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A 3-month solution for automated, data-driven materials science analytics

The materials sciences domains are attempting to use their data more effectively to drive decision-making, product innovations, new R&D research, etc. While there has been a push to improve on technologies to help with this effort, the industry, as a whole, is still hampered by many long-standing problems such as a large percentage of their data living in hundreds of thousands of flat files, report documents, and older database systems, where much of the metadata is messy or not existent.

This whitepaper provides a very clear-cut technology option that can help materials sciences companies overcome their current obstacles, by showcasing a new technology approach based on virtualized artificial intelligence (AI), that combines semantic metadata along with powerful machine learning and other algorithmic approaches. The product is called LeapAnalysis and is an award-winning AI product that has a proven track record of providing large enterprises with a new means to tackle their largest data challenges around advanced search and in-depth analytics.

Download this paper to learn how to:

  • Understand how to take immediate advantage of all of your available data, regardless of format or location within the enterprise

  • Learn how you can augment your current big data projects, which may be running long on time and over budget

  • Set up an approach that can bring you analytics that solves real problems in 3 months instead of multiple years, and for a fraction of your current data integration costs

  • Take advantage of our proven 6-step LeapAnalysis methodology to accelerate your digital transformation efforts

  • Learn how LeapAnalysis can position your company for competitive advantage in your space and save you critical steps in time to market