Big Data Technology

Machine learning molds the material world

December 18, 2014
Computational modeling has revolutionized all branches of the physical sciences, engineering and design. Leading-edge work in these fields is pushing new computational frontiers at nano scales. Computation-centric methods allow researchers to model, simulate and assess a much wider array of options far more rapidly than old-fashioned physical techniques. However, the incredible productivity of computational prototyping carries a downside: far more candidate molecules can be simulated than can reasonably be assessed by human researchers. The bottom line is that when you build bigger haystacks, you need more powerful tools for finding the golden needles that may be buried deep within.  Read More

Big data for business in 2015

December 16, 2014
The competitive landscape in business has been data. But what's changing in 2015? Read More

Big Data & Analytics Heroes: David M. Lawson

December 16, 2014
“As you dig deeper into unstructured data where feelings, emotions and other often messy information reside, you have to embrace qualitative metrics which don’t fit neatly into traditional quantitative analysis,” says David M. Lawson, co-founder & CEO of NewSci, LLC and this week’s Big Data & Analytics Hero. Read More

Harnessing and protecting big data for financial services

December 15, 2014
Financial services and banking are data-driven. Organizations in these industries store and analyze data on millions of customers, this data valued in the billions. As a consequence, they have to struggle with ever increasing volumes, velocity and variety of data. To stay ahead of competition, and to detect fraud before it happens, financial service companies are using Hadoop to more effectively analyze data and make well-informed decisions. Read More

How Hadoop is changing energy and utilities

December 12, 2014
Today, energy and utility companies are relying on Hadoop to help curb energy consumption, reduce energy loss and add more clean power to the grid. Using big data and analytics, organizations can empower users to understand their energy usage and give them the chance to reduce how much they use and pay. Read More

2015: The year of the “I” in “IT”

December 11, 2014
Organizations of all sizes are struggling with how to extract insight and mitigate risk relative to the massive volumes of information and data that they are accumulating, including dark data. Read More

Reflections and predictions for stream computing in 2015

December 10, 2014
Stream computing exploded in 2014 and we’ve got high expectations for 2015. The October 2014 IBM Institute for Business Value report  found that real-time analytics is the leading big data requirement. What’s your prediction for the future of stream computing?  Read More

Why advanced analytics projects are different from traditional IT

December 9, 2014
To fulfill the promise of analytics, we must put a lot more effort into delivering these projects right, the first time. We must think through each of the traditional success criteria and ask ourselves the burning question: how is delivering analytics different? This starts from gaining executive support, creating a business case, putting a team together, conducting proof of concept, quantifying benefits realization and socializing results for enabling analytics driven organizational change. Read More

Big Data & Analytics Heroes: Jake Porway

December 9, 2014
Jake Porway, founder and executive director of DataKind and this week’s Big Data & Analytics Hero, shares that they’ve found that "cross-sector collaborations between data scientists, managers, designers, foundations, nonprofits and more are critical for really making lasting change.” When we all come together and lock elbows we can use data to really make a difference.  Read More

Why should automotive and manufacturing CTOs care about Hadoop?

December 2, 2014
Automotive and manufacturing organizations deal with a massive volume of data, including global data from customers and data generated through internal business operations, research and development (R&D) and supply chain activities. These data sets represent an opportunity for an organization that will require specialized solutions like Hadoop. Read More

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