DATA SCIENCE: STATISTICAL AND COMPUTATIONAL METHODOLOGY FOR NASA'S BIG DATA IN SCIENCE

June 21, 2016

Big Data and High Performance Computing deeply permeates NASA’s Earth and space science endeavor. However, NASA science is not institutionally well-integrated with the large community of scholars and experts who develop the methodologies underlying modern Data Science: computer scientists, information technologists, applied mathematicians and statisticians. Technology transfer from and collaboration with these scholarly communities is insufficient to meet NASA’s needs, both within NASA centers and in the wider U.S. space science research community. This White Paper details some of these issues and recommends actions to improve methodologies used for current and future missions across all science domains. Examples include: compressed sensing for image and signal processing; Deep Learning neural networks for pattern recognition and classification; Virtual Reality visual exploration tools; and agile software development and other strategies from computer engineering.

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OTHER WHITEPAPERS
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Analytical Data Infrastructure MarketStudy (Excerpt)

whitePaper | June 23, 2021

Analytical data infrastructure (ADI) platforms underpin key analytics models via processes like data integration, preparation, management, and storage. But with complex cloud architectures, as-a-service offerings, and innovative new analytics and process developments, how can the discerning expert choose the right ADI offerings for their business?

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Enterprise Data Orchestration

whitePaper | June 3, 2021

Data growth continues at an exponential rate even as cloud architectures make data management more complex and advanced applications necessitate more data movement. So what can be done to enable clean data capture and movement across an enterprise? Read this white paper to learn the requirements for data orchestration at scale and discover how you can build a holistic data architecture that enables successful DataOps.

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Drive Analytic Innovation Through SAS and Open Source Integration

whitePaper | May 27, 2021

In many organizations, we need more collaboration between businesses, analytic teams, application developers and IT operations. These teams often work with data in silos and end up duplicating efforts, failing to integrate, or missing opportunities to deliver value from data. In addition to siloed efforts, data scientists are also faced with ever-increasing volumes and speeds of data. And the reality is they’re expected to answer questions just as fast as - or faster than - before. It’s important that we’re using the right data and the right techniques to ensure optimal outcomes. Download this guide to learn more about SAS and open source.

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Accelerating Data Modernization with Azure

whitePaper | May 18, 2021

Next-gen data operations require next-gen data technologies and strategies and Azure is an ideal platform for this modernization to take place. Download this white paper to better understand the strategies, philosophies, and technologies your organization needs to expand analytics abilities, reduce technical debt, embrace AI, and more.

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7 Trends for Data Science in 2021

whitePaper | May 5, 2021

Over the last decade, interest in the field of data science has not only increased enormously, but has also changed and developed considerably. In view of the new technological advances and the constant growth of data, we expect Data Science to continue to develop strongly in 2021. We have identified 7 trends that will be relevant for the coming year.

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A Modern Data Architecture

whitePaper | April 7, 2021

Assembling the perfect data stack is impossible. But for most data teams, the path to leveraging rapidly evolving tech and best-in-class tools is even more difficult when it’s impeded by the pitfalls of monolithic legacy applications.

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Spotlight

Pivotal

Pivotal’s cloud native platform drives software innovation for many of the world’s most admired brands. With millions of developers in communities around the world, Pivotal technology touches billions of users every day. After shaping the software development culture of Silicon Valley's most valuable companies for over a decade, today Pivotal leads a global technology movement transforming how the world builds software.

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