Innovations – Case Study
Healthcare Provider Improves
Data Services With the Right
Prescription From Daman
Developing a cost-efficient, agile and innovative solution
The Challenge
Developing a Cost-efficient, Agile, and Innovative Solution
The business world is moving to the cloud and that includes analytical platforms.
Recently, a leading healthcare providers’ IT Team developed an enhanced shared-services cloud platform to support the company’s many lines of business serve their analytical needs. Unfortunately, many of the business units’ experience with the company’s shared services Azure environment was less than optimal. They found the development of their analytical solutions to be cumbersome, time-intensive, and not worth the added cost as compared to other, commercially available solutions. As a result, the company’s shared services organization was steadily losing its existing customers and was in jeopardy of getting shut down.
The IT team hired Daman to assess the situation and develop a strategic approach to improving their shared services offering and customer experience.
How Daman Helped
Charting a Pathway
To provide a context for this strategic pathway, Daman professionals measured the company’s analytical maturity against standard industry benchmarks. This assessment suggested significant room for improvement in the following areas:
Agility: The speed at which a business could build new solutions with the existing offering.
Platform governance: How efficiently the platform services were provisioned and used.
Use-case flexibility: The analytical patterns supported by the platform
Self-service analytics: The flexibility in direct data inquiries
Time and cost to deliver: The availability of accelerators to reduce solution delivery timelines
In short, the businesses needed more than basic infrastructure, reporting and IT support. They needed an advanced and service-rich analytical platform so they could be more competitive and drive growth with the latest advances in cost-efficient, agile, and innovative data management.
Based on this assessment, Daman developed a detailed roadmap with 6, 9 and 12 month milestones, outlining the changes needed to reach successively higher levels of analytical platform maturity.
The Daman plan would help the shared services organization evolve from simply supporting Infrastructure as a Service (IaaS) and Software as a Service (SaaS) platform to delivering a mature Solution as a Service (SolaaS) offering.
Keeping in mind both short-term needs and long-term objectives, Daman provided a number of recommendations beginning with an innovative Data Ingestion Framework. Daman recommended using Spark on ADB and extending the capabilities of the current ingestion process to support additional data formats and data latency (real time and batch). Other innovative suggestions included Data Management Accelerators for improved data engineering agility and automated CI/CD capabilities to support agile releases.
To improve the acquisition rate of new businesses and increase stickiness in existing businesses, Daman recommended both SQL Data Warehouse (DW) and SQL Database (DB) as options, depending on the use case. Daman also suggested using Azure Cost Management, Cloudyn and best practices for a leaner, more tightly managed SaaS.
To help restore reusability and improve reliability with data lakes, Daman proposed Delta Lake, an open source transactional storage layer that runs on top of any existing file storage. Finally, Daman stressed the importance of being able to spin up sandboxes with SQL DB, Delta Lake workspaces, and ADF (or ADB) for tactical solutions or proof of concepts.
The Results
Key Recommendations
Based on these recommendations and the work done by Daman, the company was well-positioned to begin the next stage in their journey toward analytical platform maturity, helping to support their lines of businesses and the overall success of the shared services offering. The shared services team has reported
- Improved performance of the infrastructure resulting in a reduction of computing costs
- Introduction of new service offering around ML capabilities resulting in the acquisition of a new business unit
- More flexibility to tenant infrastructure landscape allowing customers and pick and choose service offerings
- Faster solution delivery times due to improved data ingestion capabilities and redefined CI/CD processes.
The platform continues to mature and the future looks bright for the shared services team.
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