Building Data Analytics Solution on AWS

Our Customer

Healthera operates a leading UK healthcare marketplace that provides patients with medicines, healthcare services and products through the largest digital platform of pharmacies and GPs, including national chains and independent providers. The company cooperates with over 1000 pharmacies and GPs and services more than 100,000 patients on a daily basis. Company’s objective is to transform the way healthcare is provided in the UK, from prescriptions to personalized clinical services.

The Obstacles They Faced

Due to dynamic growth of the business the client had a need to develop a data analytics solution which would ensure data driven decision making across their company. The integral requirement, which we were called to implement for this software, was the integration with Tableau Cloud, enterprise-grade solution on the world’s #1 analytics platform.

How We Helped

Our DevOps team developed and implemented a consistent solution’s architecture based on a scalable cloud data warehouse (AWS Redshift); and then established the integration of the whole system with the external data analytics platform (Tableau Cloud).

To accomplish these requirements and develop the solution according to the client’s needs, we came up with the following strategic decisions to implement in the project:

Using of AWS Redshift as the platform’s foundational data warehouse

Redshift is particularly designed and optimized to store and access much larger data sets than traditional write-optimized data bases. This can be up to 128 TB per node, potentially reaching petabytes of data in a cluster. Therefore, Redshift is much more efficient at loading large volumes of data less frequently.

To ensure Tableau integration we launched Windows based EC2 instances in a public subnet with Tableau Bridge desktop client. Data is uploaded into S3 bucket in JSON format from external MongoDB Atlas service. S3 bucket is used as a datasource for Redshift.

Adopting IaC (infrastructure as a code) approach to:

• automate AWS resource management
• speed up and automate cloud provisioning
• reuse code blocks in multiple infrastructures

Cloud infrastructure for this solution is launched on Terraform – an infrastructure as code tool that allows to create, update, and version Amazon Web Services infrastructure. The main reason for using IaC approach is to ensure consistent infrastructure as well as the ability to replicate it in multiple client’s environments (Dev, Stagging (UAT), Production).

AWS Data Analytics with Redshift and Tableu Cloud for Healthcare Marketplace – Architecture Diagram

Key deliverables:

• ensuring data-driven decision making for the client’s organization based on the advanced understanding of their customers behavior
• ability to explore unobvious dependencies via data visualization in the solution
• increased revenue due to precise data analysis on customer behavior and unveiling unobvious dependencies via data visualization in the solution
• improved business relationships due to understanding of the company’s performance and the analysis on how the performance can be improved
• easy to run & scalable solution for data processing and analytics without the need to set up and manage data warehouse infrastructure
• strong security compliance for the sensitive data: the comprehensive security capabilities of the solution’s database is able to satisfy the high demanding requirements of the industry and provide the needed level of data protection