Among the major reasons we created our Data is the fact that there just are not a ton of open datasets that are great out there for startups, small businesses, and professors to do on work.

We consider that open data should become the newest source that is open; we presume clean, enriched big data that is shared is among the essential elements to initiation that is actual.

That is why we were very pleased to learn exactly what the people around at MonkeyLearn are doing…

“Data! Data! Data! I can’t make bricks without clay!” Data is crucial, as pointed out by Sherlock Holmes two hundred years ago. In today’s business world, data is more important and valuable than ever, thanks to the accessibility of big data analytics tools.…

Guest blog post by Mirko Krivanek

Usually I tend to criticize this type of articles, but in this case I agree pretty much agree with BurtchWorks, the author of this article, even though the article is more than 6 months old. Note that BurtchWorks is a recruiting firm that recently posted…

Glimpsing the Far Side—How Healthcare Organizations are Applying Predictive Analytics

Guest blog post by Paul Bradley

Anyone who works in healthcare—or who has pondered, even fleetingly, how it differs from other sectors of the American economy—likely won’t be surprised to hear it’s the final frontier for predictive analytics.

For indeed, while predictive analytics has long since reshaped retail, shipping & logistics, and even…

Transferring large datasets especially with heterogeneous file sizes (i.e. many small and large files together) causes inefficient utilization of the available network bandwidth. Small file transfers may cause the underlying transfer protocol not reaching the full network utilization due to short-duration transfers and connection start up/tear down overhead; and large file transfers may suffer from protocol inefficiency and end-system limitations.

Application-level TCP tuning…