BluePes Blog: Insights & Trends

BluePes Blog: Insights & Trends

Designing a Healthcare Semantic Model in Power BI: Trustworthy Dashboards, Predictable Refresh, and Privacy That Holds

Designing a Healthcare Semantic Model in Power BI: Trustworthy Dashboards, Predictable Refresh, and Privacy That Holds

Hospitals don’t need flashier visuals; they need answers they can trust at the point of care. When Power BI projects mirror source systems or bury privacy behind permissions, dashboards slow down, clinicians lose trust, and ops revert to spreadsheets. This article lays out a healthcare-first approach to Power BI: a semantic model that reflects clinical reality (encounters at the right grain, vitals/labs as events), performance patterns that survive peak hours (Incremental Refresh, Aggregations, Composite models), and safety rails on the surface (freshness, completeness, RLS, governed exports). A focused 30-day plan closes things out so you can harden one high-impact dashboard without pausing delivery.

  • 24 Oct 2025
  • 10 min
From HL7v2 to FHIR R4 with Java: Interoperable Services, Audit-by-Design, and Safer Data Flows

From HL7v2 to FHIR R4 with Java: Interoperable Services, Audit-by-Design, and Safer Data Flows

Healthcare interfaces break in predictable places: retries create duplicate encounters, partial updates corrupt charts, exports leak PHI, and a Friday mapping “hotfix” ruins Monday’s ward round. Java 21 and Spring Boot 3 give you reliable primitives - virtual threads, structured concurrency, records - but resilient clinical integration still relies on operational patterns: idempotent messaging at the HL7 boundary, strict FHIR validation, consent-aware access, and an audit trail you can actually read. This article lays out a boundary-first architecture for HL7v2 → FHIR R4 bridges, shows how to validate and map safely with HAPI FHIR, and explains privacy controls that keep you out of trouble. We close with a 30-day rollout plan and pragmatic signals to prove it works in real clinics.

  • 17 Oct 2025
  • 10 min
A Telco Data Model in Power BI: From CDRs to ARPU/Churn Dashboards Without Query Timeouts

A Telco Data Model in Power BI: From CDRs to ARPU/Churn Dashboards Without Query Timeouts

Telecom data never sits still. Calls, sessions, handovers, outages - each minute brings a new peak somewhere in the network. Dashboards that feel fine during development often stall in production because the model mirrors operational tables, filters scan months, and definitions drift between reports. This article shows how to shape a telco-ready semantic model in Power BI: CDRs and network counters at the right grain, measures the NOC trusts, and performance features that keep refresh predictable. You’ll also get lightweight governance patterns (freshness, completeness, ownership) and a 30-day rollout plan you can run alongside current work.

  • 10 Oct 2025
  • 10 min
Telco-Grade Java Microservices: Resilient Provisioning, CDR Pipelines, and Observability Under Real Load

Telco-Grade Java Microservices: Resilient Provisioning, CDR Pipelines, and Observability Under Real Load

Telecom workloads punish weak designs: cascaded timeouts during launches, duplicate activations from “harmless” retries, and CDR jobs that lag exactly when usage spikes. Java 21 LTS gives you reliable building blocks - virtual threads, structured concurrency, modern records - yet stability still depends on operational patterns: explicit state, idempotent commands, guarded dependencies, and observability tied to action. This article lays out a practical approach that holds under real traffic: how to model provisioning flows, move and rate CDRs without double-counting, measure what matters (p50/p95/p99, freshness, backlog), and roll out changes safely. A focused 30-day plan at the end shows how to harden one service without pausing delivery.

  • 03 Oct 2025
  • 10 min
Lightweight Data Governance for BI: Ownership, Lineage, and Data Contracts That Don’t Slow Delivery

Lightweight Data Governance for BI: Ownership, Lineage, and Data Contracts That Don’t Slow Delivery

Dashboards break at the worst time when definitions drift, owners are unclear, and schema changes land without warning. This article outlines a practical approach for mid-market e-commerce, retail, and manufacturing teams: write one-screen KPI definitions with named owners, surface reliability where users read, add data contracts at boundaries, and run a short change path with lineage and release notes. You’ll get concrete patterns, a 30-day rollout, and the signals that show governance is helping - not slowing - delivery.

  • 26 Sep 2025
  • 9 min
Power BI vs Amazon QuickSight (2025): Features, Pros & Cons

Power BI vs Amazon QuickSight (2025): Features, Pros & Cons

The business intelligence (BI) software market keeps expanding as companies move from static reporting to cloud-first, AI-assisted analytics. When teams shortlist platforms, Microsoft Power BI and Amazon QuickSight often lead the conversation. Both are modern and widely adopted, yet they differ in ecosystems, pricing models, and where they shine. This article clarifies what each tool is, how it works, when to choose it, and compares features, scalability, and cost patterns ' so you can pick the right fit in 2025.

  • 19 Sep 2025
  • 10 min
Operational BI in 30 Days: Alerts, Write-Back, and What-If that Close the Loop

Operational BI in 30 Days: Alerts, Write-Back, and What-If that Close the Loop

Dashboards surface problems; businesses win when those problems turn into actions fast. This article shows how mid-market e-commerce, retail, and manufacturing teams can add alerting, safe write-back, and simple what-if to close the loop directly in BI. You’ll get a concrete 30-day plan, implementation patterns, and the signals that prove decisions land on time.

  • 10 Sep 2025
  • 10 min
Designing BI for Speed: Modeling Patterns that Cut Query Time by 30–60%

Designing BI for Speed: Modeling Patterns that Cut Query Time by 30–60%

Slow dashboards aren’t inevitable. Most delays come from a handful of fixable choices in modeling and SQL. This article outlines a practical approach for mid-market teams in e-commerce, retail, and manufacturing: shape the data for analysis, pre-compute what’s heavy, and keep queries friendly to the engine. You’ll find concrete patterns, a 30-day plan, and simple signals to track whether performance is actually improving.

  • 01 Sep 2025
  • 9 min

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