;


COPY table_name (col1, col2, col3, col4)
FROM 's3://<your-bucket-name>/load/file_name.csv'
credentials 'aws_access_key_id=<Your-Access-Key-ID>;aws_secret_access_key=<Your-Secret-Access-Key>'
CSV
INGOREHEADER 1;

Limitations of Connecting Front to Redshift

Exporting Front data and importing it to Amazon Redshift manually seems easy, but in reality, this process does not allow users to work with real-time data. Therefore, users can use standard APIs to connect Front to Redshift. But, you need a strong technical team to work with APIs. As a result, to overcome all such issues, users can use third-party ETL tools like Hevo data, which allows seamless and autonomous integration between Front and Amazon Redshift.

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Conclusion

In this article, you learn how to connect Front to Redshift. Front allows organizations to help their teams ensure that every customer interaction is strengthened. Many organizations use Front to bring their customer data to a unified platform to analyze it using Front Analytics. However, to obtain an in-depth analysis, you can store Front data in a centralized repository like Amazon Redshift that can be used with powerful BI tools for gaining meaningful insights and better decision-making.

However, as a Developer, extracting complex data from a diverse set of data sources like Databases, CRMs, Project management Tools, Streaming Services, and Marketing Platforms to your Database can seem to be quite challenging. If you are from non-technical background or are new in the game of data warehouse and analytics, Hevo Data can help!

Visit our Website to Explore Hevo

Hevo Data will automate your data transfer process, hence allowing you to focus on other aspects of your business like Analytics, Customer Management, etc. This platform allows you to transfer data from 100+ multiple sources to Cloud-based Data Warehouses like Snowflake, Google BigQuery, Amazon Redshift, etc. It will provide you with a hassle-free experience and make your work life much easier.

Want to take Hevo for a spin? Sign Up for a 14-day free trial and experience the feature-rich Hevo suite first hand.

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Manjiri Gaikwad
Technical Content Writer, Hevo Data

Manjiri is a proficient technical writer and a data science enthusiast. She holds an M.Tech degree and leverages the knowledge acquired through that to write insightful content on AI, ML, and data engineering concepts. She enjoys breaking down the complex topics of data integration and other challenges in data engineering to help data professionals solve their everyday problems.

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