How to load data from Freshcaller to Kafka

Learn how to use Airbyte to synchronize your Freshcaller data into Kafka within minutes.

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Set up a Freshcaller connector in Airbyte

Connect to Freshcaller or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up Kafka for your extracted Freshcaller data

Select Kafka where you want to import data from your Freshcaller source to. You can also choose other cloud data warehouses, databases, data lakes, vector databases, or any other supported Airbyte destinations.

Configure the Freshcaller to Kafka in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.

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TL;DR

set up Freshcaller as a source connector (using Auth, or usually an API key)
set up Kafka as a destination connector
define which data you want to transfer and how frequently

You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

This tutorial’s purpose is to show you how.

What is Freshcaller

Setup a connection to your Freshcaller site in minutes, and select the Freshcaller collections you want to replicate.

What is Kafka

A communication solutions agency, Kafka is a cloud-based / on-prem distributed system offering social media services, public relations, and events. For event streaming, three main functionalities are available: the ability to (1) subscribe to (read) and publish (write) streams of events, (2) store streams of events indefinitely, durably, and reliably, and (3) process streams of events in either real-time or retrospectively. Kafka offers these capabilities in a secure, highly scalable, and elastic manner.

Integrate Freshcaller with Kafka in minutes

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Prerequisites

A Freshcaller account to transfer your customer data automatically from.
A Kafka account.
An active Airbyte Cloud account, or you can also choose to use Airbyte Open Source locally. You can follow the instructions to set up Airbyte on your system using docker-compose.

Airbyte is an open-source data integration platform that consolidates and streamlines the process of extracting and loading data from multiple data sources to data warehouses. It offers pre-built connectors, including Freshcaller and Kafka, for seamless data migration.

When using Airbyte to move data from Freshcaller to Kafka, it extracts data from Freshcaller using the source connector, converts it into a format Kafka can ingest using the provided schema, and then loads it into Kafka via the destination connector. This allows businesses to leverage their Freshcaller data for advanced analytics and insights within Kafka, simplifying the ETL process and saving significant time and resources.

Step 1: Set up Freshcaller as a source connector

1. Open the Airbyte dashboard and click on "Sources" from the left-hand menu.
2. Click on the "Create a new source" button and select "Freshcaller" from the list of available connectors.
3. Enter a name for your Freshcaller source and click on "Next".
4. Enter your Freshcaller API credentials, including the API key and domain name.
5. Click on "Test connection" to ensure that the credentials are correct and the connection is successful.
6. Select the data you want to replicate from Freshcaller, including calls, agents, and call recordings.
7. Choose the replication frequency and the destination where you want to store the data.
8. Click on "Create source" to save your Freshcaller source connector on Airbyte.
9. You can now monitor the replication status and view the data in your destination of choice.

Note: It is important to ensure that your Freshcaller API credentials are correct and have the necessary permissions to access the data you want to replicate. Refer to the Freshcaller API documentation for more information on how to generate API keys and manage permissions.

Step 2: Set up Kafka as a destination connector

1. First, you need to have an Apache Kafka destination connector installed on your system. If you don't have it, you can download it from the Apache Kafka website.
2. Once you have the Apache Kafka destination connector installed, you need to create a new connection in Airbyte. To do this, go to the Connections tab and click on the "New Connection" button. 3. In the "New Connection" window, select "Apache Kafka" as the destination connector and enter the required connection details, such as the Kafka broker URL, topic name, and authentication credentials.
4. After entering the connection details, click on the "Test Connection" button to ensure that the connection is working properly.
5. If the connection test is successful, click on the "Save" button to save the connection.
6. Once the connection is saved, you can create a new pipeline in Airbyte and select the Apache Kafka destination connector as the destination for your data.
7. In the pipeline configuration, select the connection you created in step 3 as the destination connection.
8. Configure the pipeline to map the source data to the appropriate Kafka topic and fields.
9. Once the pipeline is configured, you can run it to start sending data to your Apache Kafka destination.

Step 3: Set up a connection to sync your Freshcaller data to Kafka

Once you've successfully connected Freshcaller as a data source and Kafka as a destination in Airbyte, you can set up a data pipeline between them with the following steps:

Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
Choose your source: Select Freshcaller from the dropdown list of your configured sources.
Select your destination: Choose Kafka from the dropdown list of your configured destinations.
Configure your sync: Define the frequency of your data syncs based on your business needs. Airbyte allows both manual and automatic scheduling for your data refreshes.
Select the data to sync: Choose the specific Freshcaller objects you want to import data from towards Kafka. You can sync all data or select specific tables and fields.
Select the sync mode for your streams: Choose between full refreshes or incremental syncs (with deduplication if you want), and this for all streams or at the stream level. Incremental is only available for streams that have a primary cursor.
Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from Freshcaller to Kafka according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your Kafka data warehouse is always up-to-date with your Freshcaller data.

Use Cases to transfer your Freshcaller data to Kafka

Integrating data from Freshcaller to Kafka provides several benefits. Here are a few use cases:

Advanced Analytics: Kafka’s powerful data processing capabilities enable you to perform complex queries and data analysis on your Freshcaller data, extracting insights that wouldn't be possible within Freshcaller alone.
Data Consolidation: If you're using multiple other sources along with Freshcaller, syncing to Kafka allows you to centralize your data for a holistic view of your operations, and to set up a change data capture process so you never have any discrepancies in your data again.
Historical Data Analysis: Freshcaller has limits on historical data. Syncing data to Kafka allows for long-term data retention and analysis of historical trends over time.
Data Security and Compliance: Kafka provides robust data security features. Syncing Freshcaller data to Kafka ensures your data is secured and allows for advanced data governance and compliance management.
Scalability: Kafka can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding Freshcaller data.
Data Science and Machine Learning: By having Freshcaller data in Kafka, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
Reporting and Visualization: While Freshcaller provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to Kafka, providing more advanced business intelligence options. If you have a Freshcaller table that needs to be converted to a Kafka table, Airbyte can do that automatically.

Wrapping Up

To summarize, this tutorial has shown you how to:

Configure a Freshcaller account as an Airbyte data source connector.
Configure Kafka as a data destination connector.
Create an Airbyte data pipeline that will automatically be moving data directly from Freshcaller to Kafka after you set a schedule

With Airbyte, creating data pipelines take minutes, and the data integration possibilities are endless. Airbyte supports the largest catalog of API tools, databases, and files, among other sources. Airbyte's connectors are open-source, so you can add any custom objects to the connector, or even build a new connector from scratch without any local dev environment or any data engineer within 10 minutes with the no-code connector builder.

We look forward to seeing you make use of it! We invite you to join the conversation on our community Slack Channel, or sign up for our newsletter. You should also check out other Airbyte tutorials, and Airbyte’s content hub!

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How to Sync Freshcaller to Kafka Manually

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FAQs

What is ETL?

ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.

What is Freshcaller?

Setup a connection to your Freshcaller site in minutes, and select the Freshcaller collections you want to replicate.

What data can you extract from Freshcaller?

Freshcaller's API provides access to a wide range of data related to call center operations. The following are the categories of data that can be accessed through Freshcaller's API:

1. Call data: This includes information about incoming and outgoing calls, call duration, call recordings, and call transcripts.
2. Agent data: This includes information about agents, such as their availability, status, and performance metrics.
3. Queue data: This includes information about call queues, such as the number of calls waiting, the average wait time, and the number of agents available.
4. IVR data: This includes information about Interactive Voice Response (IVR) systems, such as the number of calls handled by the IVR, the number of calls transferred to agents, and the success rate of the IVR.
5. Ticket data: This includes information about tickets created from calls, such as the status of the ticket, the agent assigned to the ticket, and the resolution time.
6. Analytics data: This includes information about call center performance metrics, such as call volume, call abandonment rate, and average handle time.

Overall, Freshcaller's API provides a comprehensive set of data that can be used to monitor and optimize call center operations.

How do I transfer data from Freshcaller?

This can be done by building a data pipeline manually, usually a Python script (you can leverage a tool as Apache Airflow for this). This process can take more than a full week of development. Or it can be done in minutes on Airbyte in three easy steps:
1. Set up Freshcaller to Kafka as a source connector (using Auth, or usually an API key)
2. Choose a destination (more than 50 available destination databases, data warehouses or lakes) to sync data too and set it up as a destination connector
3. Define which data you want to transfer from Freshcaller to Kafka and how frequently
You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

What is ELT?

ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.

Difference between ETL and ELT?

ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.

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How to load data from Freshcaller to Kafka

Learn how to use Airbyte to synchronize your Freshcaller data into Kafka within minutes.

Try Airbyte Cloud free

Deploy Airbyte Open Source

Step 1: Setup Freshcaller

Step 2: Setup Kafka

Step 3: Setup a connection Use Cases Wrapping Up

Example H2

Example H3

Sync data between Freshcaller and Kafka

Get your data syncing in minutes

Try Airbyte free

TL;DR

set up Freshcaller as a source connector (using Auth, or usually an API key)
set up Kafka as a destination connector
define which data you want to transfer and how frequently

You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

This tutorial’s purpose is to show you how.

What is Freshcaller

Setup a connection to your Freshcaller site in minutes, and select the Freshcaller collections you want to replicate.

What is Kafka

Integrate Freshcaller with Kafka in minutes

Try for free now

Prerequisites

A Freshcaller account to transfer your customer data automatically from.
A Kafka account.
An active Airbyte Cloud account, or you can also choose to use Airbyte Open Source locally. You can follow the instructions to set up Airbyte on your system using docker-compose.

Step 1: Set up Freshcaller as a source connector

Step 2: Set up Kafka as a destination connector

Step 3: Set up a connection to sync your Freshcaller data to Kafka

Once you've successfully connected Freshcaller as a data source and Kafka as a destination in Airbyte, you can set up a data pipeline between them with the following steps:

Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
Choose your source: Select Freshcaller from the dropdown list of your configured sources.
Select your destination: Choose Kafka from the dropdown list of your configured destinations.
Configure your sync: Define the frequency of your data syncs based on your business needs. Airbyte allows both manual and automatic scheduling for your data refreshes.
Select the data to sync: Choose the specific Freshcaller objects you want to import data from towards Kafka. You can sync all data or select specific tables and fields.
Select the sync mode for your streams: Choose between full refreshes or incremental syncs (with deduplication if you want), and this for all streams or at the stream level. Incremental is only available for streams that have a primary cursor.
Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from Freshcaller to Kafka according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your Kafka data warehouse is always up-to-date with your Freshcaller data.

Use Cases to transfer your Freshcaller data to Kafka

Integrating data from Freshcaller to Kafka provides several benefits. Here are a few use cases:

Advanced Analytics: Kafka’s powerful data processing capabilities enable you to perform complex queries and data analysis on your Freshcaller data, extracting insights that wouldn't be possible within Freshcaller alone.
Data Consolidation: If you're using multiple other sources along with Freshcaller, syncing to Kafka allows you to centralize your data for a holistic view of your operations, and to set up a change data capture process so you never have any discrepancies in your data again.
Historical Data Analysis: Freshcaller has limits on historical data. Syncing data to Kafka allows for long-term data retention and analysis of historical trends over time.
Data Security and Compliance: Kafka provides robust data security features. Syncing Freshcaller data to Kafka ensures your data is secured and allows for advanced data governance and compliance management.
Scalability: Kafka can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding Freshcaller data.
Data Science and Machine Learning: By having Freshcaller data in Kafka, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
Reporting and Visualization: While Freshcaller provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to Kafka, providing more advanced business intelligence options. If you have a Freshcaller table that needs to be converted to a Kafka table, Airbyte can do that automatically.