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IT Person

IT and Enterprise Systems Experts

Support organizational growth with vendor-agnostic SciY Suite of solutions


Data Integration
SciY automates data ingestion and normalization, reducing manual effort and errors
Data Preservation
SciY provides robust data management tools that handle data from ingestion to long-term storage, ensuring data integrity and accessibility
Data Reutilization
SciY’s digitalization Data Platform automatically ingests data and converts it into standardized, human- and machine-readable formats for easy exploitation
Security & Compliance
State-of-the-art cloud environment and quality system, designed with cybersecurity and the principles of data integrity and 21CFPR part 11 in mind

Bringing data centralization and standardization with security and compliance

Organization actively embracing digitalization are facing major challenges such as i) the disparity of data sources and format; ii) managing large volumes of data while ensuring quality and consistency; iii) scalability of data infrastructures and iv) making data readily available for analysis and decision making, while ensuring security and compliance. SciY suite of digitalization solutions helps organizations, and their IT departments overcome these challengers, enhancing their ability to manage data, streamline process and support organization growth and drive innovation.

Benefits

  • Data Centralization and Standardization: SciY’s Data Platform automates the process of capturing and centralizing data across an organization, ensuring it is Findable, Accessible, Interoperable, and Reusable (FAIR). This reduces the complexity of managing disparate data sources and improves data quality
  • Seamless Integration: SciY provides seamless connectivity between different systems, such as ELN and LIMS. This integration eliminates the need for manual data assimilation and reduces disruptions, making it easier to manage and access their data
  • Enhanced Data Security and Compliance: SciY's solutions include robust security measures, customizable retention policies, and reliable disaster recovery options. This ensures that data is securely backed up and compliant with industry standards, such as GLP and GMP
  • Advanced Analytics: The platform supports advanced analytics and AI-driven insights, enabling harnessing data for informed decision-making. This can lead to improved operational efficiency and innovation
  • Scalability and Flexibility: SciY's solutions are designed to be scalable, allowing them to grow with the organization. This flexibility ensures that the technology infrastructure can adapt to changing business needs and support long-term growth
  • Improved Workflow Efficiency: By automating routine tasks and streamlining workflows, SciY helps optimize processes and reduce manual intervention. This leads to increased productivity and allows IT teams and scientist to focus on strategic initiatives
  • Vendor-Agnostic Platform: SciY's platform is vendor-agnostic, meaning it can integrate with various existing systems and tools. This provides flexibility and ease of adoption, making it easier for IT specialists to implement and manage the platform

At the core of SciY Digitalization Suite, there is the Data Platform, integrating data from various scientific sources, including R&D, analytical chemistry, bioassay, enterprise systems, and robotics.

Manual data integration is time-consuming and error-prone, but SciY automates this process using data harvesters and parsers, currently handling 700 sources and expected to exceed 800 by year-end. Once ingested, data is standardized into human and machine-readable formats, making it ready for exploitation by data consumers such as experiment planning tools, ML/AI systems, and visualization dashboards. The application hub, through a set of APIs, ensures all data in the repository is accessible for further analysis, learning, and visualization, thereby enhancing knowledge and accelerating research, development, and market readiness.

Articles


Getting Data Ready for AI: Preparing Your Data for Machine Learning


The Importance of Data Centricity in Achieving a Successful Digital Transformation for Modern Laboratories


Unlocking the Power of Scientific Data: A Data Scientist’s Perspective

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