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Data Engineering

Build efficient data pipelines and systems to collect, and analyze raw data from a variety of sources and formats.  

Our data engineering solutions will help you find practical applications for your data, suited to support your mission. 

Stages of Data Engineering

World-class solutions for each stage of the Data Engineering Process

Stage 1

Data Sources

Streaming or batched?  Structured or unstructured?  Your systems must be prepared to handle data of any scale and complexity.

Stage 2

Data Ingestion

Delivery mechanisms, formats, cadence, and volume of inbound data require thoughtful engineering.

Stage 3

Raw Data Storage

Transient and secure storage data while awaiting processing.

Stage 4

Data Validation

Received data must be checked for integrity, accuracy and structure before it is used for data processing.

Stage 5


Prior to processing, a standard must be created to transform data from different sources into a consistent, data-adhering format.

Stage 6


Standard code systems & value sets must be selected; and the data transformed to meet these standards.

Stage 7

Clean Storage

Clean data must be stored in a manner that enables analysis and preparation of data for enrichment and transformation for downstream consumption.

Stage 8

Data Enrichment

Existing information may be enriched by supplementing missing or incomplete data with internal and external sources.

Stage 9


Prior to consumption, the data will need to be converted from one format or structure into another for defined consumption purposes.

Stage 10

Curated Data

Enriched data must be partitioned, cataloged, and stored in formats enabling effective and efficient consumption based on organizational needs.

Stage 11

Data Consumption

Feed data into standardized tools used for gaining insight into the inforamtion available in the data infrastructure

Solve Key Data Challenges

Work with MedicalSuite

Work with us to build and optimize world-class data highways to support your analytics and business intelligence needs.  

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