Big Data: “Cloud infrastructure and platforms will play a huge role in accessing, processing, and analyzing such massive amounts of data. This is where cloud-based systems shine.” ...

How to create a social media strategy with big data. The most successful social media strategies match what your customers and the outside world are telling you. Here’s a step-by-step guide to ...

Big Data's cloud computing and cybersecurity technologies integrate exceptionally well from a portfolio perspective, as the data-dense cloud necessitates ongoing cybersecurity spending and investment.

Today we typically equate "big data" and "social media" but that is largely because of social data's widespread machine-friendly availability, yet this over reliance has constrained the questions ...

Big Data comes from a multitude of sources including social media platforms, mobile devices ... data visualization techniques and cloud computing infrastructure. As Big Data continues to grow ...

Whether you’re involved in the business or tech industries, you’ve probably heard a lot of discussions regarding ‘big data.’ But, what exactly is big data and how is it being used to solve ...

Existing distributed computing frameworks are failing to keep a lid on the growing computational, memory and even energy costs resulting from the constantly expanding volume Big Data for anything ...

Social computing is also having a big impact on mainstream media, and Outsell’s report notes the slow growth of the News and Trade segment, which has been impacted by several new trends ...

That’s the power of modern computing and the promise of big data. To sequence the first human genome cost almost $3 billion and took about 15 years to complete. Now it can cost less than $2,000 ...

Big Data, as the name implies, relates to very large sets of data collected through free or commercial services on the internet. This massive amount of data arises from sensors, posts to social ...

AI has a central role to play in managing and contextualizing big datasets, and combining AI with edge computing is key to efficiently extracting actionable insights from those data flows.

Trained social scientists are needed to deal with such big-data pitfalls as reverse causality, or others such as unobserved heterogeneity, sample-selection issues, aggregation bias, or spatial or ...