Qlik Cloud and Qlik Sense Client-Managed share the same analytics engine, but they diverge significantly in features, flexibility, and total cost of ownership. Here is what you need to know before choosing.

Qlik is your single source of truth, but your teams want to work in Excel, Power BI, Tableau, and SAS. The inProcess ODBC Driver lets them. Same data, same business logic, any tool.

A fully managed clinical data warehouse that automatically builds data pipelines from EMR sources, publishes over 100 analytics applications, and delivers a single source of truth for clinical, operational, and financial teams, up and running in days.

Contact tracing is only one piece of the puzzle. Schools and districts that build comprehensive, data-driven campus health systems that are automated, integrated, and HIPAA/FERPA compliant are better positioned to stay open, reduce spread, and protect their communities.

IoT generates enormous volumes of data, but without the right pipeline architecture, that data never becomes insight. Four key concepts, built on AWS, give organizations the foundation to move faster, spend less, and make better decisions in real time.

The decisions you make early in building your clinical research platform have long-term consequences for speed, compliance, and publication quality. Here is what to prioritize before you commit.

Underestimate demand in the ED or OR and patient wait times climb. Overestimate it and costs spike from wasted supplies and underutilized staff. Getting it right requires real-time, data-driven insight, not gut instinct.

Rising costs, longer revenue cycles, and increasing claims complexity are squeezing healthcare providers. Data integration and predictive analytics give revenue cycle teams the visibility to stay ahead and the tools to act.

Hospital performance, patient safety, and quality of care depend on the right data reaching the right people at the right time. Analytics built for clinical and operational leaders turns complex inpatient and outpatient data into decisions that reduce harm and improve outcomes.

Federal price transparency requirements now force payors and providers to publish negotiated rates publicly. Health systems that know how to analyze this data gain a significant edge in contracting, benchmarking, and revenue strategy.

Artificial intelligence is transforming healthcare—from clinical decision support to operational efficiency and patient outcomes. But realizing AI's promise requires more than algorithms; it depends on data quality, governance, and thoughtful implementation.

Language-centric analytics represents a fundamental shift in how people interact with data. Instead of navigating dashboards, filters, and charts, users can ask questions in natural language and receive contextual, explainable answers. Platforms like Qlik are pushing analytics toward more human-centered experiences—expanding access to insight while challenging organizations to rethink governance, trust, and adoption.

Language-centric analytics is reshaping how users interact with data. Moving from dashboards and filters to natural language, generative insights, and AI-assisted discovery. Qlik's upcoming enhancements signal a shift toward more intuitive, conversational analytics experiences that expand access without sacrificing governance.

As machine learning becomes more embedded in business decision-making, understanding why a model produces a specific result is just as important as the result itself. SHAP values provide a powerful framework for explaining model behavior—helping organizations build trust, validate outcomes, and meet growing transparency expectations.

Healthcare organizations face rising data complexity and increasing regulatory oversight. As electronic medical records (EMRs) move to the cloud, data must be accurate, accessible, and governed to support compliance, operational performance, and better patient care.