DMZCUBE’s Ingestion process uses two approaches based on the capacity or volume, context or variety and degree of latency or velocity of the incoming data feeds:

Ingest via Batch Process:

  • Has Known / Structured Format
  • For Light Weight Transformations
  • Extracting from Relational Sources
  • Data to be loaded into pre-analysis database

Ingest via Streaming Process:

  • Unstructured / Semi-Structured Format
  • Real time Feed
  • Transformations on-the-fly
  • Distributed Real Time Computation


DMZCUBE’s approach to Health Data Integration involves vistaBI Framework that streamlines consolidation of Clinical, Financial and Operational data. The consolidated data is profiled for Quality Assurance to get qualified, run through the Rules Engine to accommodate business logic and streamed into the Repository to be consumed by the Analytics Engine for Data Exploration.

DMZCUBE utilizes following approach based on the Variety, Volume and Veracity of data ingested.

Traditional Approach

  • Heavy Lifting is executed on-the-fly
  • Works best when sources are traditional databases that have limited scalability

Contemporary Approach

  • Heavy Lifting of Transformation is pushed to the target databases to overcome transformation on-the-fly performance issues.
  • Works best for Social Feeds, Machine and Sensor data to manage data volumes in petabytes.


Once transformed, our solution unlocks the knowledge of Clinical, Financial and Operational data to gain insight and improve quality of care.

Clinical Insight:

  • Identify gaps in Care Management
  • Identify and Stratify Population Health Risk buckets

Financial Insight:

  • Evaluate Pay for Performance Metrics
  • Track Claims, Collections, Cash Flows

Operational Insight:

  • Establish benchmarking of your performance vis a vis Industry Standards
  • Reduce the Turn Around Time involved in Data Consolidation and Reporting
  • Capabilities to drill down for more accurate information regarding competitors, market shares and future prospects.

Influence Decisions

Quality decision-making depends upon the quality of information available to support decisions. Our Solutions generate the information which is used by management for making more informed decisions and can evaluate various alternatives during decision making process. We help organizations to optimize their key business processes over time. Also encourage the decision makers to innovate and increase the operational efficiencies in different ways.

  • Our Streamlined Dashboards and Drill down solutions provides management with more purposeful approach in making decisions.
  • Our Data Analytics helps in extracting and providing valuable information from large amount of data to providers and decision-makers which is extremely important for formulating strategies, plans and crucial decisions.
  • Real-time healthcare analytics and decision-making tools helps improves timeliness and efficiency of Decision Making.