Azure Migration for a Healthcare Tech Company 2022-23
Customer Background
The customer is a renowned healthcare technology company in the United States. Over the years, the company has provided software solutions to an array of hospitals, clinics, research centers and other medical institutions. The business provides information management services on their native tool in United States.
Business Requirement
As the business underwent significant expansion, the customer wanted to reduce the maintenance hassle and focus on core functionalities in their databases. They approached Intellinez for a secure azure migration of their legacy system data to the cloud. Subsequently, our team performed a deep system understanding before scoping out a cloud migration relevant solution.
Approach
After series of requirement gathering and solution scoping, we finalized a Refactoring Database approach for migration’ to meet the customer requirements. The following key points were identified as areas of focus
- Reduce maintenance overhead for the infrastructure
- Secure transition to cloud without impact on current processing
Following the azure migration Framework benchmark from Microsoft, we devised the roadmap to achieve the milestones. Post discussions, the below system architecture was proposed and locked to identify business outcomes.
Implementation
Diligently following the migration benchmarks from adoption framework guide and the business requirements as above, we executed the project as follows:
Strategy
- Identified multiple databases with unpredictable peaks of loads
- Plan secure transition to cloud as per expected business outcomes
Plan
- Finalized Azure SQL Elastic Pool to accommodate varying databases
- Pre-allocated a provisional database for fixed amount of resources
Ready
- Created a provisional Azure subscription and create new users
- Provided RBAC to all the users as per scoped requirement
- Created an Azure SQL server
Adopt
- 5 databases are migrated as elastic pooled databases to Azure SQL Server
- 2 databases are migrated to the same SQL Server as standalone databases
- Delegated permissions to business applications/users required to connect to the database
DocQuest enables seamless document upload, accommodating a wide array of document types, such as reports, contracts, and policies that too in various formats. Using advanced content-based search capabilities, users can ask specific questions and receive precise answers directly from uploaded documents, ensuring rapid access to accurate and contextually relevant information.
This case study delves into the challenges faced by client, the solution we provided by streamlining workflow process automation using WordPress & Woo-Commerce.
Introduction: Overview of the Project This case study entails the development of a software system to track fuel inventories for Badri Rai & Company across its multiple warehouses. The objective was to prevent fuel theft, record fuel purchases, and automate the input data related to stock transfers and purchases. The lead project engineer, solution architect,
Abstract Insurance service providers operate in a highly competitive environment wherein customers and stakeholders expect on-demand settlement of claims. Despite digitization of processes, the insurance industry is prone to delay in grievance handling and claims processing resulting into rise in frauds and a dissatisfied consumer. One of the unresolved bottlenecks here is the errors in
Customer Background The customer is a renowned healthcare technology company in the United States. Over the years, the company has provided software solutions to an array of hospitals, clinics, research centers and other medical institutions. The business provides information management services on their native tool in United States. Business Requirement As the business underwent significant
We at Intellinez employed React, a declarative, efficient, and flexible, open source javascript library for building user interface.
A multinational company wanted to benefit from using data warehouse services, advanced analytics, data mining, and reporting, by migrating from an on-premise Oracle-based platform into a scalable cloud data warehouse solution. The solution to be migrated had two terabytes-sized Oracle databases. Advanced analytics queries were in many cases timing out and underlying infrastructure had to be optimized for OLAP rather than OLTP.