Top 3 Reasons to Invest in Big Data
In this contributed article, business strategist and finance columnist Dr. Diane Schleier-Keller, takes a look at the top 3 reasons to invest in big data. People are starting to notice the astonishingly useful applications of collating unimaginably large data sets. With this realization, another soon follows: big data has the capability to generate a profusion of wealth. [READ MORE...]
Featured Stories
The Next Generation of Managing Enterprise Data: Data Conductor
With capabilities to act as what we call a “data conductor”, businesses are free to work with any data at anytime, anywhere to best serve business goals, unlocking the constraints of any data management environment. This sponsored post from Chris Ortega, Senior Director, Customer Success, at Podium Data, is the second in a three-part series focused on the need for increased data agility. [READ MORE...]
How to Move a Petabyte of Data to the Cloud in Four Steps
Organizations of all sizes are increasingly using public cloud infrastructure, but those with hundreds of terabytes or petabytes of data find the shift to cloud more complex, disruptive, and inflexible than it is presumed. The business value of cloud storage is desirable, but large data volumes present large challenges for migration, compatibility, and agility. Below are four steps to transition even petabyte-scale data to cloud environments from experts at SwiftStack, a company that powers hybrid cloud storage for enterprises. [READ MORE...]
“Above the Trend Line” – Your Industry Rumor Central for 8/21/2017
Above the Trend Line: your industry rumor central is a recurring feature of insideBIGDATA. In this column, we present a variety of short time-critical news items grouped by category such as people movements, funding news, financial results, industry alignments, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and curious buzz. [READ MORE...]
Featured Resource
insideBIGDATA Guide to Artificial Intelligence & Deep Learning
In this guide we explain the difference between AI, machine learning and deep learning, and include highlights of the insideBIGDATA audience survey. To learn more about AI and deep learning download this guide.
Industry Perspectives
Microservices and Your Data: What You Need To Know
In this special guest feature, Christian Posta, Chief Architect, Cloud Application Development at Red Hat, argues that data is one of the hardest parts of microservices. If a core tenet of microservices is that each service should have its own database, how does the system reconcile changes across these databases while maintaining independence and autonomy? The answer, according to Christian, is to adopt a domain-driven design approach. By modelling the data within a set domain and context, microservices can shed these dependencies while still maintaining data consistency throughout the system. [Read More...]
For a Successful Data-driven Transformation, Follow These Three Steps
In this special guest feature, Lars Fæste and Antoine Gourévitch of The Boston Consulting Group, discuss how data is becoming an increasingly powerful tool for business leaders in many industries who want a competitive edge, and how many companies struggle to collect and profit from data in new ways. He then outlines a three-step approach to data transformation that is easier, cheaper and more successful than attempts at sweeping, large-scale change. [Read More...]
Featured from insideHPC
- IEEE Approves Standards Project for Quantum Computing Definitions"While Quantum Computing is poised for significant growth and advancement, the emergent industry is currently fragmented and lacks a common communications framework,” said Whurley (William Hurley), chair, IEEE Quantum Computing Working Group. “IEEE P7130 marks an important milestone in the development of Quantum Computing by building consensus on a nomenclature that will bring the benefits […]
News from insideHPC
- IEEE Approves Standards Project for Quantum Computing Definitions
- Podcast: A Look at the Intel Nervana Platform for AI
- NCSA Industry Conference to Showcase Supercomputing Partnerships
- Intel FPGAs Accelerate Microsoft’s Project Brainwave
- ANSYS 18.2 Enhances Simulation Speed and Accuracy
- New Study Uncovers Best Practices for Effective Partnerships between Public HPC Centers and Industrial Users
- Dell EMC Joins Atos Global Reseller Alliance
Editor’s Choice
Big Data or Small Data? The Correct Answer is Both
In this special guest feature, Dr. Ricardo Baeza-Yates, CTO at NTENT, discusses how it’s not enough to weigh data decisions on the descriptor of big versus small alone - a number of other things must be considered. [Read More...]
Interview: Michael Stonebraker, Adjunct Professor, MIT Computer Science and AI Laboratory (CSAIL)
The following is a discussion with Michael Stonebraker, Adjunct Professor, MIT Computer Science and Artificial Intelligence Laboratory (CSAIL); ACM 2014 Turing Award Recipient. The Association of Computing Machinery (ACM) just concluded a celebration of 50 years of the ACM A.M. Turing Award (commonly known as the “Nobel Prize of computing”) with a two-day conference in San Francisco. The conference brought together some of the brightest minds in computing to explore how computing has evolved and where the field is headed. [Read More...]
The Difference Between Data Science and Data Analytics
In this contributed article, tech writer Rick Delgado, examines the differences between the terms: data science and data analytics, where people working in the tech field or other related industries probably hear these terms all the time, often interchangeably. Although they may sound similar, the terms are often quite different and have differing implications for business. [Read More...]
Interview: Anusua Trivedi, Data Scientist on Microsoft's Advanced Data Science & Strategic Initiatives Team
In this podcast interview, I caught up with Anusua Trivedi, a Data Scientist on Microsoft’s ADS team, to get her take on the upward trajectory of AI and deep learning that we're seeing in the industry today. [Read More...]
Big Data Industry Predictions for 2017
Wow! What a year 2016 has been. The big data industry has significant inertia moving into 2017. In order to give our valued readers a pulse on important new trends leading into next year, we here at insideBIGDATA heard from all our friends across the vendor ecosystem to get their insights, reflections and predictions for what may be coming. We were very encouraged to hear such exciting perspectives. Even if only half actually come true, Big Data in the next year is destined to be quite an exciting ride. Enjoy! [Read More...]
