Data Science and Analytics Platform

The Data Science and Analytics Platform occupies a distinct position within the ASPIRE Precision Medicine Research Institute *Abu Dhabi. While other platforms and research themes generate data, this platform focuses on data analysis, producing metadata and preliminary conclusions. It serves as a bridge connecting all other platforms and research projects. The data across platforms and research themes are diverse, coming from various sources, types, and governed by different institutions. To integrate this data, we aim to develop a novel governance structure, ensuring collaboration amongst all data providers.


Our Objectives

Our commitment at the Data Science and Analytics Platform centers around enhancing data governance and broadening our research capabilities in the realm of precision medicine. Here are the core tenets of our approach:

establish foundational data governance for the Data Science and Analytics Platform

develop an operational model, policies, capabilities, and infrastructure

serve the APMAD themes seamlessly

provide automated analytical tools for APMAD researchers

explore innovative methodologies to address gaps in the field of precision medicine

Machine Learning & Data Analytics Architecture

Dive into our advanced architecture designed to harness the power of data analytics and machine learning. From the ingestion of raw data to the delivery of actionable business intelligence, our platform covers all aspects of modern data processing and analysis.

Blueprint of our Advanced Data Analytics & Machine Learning Architecture: From data ingestion to actionable insights, explore the comprehensive layers that drive intelligent decision-making.

Available resources

Discover the cutting-edge technology and equipment that powers APMAD's research and innovation. Our resources section provides detailed insights into our advanced hardware and systems.

DGX-1 Supercomputer
  • NVIDIA DGX: 8x NVIDIA® Tesla® V100 GPUs with 32GB memory each.
  • Available to use within the UAEU network as per request. Learn more here.
Cloud Computing

Research Infrastructure for Computing (RIC) Data Platform

  • Infrastructure Type: On-premise Cloud Computing.
  • Technologies Used: VMware virtualization software and Apache open-source Hadoop ecosystems (hdfs/Hive/Yarn/Spark).

Hardware Summary

  • Dell R740XD
    • Configuration: Intel Xeon Gold (Variants: 6226R 2.9G, 16C/32T & 6226 2.7G, 12C/24T), Memory up to 256GB, Storage up to 48TB.
    • Total Units: 8
  • Dell R440
    • Configuration: Intel Xeon Silver 4214R 2.4G, 12C/24T, 128GB Memory, 6TB Storage.
    • Total Units: 1
  • Dell R740XD GPU
    • Configuration: Intel Xeon Gold 6238R 2.2G, 28C/56T with NVIDIA Tesla V100 16G Passive GPU, 256GB Memory, 6TB Storage.
    • Total Units: 1


Platform Directors

Prof. Nazar Zaki

Platform Director, Big Data Analytics

Theme Members

Prof. Mohd Saberi Mohamad

Genetics Theme - Professor in Genetics and Genomics

Dr. Rafat Damseh

Scientific Board Member

Mr. Jaloliddin Rustamov

PhD Student

Mr. Zahiriddin Rustamov

PhD Student

Have questions?

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