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Abilis Data Rocket for Healthcare Providers

Abilis Solutions Inc.

Create data architecture to help healthcare leadership respond to crisis and increased demands.

Abilis Data Rocket, a three-month POC for healthcare institutions, proves how close you are to obtaining 360-degree institutional insights with real-time data ingestion and reporting, and predictive analysis. It will change the way you use data to make decisions. With Abilis Data Rocket: 

  • Automated dynamic ingestion framework saves time and money, delivering value and minimizing upfront and future maintenance costs.
  • Audit and Control framework simplifies data ingestion troubleshooting – saving time and money by orders of magnitude.
  • Operational zones and workflow blueprints accelerate time to implement, scaling with use and growth.
  • Predictive insights from Microsoft Azure ML are scaled to enterprise use with Abilis Data Rocket ML Integration Framework.
  • Securely scaled self-service business intelligence democratizes data for better decision making.
  • Security framework supports BI tooling that provides Authentication, SSO, User/Role administration structure, Role and Permission level mapping to Data Model, and Role and Permission Level Mapping.
  • Standardize and Master Data to classify and uniquely identify data from disparate silos, supporting unified views of key items such as customers and products.

Abilis Data Rocket couples Talend’s trusted Data Fabric with the Snowflake Data Cloud, connecting to visual analytics with Tableau or PowerBI. Streamlined connections and verified blueprints create value throughout the Data Rocket’s framework, and industry-best implementation and technical support ensure your investment is fully utilized and future-proof.

Abilis Data Rocket is the ideal solution for healthcare institutions who want to use their data to improve patient outcomes and improve their bottom lines. Contact us today for a no-cost discovery call to get started. Plans start at $30K for a three-month prototype and scales based on expected use.

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