Big Data Project Failure Pain Points and their Solution
Big data projects don’t typically fail for a single reason, and certainly not for technology alone. A combination of factors serve to derail big data deployments. Problems and failures occur due to factors including business strategy, people, culture, inattention to analytics details or the nuances of implemented tools, all intensified by the rapid advancement of digital transformation. [READ MORE...]
Recent Features
Building a Machine Learning Platform at Quora
In this MLconf SF 2016 talk "Building a Machine Learning Platform at Quora," Nikhil Garg, Engineering Manager at Quora, discusses the core ideas behind his company's machine learning platform, as well as some of the specific systems, tools, and abstractions that have enabled the company to scale their approach to machine learning. [READ MORE...]
Book Review: The Mathematical Corporation by Josh Sullivan and Angela Zutavern
As a data scientist, I know first hand how today's enterprise has some catching up to do with engaging the mathematical foundations for capitalizing on an ever-increasing volume of data assets. This is why a new title is so important: "The Mathematical Corporation - Where Machine Intelligence and Human Ingenuity Achieve the Impossible," by Josh Sullivan and Angela Zutavern. Sullivan and Zutavern are, respectively, senior vice president and vice president of Booz Allen Hamilton. [READ MORE...]
Want to Run Cassandra in a Container? You Need to Solve These 4 Problems First
In this contributed article, Gou Rao, Co-founder and CTO at Portworx, discusses how running the open source distributed NoSQL database Cassandra in a container requires some special considerations. If you can solve these problems, you’ll have gotten most of the way to a successful Cassandra deployment in containers. [READ MORE...]
Featured Resource
Making Machine Learning Simple
For enterprises who need to jump start into machine learning, Databricks provides the performance, reliability, and ease of use to tackle machine learning with big data. With Databricks, teams will be able to focus on solving hard machine learning problems instead of supporting infrastructure. To learn more on making machine learning simple download this white paper.
Industry Perspectives
How Enterprises Can Finally Capitalize on Machine Learning
In this special guest feature, Dr. Michael Zeller, SVP, AI Strategy & Innovation at Software AG, discusses how enterprises have reached a pivotal moment for operationalizing machine learning. For a while now artificial intelligence has been over hyped, its benefits over promised and, in the end, it always under-delivered. Now the hype is back stronger than ever. For AI to not fade away again, however, it needs to be made actionable. [Read More...]
The Future of Federal Agency Data Access, Integration, Sharing and Security
In this special guest feature, Gavin Robertson, CTO and SVP of WhamTech, discusses the future technology of data federation and protection within federal agencies. These new technologies could have a profound positive impact on the effectiveness and efficiency of future government programs. The benefits will be significant, including cost savings, accelerated implementations, improved and new capabilities, leveraged existing IT investments, improved data security, flexible future options and increased stakeholder satisfaction. [Read More...]
Featured from insideHPC
- Video: New Mellanox SHIELD Technology Enables Self Healing Networks“The CPU-centric data center architecture has come to an end and new data centers are now built based on a data-centric architecture. These systems require an intelligent interconnect that can deliver In-Network Computing and Self-healing capabilities, to ensure highest performance, scalability and resiliency." The post Video: New Mellanox SHIELD Technology Enables Self Healing Networks appeared […]
News from insideHPC
- RSC Group from Russia Brings Hot Water Cooling to HPC
- Video: New Mellanox SHIELD Technology Enables Self Healing Networks
- Bright Computing Steps up with Cloud Bursting to Azure at ISC 2017
- Interview: Piz Daint Supercomputer advances to the #3 position on the TOP500
- Andrew Jones wraps up ISC 2017
- Supercomputing the Secrets of the Snake Genome at TACC
- Intel Omni-Path Architecture: Incredible Momentum for a New Technology
Editor’s Choice
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...]
Pulling Real ROI from a Sea of Big Data Analytics
In this special guest feature, Jessica Hawthorne-Castro, CEO of Hawthorne Direct, provides some strategic best practices for marketers that want to extract ROI from big data in order to improve the customer experience and generate sales. [Read More...]
Interview: Emily Glassberg Sands, Data Science Manager at Coursera
I recently caught up with Emily Glassberg Sands, Data Science Manager at Coursera, to talk about applying machine learning, neural networks, natural language processing, and big data analytics to the retail industry. Emily leads an awesome team of data scientists and data science managers working on growth, discovery, the learning experience, and a new enterprise offering. The team's job is to help build a better Coursera through data-driven decisions and products. [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...]
