Data Harvesters

Capturing, ingesting, understanding and enriching data from data sources and data producers across your organization

Vendor-Neutral
Data Conversion

SciY’s harvesters and parsers extract files from various data sources and convert them into a vendor-neutral format, making data accessible and usable during its entire life cycle

> 700, > 100 / year

Over 700 parsers/harvesters and increasing by more than 100 a year, capturing and managing data from all connected sources

Metadata
Enrichmen

The system enriches metadata, providing a deeper understanding of the data and making it easier to manage and analyze, now and in the future

Semantic Database
Integration

By storing data in a semantic database, the need for extensive ETL (Extract, Transform, Load) processes is eliminated, allowing users to access and analyze data directly

Optimizing Organizations Data Management and Analytics Capabilities

The industry and scientific community are currently generating tons of data every second in hundreds, if not thousands, of different formats. While efforts are being made to gather and reutilize this data, non-automated or semi-automated data capture processes are still in use, which are unreliable and pose the risk of losing valuable information.

SciY’s Data Platform ingests, normalizes, and manages data from all possible sources, from simple instruments to those producing data larger than 1 TB per file, and from enterprise experiment design to experiment execution systems. Once data is in the SciY platform, it can be fully utilized, being both AI-ready and automation-ready.

Features

Over 700 data parsers/harvesters, growing by > 100 per year
Automatically capture and manage data from all connected sources
Extracting ALL extractable information from the relevant data entity
Store the data in its original format (primary data)
Enrich with all the available metadata
Convert the data to a vendor neutral format to simplify connectivity across the organization

GET IN TOUCH

SciY’s digitalization Data Platform, capturing, storing and converting data from laboratory instrumentation and from other enterprise informatics platforms

Articles

Empowering Discovery Through Scientific Data: A Data Scientist's View

Digitizing Analytical Techniques: Integrating for the Automation Era

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

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