One of the biggest challenges for life science and healthcare organizations is dealing with a vast array of heterogeneous sources, objects, clinical data, and real-world evidence.
Quantori has deep domain expertise that applies to widely used public and private data sources. Our data scientists are experienced in working with diverse types of data and in combining data from multiple sources to achieve optimal results.
Data science is only one part of the process — wrangling the right data points and engineering them for optimal results is what makes Quantori uniquely positioned to take on this kind of projects.
• Design a data strategy that reflects business goals and scientific needs
• Develop a data architecture blueprint and executable roadmap
• Develop approaches to building-up cloud-based solutions for managing and storing large volumes of data
• Migration from on-premises environment to Cloud, including RDBS replacement
• Complex data migration from legacy systems to a client’s new stack
• Data extraction from various sources
• Source data cleansing
• Real-time/streaming and batch data processing
• Data format conversions, transformation, and normalization
• Data standardization services, reducing data complexity
• Working with structured, semi-structured, & unstructured data
• Build complex architectures for future DWH
• Adjust existing solutions to increase scalability and performance
• Configure data pipelines to feed into Data Lakes
• Connect BI solutions
• Develop database architectures
• Database performance tuning
• OLTP systems creation
• Best practices for building business logic around/inside a database layer
• NoSQL solutions
• Provide a proven methodology for establishing data governance within the organization
• Provide solutions for data high availability and consistency
• Provide robust data security solutions/data anonymization according to requirements of regulatory authorities
• Data quality assessment
• Deriving relevant business and scientific insights from the data
• Creation of data reports and data repositories
• Optimizing the entire data analysis process
• All possible types of data analysis: searching of the common patterns for data groups comparisons, exploring outlying data points, assessing missing variables, etc.
Intelligence
• BI implementation and operation to help analyze data and provide intelligent insights that maximize operational efficiency and create a competitive advantage
• BI performance management
• Develop interactive reporting solutions
• Develop dashboards, platforms, and UX/UI services for data representation and manipulation
• Improve existing visualization solutions for clients
• Prepare client data for visualization and analytics
• Provide client with valuable insights using data visualization tools
• Enhance analytical power by providing interactive visualizations
• Streaming and real-time data visualization
• Engineer complex ML/DL pipelines that can accommodate multimodal data, including text and images
• Design and implement AI solutions
• Extract data insights using AI and ML
• Cloud-based AI/ML platform integration
• Computer vision, natural language processing, and optimization