Healthcare Benefits
One platform, six systems, and a quarterly report that runs itself.
Our client, a healthcare benefits company, had data spread across transactional systems, definitions buried in 487 report workbooks, and a contractually required quarterly report running on deprecated technology its author no longer maintained. We built a Microsoft Fabric data warehouse and lakehouse that unified it all, then automated the work on top of it.
72 to under 5
Quarterly report, staff hours
6 weeks to 45 min
Ad hoc analysis
Under 6 months
Full implementation
10/10
Client rating
The challenge
Data lived everywhere and agreed nowhere. SQL Server, Salesforce, NetSuite, and files from outside partners each held a piece of the truth. Teams pulled data by hand and shaped it in Excel. Business definitions were embedded in code across 487 individual Tableau workbooks, so identical questions produced different answers depending on which report you opened.
The operational risks were bigger than the inconvenience. Critical processes depended on individual people and undocumented steps. Storage costs kept climbing because transactional systems had no place to offload history. And the quarterly customer report, owed to every customer by contract, ran on deprecated technology that nobody remaining at the company understood.
Why Digital2DNA
Eight firms competed for the work. Most arrived with the answer already chosen. We arrived with questions, ran a technology-agnostic discovery across every affected team, and facilitated working sessions with the product vendors so the client reached the recommendation with us rather than receiving it from us. The security audit inside that discovery covered HITRUST, SOC 2, HIPAA, and protected health information (PHI) handling before a single pipeline was built.
You were the only one in the pile of eight that wasn't trying to talk about solutioning upfront. Everyone else had done Databricks a million times, or came in saying "I've got a Snowflake, this is what we're going to do." You were actually asking, what's the problem?
What we delivered
A governed Microsoft Fabric platform with development, UAT, and production environments, source control for every change, and connections to an on-premises SQL Server, Salesforce, two NetSuite environments, Amazon S3, Azure Blob storage, network file shares, and Exchange mailboxes. Raw data lands in a bronze layer, then flows into a normalized master database that preserves change history, so any query can run against today or any point in the past.
On that foundation we automated the work itself. The quarterly customer report pipeline ingests NetSuite data, applies the business logic, calls the Power BI API, and delivers a customized deck for every customer with no human in the loop. A fuzzy matching capability reconciles free-text drug names against claims at a 95 percent confidence threshold. An automated audit of invoice folders against the accounts receivable mailbox is rolling out now, and a daily validation run hands the operations team a worklist of records in an invalid state before they become customer-facing errors.
The results
Quarterly reporting went from 72 hours of staff time to under 5 hours, fully automated, with some cycles closer to 3. The step that processes raw data covers every customer, every quarter, back to the beginning of the company's history, in about six minutes. The automation shipped in two months against a three-month timeline. An executive request that previously took the analytics team four to six weeks was answered in 45 minutes. Invoice auditing is moving from a small manual sample to complete coverage, surfacing revenue that used to appear months late or not at all.
The platform holds three terabytes and runs on reserved capacity for about $2,500 a month. When priorities shifted mid-project and call center data became urgent, the team pivoted without stalling the roadmap. The full implementation took under six months.
In Jac's words
Digital2DNA comes equipped with solid HIPAA, PHI, and security capabilities just as a base. There was no need to teach them healthcare. They already understood HITRUST, SOC 2, all of it, and it was vetted during discovery. I never worried about it once during the project.
I sometimes have to remember, oh yeah, you're a third party. We come through as such a gelled team that I forget.
Her recommendation score: 10 out of 10.
Have data that doesn't agree with itself?
You'll see working results within the first two weeks, then every week after.