This is the first entry in an insideBIGDATA series that explores the intelligent use of big data on an industrial scale. This series, compiled in a complete Guide, also covers the changing data landscape and realizing a scalable data lake, as well as offerings from HPE for big data analytics. The first entry is focused on the recent exponential growth of data.
A collection of big data white papers reviewed by the editors of insideBIGDATA. Please visit the insideBIGDATA White Paper Library for a comprehensive list of white papers focus on big data strategies.
The insideBIGDATA Guide to Deep Learning & Artificial Intelligence is a useful new resource directed toward enterprise thought leaders who wish to gain strategic insights into this exciting area of technology. This is the second in a series of articles providing content extracted from the guide. The topic for this segment is the difference between AI, machine learning and deep learning.
The insideBIGDATA Guide to Deep Learning & Artificial Intelligence is a useful new resource directed toward enterprise thought leaders who wish to gain strategic insights into this exciting area of technology. In this guide, we take a high-level view of AI and deep learning in terms of how it’s being used and what technological advances have made it possible. We also explain the difference between AI, machine learning and deep learning, and examine the intersection of AI and HPC. We present the results of a recent insideBIGDATA survey, “insideHPC / insideBIGDATA AI/Deep Learning Survey 2016,” to see how well these new technologies are being received. Finally, we take a look at a number of high-profile use case examples showing the effective use of AI in a variety of problem domains.
In this special technology white paper, From Small to Big Data, Adopting the Advanced Analytics Mindset, you’ll learn how to help data teams — analysts, scientists, and managers — to collaborate on data projects. One of the key success factors for these teams is to allow analysts to work on Big Data as easily as they do on smaller data with Excel, as well as to help them find new use cases specific to the data available and the tools at hand.
In this whitepaper, you’ll learn how advanced analytics has the potential to transform the ways in which segmentation for marketing purposes is accomplished. It starts with a look at traditional segmentation methods and then moves on to exploring how advanced analytics (model-based segmentation) can change the game. Then you’ll explore a few marketing & analytics use cases in various industries. Lastly, you’ll examine the methodologies needed to implement model based segmentation in the real world.
In this special technology white paper, The 5 Key Challenges to Building a Successful Data Science Lab & Data Team, you’ll learn how a Data Lab establishes an effort to answer business needs by making sense of raw information. Data labs are intended to create critical mass within the organization that enables them to reach the level of innovation required for new data-driven products.
In this special technology white paper, The GridGain In-Memory Data Grid, you’ll learn that with the cost of system memory dropping 30% every 12 months, in-memory computing has become the first choice for a variety of workloads across all industries. In-memory computing can provide a lower TCO for data processing systems while providing an unparalleled performance advantage.
In this special technology white paper, Architecting for Access: Simplifying Analytics on Big Data Infrastructure, you’ll learn how designing systems for data analytics is a bit of a trapeze act—requiring you to balance front-end convenience and access without compromising on back-end precision and speed.
The insideBIGDATA Guide to Healthcare & Life Sciences is a useful new resource directed toward enterprise thought leaders who wish to gain strategic insights into this exciting new area of technology. This segment focuses on big data case studies.