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Analytics is critical to the success of your contact center. Having insight into each touchpoint of the customer experience allows you to accurately measure performance and adapt to changing business needs. You can find common metrics in the Amazon Connect console, but sometimes you need more details and custom requirements for reporting based on the unique needs of your business.
Starting today, the Amazon Connect analytics data lake is generally available. As announced in preview last year, this new feature helps eliminate the need to build and maintain complex data pipelines. Amazon Connect data lakes support zero ETL, meaning no extract, transform, or load (ETL) is required.
Let’s take a quick look at the Amazon Connect analytics data lake.
Improve your customer experience with Amazon Connect
The Amazon Connect analytics data lake helps you integrate disparate data sources, such as customer contact records and agent activity, into a single location. By keeping your data in a centralized location, you can now analyze and gain insights into your contact center performance while reducing the costs associated with implementing complex data pipelines.
The Amazon Connect analytics data lake allows you to access and analyze contact center data, such as contact tracing records and Amazon Connect contact lens data. This gives you the flexibility to prepare and analyze data with Amazon Athena and use the business intelligence (BI) tools of your choice, such as Amazon QuickSight and Tableau.
Getting started with Amazon Connect analytics data lake
To get started with your Amazon Connect analytics data lake, you first need to set up an Amazon Connect instance. You can create a new Amazon Connect instance by following the steps on the Create an Amazon Connect Instance page. Since we’ve already created an Amazon Connect instance, we’ll jump right in and show you how to get started with an Amazon Connect analytics data lake.
First, go to the Amazon Connect console and select your instance.
You can then set up your analytics data lake by going to: analysis tools and choose Add data sharing.
When a pop-up dialog box appears, you must first define the target AWS account ID. This option allows you to set up a centralized account to receive all data from Amazon Connect instances running in multiple accounts. Then below data type, you can select the type that needs to be shared with the target AWS account. To learn more about the types of data you can share in your Amazon Connect analytics data lake, see Connecting Tables to Your Analytics Data Lake.
Once complete, you can see a list of all target AWS account IDs with which all data types have been shared.
In addition to using the AWS Management Console, you can also use the AWS Command Line Interface (AWS CLI) to associate tables with your analytics data lake. Here is a sample command:
$> aws connect batch-associate-analytics-data-set --cli-input-json file:///input_batch_association.json
where input_batch_association.json A JSON file containing connection details. Here’s a sample:
{
"InstanceId": YOUR_INSTANCE_ID,
"DataSetIds": (
"<DATA_SET_ID>"
),
"TargetAccountId": YOUR_ACCOUNT_ID
}
Next, you must approve (or deny) the request in the target account’s AWS Resource Access Manager (RAM) console. RAM is a service that helps you securely share resources across AWS accounts. Navigate to AWS RAM and select it. resource sharing at Shared with me part time job.
Then select the resource and Accept resource sharing.
This step allows Amazon Connect to access the shared resource. You can now start creating linked tables from shared tables in AWS Lake Formation. From the Lake Formation console table select a page Create table.
I am Resource Link To a shared table. Then enter your details and select the available items. database and Region of shared table.
Then if you select shared tableClicking will list all available shared tables that you can access. 
When you select a shared table, it is automatically populated. Database of shared tables and Owner ID of shared table. When you are satisfied with your configuration, select Next. make.
Go to the Amazon Athena console to run queries on your data. Here is an example of the query I ran:
This configuration allows you to access specific Amazon Connect data types. You can also visualize your data by integrating with Amazon QuickSight. The following screenshot shows some visuals from an Amazon QuickSight dashboard with data from Amazon Connect.
voice of the customer
During the preview period, we’ve heard a lot of feedback from customers about the Amazon Connect analytics data lake. Here’s what our customers have to say:
Joulica is an analytics platform that powers insights into software like Amazon Connect and Salesforce. Tony McCormack, founder and CEO of Joulica, said: “Our core business is providing real-time and historical contact center analytics to Amazon Connect customers of all sizes. “In the past, we often had to set up complex data pipelines, so we’re excited to use the Amazon Connect analytics data lake to simplify the process of delivering actionable intelligence to our shared customers.”
Things you need to know
- price — The Amazon Connect analytics data lake can use up to two years of data from Amazon Connect at no additional cost. You only pay for any services you use to interact with your data.
- effectiveness — Amazon Connect analytics data lakes are generally available in the following AWS Regions: US East (N. Virginia), US West (Oregon), Africa (Cape Town), Asia Pacific (Mumbai, Seoul, Singapore, Sydney, Tokyo), and Canada. there is. (Central) and Europe (Frankfurt, London)
- Learn more — For more information, see the Analytics data lake documentation page.
happy building,
— Donny
