Analysis-Ready Data

Accelerate Scientific Discovery and Drive Outcomes.

Taking scattered, complex, and varied R&D data and giving it new life as a value-generating engine.

Scientific Data is Different

Scientific innovation starts with data, and research labs are sitting on an untapped goldmine. Data need to be in the hands of scientists to allow for rapid iteration and discovery. However R&D data is different, making unlocking its value difficult.

In R&D, working with data is much more labor-intensive than other parts of the business because the data are complex, multimodal, and from many different sources. Scientific data includes images, time series, tables, machine-generated binary files, electronic lab notes, and more. It is continuously being generated in the laboratory by instrument machines that are used in experiments. Scientists run computational workflows that process raw data and generate new data. Some data is under management and some is not. Before performing any analysis, the right pieces of data need to be curated in one place.

Enthought | Scientific R&D
Enthought | Scientific Data

What is Analysis-Ready Data?

Analysis-ready data is highly curated and highly available data that support specific analytical use cases. Starting with analysis-ready data accelerates the users by significantly reducing the time that they otherwise had to spend on preparing data for analysis. 

In labs lacking the technical infrastructure to readily make their data analysis-ready, scientists and engineers are unnecessarily burdened with spending too much time wrangling their data instead of using it. They spend the majority of their time on trying to access data that are locked in data warehouses, data lakes, or other data management systems; setting up their computational environment; waiting for computing resources to be approved or become available; and figuring out how to share their work with colleagues for feedback or get into production.

Data Tools Purpose-Built for Scientific Research

Many science-driven companies focus purely on the organizational structure of their R&D data. Most find however that data stored and newly organized does not mean it’s more usable to accomplish their research goals. Enthought helps companies leverage that data with advanced analytics solutions tailored to meet the needs of the scientists and the lab. 

Enthought solutions have saved scientists up to 80% of their time by automating data compilation, accelerating data analysis by 10x, and optimizing workflows to achieve a 3x ROI within 2 years.

Contact us to learn how your scientists can take control of their data and accelerate their research.

Enthought | Scientific R&D

Unlock the Value of R&D Data with the Enthought Edge Platform

While the value of R&D data is clear, finding a way to sort through it can be daunting given the special handling required to extract its value. In fact, 75 percent of surveyed R&D executives believe advanced analytics techniques would play a pivotal role in their future R&D activities, but only 25 percent state that their R&D organizations were actually using these analytics.

General-purpose data management solutions are ill-equipped to confront the challenges of R&D data, leaving researchers to manage time-intensive and/or manual processes that may or may not yield results. That’s where Enthought Edge steps in.


Have a question? Check out our Knowledge Base for FAQs, announcements and more resources.


The Enthought Tool Suite is a collection of open-source components developed by Enthought, our partners and the scientific Python community, which we use every day to construct custom scientific applications.

What Materials Informatics Looks Like in the Modern R&D Lab

The Modern Materials Science and Chemistry Lab Industry success now more than ever is being dictated by the ability to continuously develop innovative new materials…

Read More

Cheat Sheet | Large Language Models+ For Scientific Research

Large Language Models+ For Scientific Research Updated August 2023 LLMs and Tools for R&D To help scientists and researchers navigate the increasing number of advanced…

Read More

WEBINAR: What Every R&D Leader Needs to Know About ChatGPT and LLMs

View Webinar-on-Demand Live webinar held on June 27, 2023 Overview ChatGPT and the explosion of advanced Large Language Models (LLMs) are disrupting every industry. We…

Read More

WEBINAR: Drug Development in the AI-Driven Lab

October 24, 2023 Overview The recent advancements in artificial intelligence (AI) and large language models have unleashed a new era of possibilities for drug development….

Read More

WEBINAR: Materials Informatics for Product Development: Deliver Big with Small Data

May 17, 2023 Overview For many industry labs, scientific data has historically been generated to answer specific, immediate research questions and then archived to protect…

Read More

Unlocking the Value of High Throughput Screening Pipelines in Small Molecule Drug Discovery

Transforming High Throughput Screening Data into Actionable Insights with Data Modeling and Visualization A mid-size small molecule cancer therapeutics biotechnology company using a custom high…

Read More

Why Top Materials Company Idemitsu Partnered with Enthought to Accelerate Product Innovation using Materials Informatics

Idemitsu’s Path to R&D Digital Transformation Idemitsu has a rich 100 year history of developing products alongside leading OEMs from project onset, and today is…

Read More

[eBook] Digital Transformation in the Life Sciences Industry

The Lab of the Future: Barriers to Digital Transformation in the Life Sciences Industry Experts predict over the next two years, life sciences companies will…

Read More

[eBook] Digital Transformation in the Materials Science Industry

Building the Materials and Chemicals Lab of the Future Materials and chemical companies know that building a digital “lab of the future” to accelerate discovery…

Read More

5 Tips to Kickstart Your Journey to the Future-Proofed R&D Lab

5 Tips to Kickstart Your Journey to the Future-Proofed R&D Lab   Despite an increase in digital transformation efforts across all industries, 70% fall short…

Read More

Alexandre Chabot-Leclerc

Vice President, Digital Transformation Solutions

Mark Dickinson

Principal Engineer, Software Architecture

Sandhya Govindraraju

Senior Scientific Software Developer

Kuya Takami

Senior DTX Services Consultant and Instructor