• Addressing Governmental Challenges when Engaging AI, ML and Data Analytics

    Gartner recently stated that all industries and levels of government agree the top three game-changing technologies today are AI/machine learning, data analytics/predictive analytics and cloud technologies. However, there are some primary sticking points when it comes to innovation in these areas. Government organizations continue to encounter challenges when trying to pursue these initiatives due to complex security and compliance requirements, poor scalability of legacy IT infrastructure, and perceived risks associated with cloud and IT modernization efforts. How can these challenges be addressed? [READ MORE…]

Featured Stories

  • The Key to Future-Proofing any Enterprise Data Architecture: Create Optionality

    In this special guest feature, Justin Borgman, Co-founder and CEO at Starburst Data, outlines how can IT future-proof the enterprise for the next big trend – by creating optionality. Specifically, he offers three strategic steps toward future-proofing the cloud data lake. [READ MORE…]

  • AI-Driven Data Catalogs: How to Find the Right one for Your Business

    data catalogs

    The commoditization of data has opened a world of opportunities up for countless enterprises. But as big data explodes, metadata initiatives are failing, and data discovery and retrieval is getting more and more difficult. A new white paper from IO-Tahoe explores data catalogs as a potential answer to this challenge. [READ MORE…]

  • TOP 10 insideBIGDATA Articles for May 2019

    In this continuing regular feature, we give all our valued readers a monthly heads-up for the top 10 most viewed articles appearing on insideBIGDATA. Over the past several months, we’ve heard from many of our followers that this feature will enable them to catch up with important news and features flowing across our many channels. [READ MORE…]

Featured Resource

big data

AI, Analytics and the Future of Your Enterprise

Tapping into the power of big data and analytics can be daunting. Download a new white paper from Pure Storage that explores how to jump into the world of big data and emerging AI technology, and take advantage of its benefits. The company’s research of emerging trends revealed three challenges of big data, and opportunities therein.

All Recent News

Industry Perspectives

  • DeepOps: The Lessons Deep Learning Can Learn From DevOps

    In this special guest feature, Yuval Greenfield from MissingLink.ai, discusses the rise of “DeepOps” aka AIOps and how it is where DevOps was in the 1990s—a nascent field that is becoming increasingly necessary. It starts with simple, but key facets like addressing some of the biggest pain points in the deep learning development lifecycle, such as automating version control. [READ MORE…]

  • Digital Trust & Safety: The Next Generation of Fraud Prevention is Powered by Machine Learning

    In this special guest feature, Kevin Lee, a Trust and Safety architect at Sift, discusses how Digital Trust & Safety, powered by machine learning, is taking the lead with fraud prevention efforts. Digital Trust & Safety is the only scalable and effective approach for the digital era. Companies that adopt Digital Trust & Safety are empowered to join the ranks of leading companies building the most groundbreaking products of our time. [READ MORE…]

RSS Featured from insideHPC

  • Nissan Moves HPC to the Cloud with Rescale
    Today Rescale announced that Nissan selected Rescale and AWS to extend its on-premise high performance computing systems to the cloud. "It is exciting to see that our hybrid platform on AWS will help Nissan immediately reduce time to market for their newest innovations, while getting access to unlimited computing resources on demand.” The post Nissan Moves […]

Editor’s Choice

  • The insideBIGDATA IMPACT 50 List for Q2 2019

    The team here at insideBIGDATA is deeply entrenched in following the big data ecosystem of companies from around the globe. We’re in close contact with most of the firms making waves in the technology areas of big data, data science, machine learning, AI and deep learning. Our in-box is filled each day with new announcements, commentaries, and insights about what’s driving the success of our industry so we’re in a unique position to publish our quarterly IMPACT 50 List of the most important movers and shakers in our industry. These companies have proven their relevance by the way they’re impacting the enterprise through leading edge products and services. We’re happy to publish this evolving list of the industry’s most impactful companies! [READ MORE…]

  • Field Report: GPU Technology Conference 2019 #GTC19

    I eagerly attended my 3rd GPU Technology Conference (GTC): “Deep Learning & AI Conference,” in Silicon Valley, March 23-26 as a guest of host NVIDIA. GTC has become my favorite tech event of the year due to its highly focused topic areas that align well with my own; data science, machine learning, AI, and deep learning; plus the show has an academic feel that I appreciate. [READ MORE…]

  • insideBIGDATA 2019 Annual Executive Round Up

    Our annual insideBIGDATA Executive Round Up showcases the insights of thought leaders on the state of the big data industry, and where it is headed. In our annual 2019 round up, we examine five topics: the importance of AI explainability in 2019, what industries are making the best competitive use of AI in 2019, how enterprises are seeking to improve technological infrastructure and cloud hosting processes for supporting AI, how AI-optimized hardware solves important compute and storage requirements, and how AI plays important roles at 3 leading companies. [READ MORE…]

  • Field Report: H2O World 2019 San Francisco

    I was pleased to be on-hand for the recent (Feb. 4-5) H2O World 2019 conference in beautiful San Francisco. This was my first H2o.ai conference and I was looking forward to drilling down into their popular open source solutions for data scientists including the H2O machine learning platform, Sparkling Water machine learning platform on Spark, H2O4GPU accelerated AI for GPUs, as well as the groundbreaking Driverless AI automatic machine learning (AutoML) platform. With all this leading-edge technology and resulting industry buzz, I can see why the company recently ranked #9 on insideBIGDATA’s IMPACT 50 list of the industry’s most impactful companies. [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…]

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