HCTI’s Next Generation Data Operations for Life sciences and Healthcare
Powered by Data Engineering and Data Bots to enable Data Pipeline Creation & Management
Digital Transformation in Healthcare and Life Sciences (HCLS) requires digitizing large amounts of legacy data & processes. Moreover, the adoption of Business process automation requires complex integrations with disparate tools and solutions. This means that currently Data driven decision making is challenged by the capability of collecting and meaningfully managing Data at scale. For HCLS the added constraints of accounting for Security & Compliance controls for data protection & changing data regulations and requirements for PHI and PII level of Data must be factored in.
Managing such complex entities is cumbersome and not cost effective. HCTI has helped many healthcare and pharmaceutical companies to meet and exceed these challenges by building highly modular, scalable, secure, and compliant AI Engineering & Analytics platforms. Data Engineering and operations allows organizations to ingest, prep, curate, catalog and classify the data so the organization can gain valuable insights from their data artifacts.
Data Engineering and Operations
Organizations today require data engineering across different aspects of the data processing pipeline. Data engineering involves writing and updating code artifacts which will interact with the organization’s data like code for Data Ingestion, Data Classification, Data Quality, Data transformation, PHI detection & Redaction, Data lineage, Data provenance, Advanced Analytics, AI/ML Model Development etc. Data Engineering also needs to meet and exceed the software development best practices.
Data operations involves management of the above code artifacts. Data Operations leverage Data Engineering and next generation of data management strategies to ensure that the data pipelines are running optimally. Data Operations include monitoring data pipelines, data pipeline debugging, performance management, troubleshooting, forensics & diagnostics.
Data bots further improve the overall efficiency of the Data Engineering and Operations by introducing autonomous and event driven actions to interact with the organizations Data. These bots can act and interact with each stage in an established data pipeline. These include but not limited to:
- Quality Bots, enforces quality of data, tags and quarantines data with missing tags and fields
- ETL Bots, enforces data structure based on tags and custom driven rules for driven datasets and objects
Data Security and Compliance
We ensure that your mission critical, PHI and non-PHI Data in the cloud / On Prem are secure and continuously meet industry standard required for security and compliance regulations like HITRUST, HIPAA & GDPR.
We have comprehensive dashboards, alerts & notifications and security & compliance controls which have proven not only to meet but more importantly, exceed even the most stringent security regulations and audits around data and data access.
HITRUST certified Platforms & Operations
Continuously Compliant to meet HIPAA, GxP & GDPR regulations
Automated Compute and Environment hardening
Defense in Depth
Cloud Business Accelerators with built-in Security & Compliance Controls.
8X5 and 24X7 Operational Models
Industry leading SLAs and response times
Trained and Qualified Personnel to handle PHI & PII Data
Developing a Future-Forward Digital Strategy in Life Sciences
Data Analytics and AI in Life Sciences: Key Insights
Focus on Your Data and Meaningful Insights, Not Technology, Security, and Compliance.