Latest release of Tetra Data Platform adds full-text search, filtering, and harmonized experimental data browsing features for advanced data science
TetraScience, the R&D Data Cloud company, announced that the latest release of its Tetra Data Platform (TDP) now includes full-text search and browsing features for faster and more flexible access to experimental data. These capabilities will reduce time spent on implementing queries while enabling lab and data scientists to explore search results more intuitively, apply advanced data science, and accelerate time-to-insight.
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“Life sciences R&D teams struggle with fragmented, heterogeneous lab equipment and software systems that generate massive amounts of data. Accessing disparate experimental data in these disconnected lab solutions and workflows has always been a challenge – let alone the ability to effectively query the data and enable advanced data science applications,” said Siping “Spin” Wang, TetraScience founder, president and CTO. “Global biopharma companies are continually looking to fuel innovation and gain deeper insights from their data. The ability to easily access, search, and preview data in a life sciences R&D Data Cloud will further accelerate discovery across the industry,” continued Wang.
“Our customers are accelerating discovery and gaining competitive advantage by replatforming their experimental data to the cloud,,” said Michelle Bradbury, vice president of products at TetraScience. “By providing users with more powerful and intuitive search capabilities, along with the ability to quickly browse all their harmonized data in a centralized cloud-native platform, our customers will be able to gain far greater insights and more rapidly iterate on experimental results,” continued Bradbury.
Full-text index and search capabilities, in addition to ElasticSearch, help ensure users find data points and insights that are typically easy to miss when querying RAW experimental data. Additionally, browsing and previewing data based on internally-known source file paths gives users an intuitive way to explore the Tetra Data Lake, significantly minimizing time spent searching for data. In addition to enhanced query capabilities, scientists can use their favorite data science tools with an improved data access layer.
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