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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.

“Above the Trend Line” – Your Industry Rumor Central for 6/26/2017

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.

How San Francisco Company Index Is Transforming Offline Sales with Big Data

In this contributed article, technology writer and blogger Kayla Matthews discusses how the rise of big data has already blurred the lines between online retailers and brick-and-mortar storefronts. While many continue to pour their resources into e-commerce, those who would prefer to stick with tradition are finding it increasingly harder to do so.

Creating a Data-Based and Client-Focused Culture

In the world of social media, increasingly quick-moving communication amid rapidly growing data, a company’s culture defines its reputation, and its reputation often defines its success – or failure. Clarity Insights shares how companies can create a data-based and client-focused culture from the top down.

TERATEC 2017 Forum – The International Meeting for HPC, Simulation, Big Data

The TERATEC Forum is a major event in France and Europe that brings together the best international experts in HPC, Simulation and Big Data. It reaffirms the strategic importance of these technologies for developing industrial competitiveness and innovation capacity. The TERATEC Forum welcomes more than 1 300 attendees, highlighting the technological and industrial dynamism of HPC and the essential role that France plays in this field.

TOP 10 insideBIGDATA Articles for May 2017

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. We’re happy to oblige! We understand that busy big data professionals can’t check the site everyday.

BlueData, Intel Compare Bare-Metal & Containers for Big Data Workloads

Has your business ever tried to decide between a bare-metal environment or a container-based environment for dealing with Big Data needs? BlueData and Intel collaborated to discuss this very issue in a benchmark study of the performance of Big Data workloads.

“Above the Trend Line” – Your Industry Rumor Central for 6/5/2017

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.

TOP 10 insideBIGDATA Articles for April 2017

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. We understand that busy big data professionals can’t check the site everyday.

Hadoop, Spark or Both?

In this contributed article, tech writer Blake Davies asks the question: Spark or Hadoop? This question has recently sparked various discussions throughout the online communities. Even though these two work on different principles, they can be applied in a same way for various uses. While Hadoop is a household name in the world of big data processing, Spark is still building a name for itself and it’s doing so with “style”.