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Tag: popularity
A Recession Before 2020 Is Likely; On the Distribution of Time Between Recessions
Feed: R-bloggers. Author: ntguardian. I recently saw a Reddit thread in r/PoliticalDiscussion asking the question “If the economy is still booming 2020, how should the Democratic address this?” This gets to an issue that’s been on my mind since at least 2016, maybe even 2014: when will the current period of economic growth end? For some context, the Great Recession, as economists colloquially call the recession beginning in 2007 and punctuated with the 2008 financial crisis, ended officially in June 2009; it was then the economy resumed growth. As of this writing, that was about eight years, ten months ago ... Read More
IMDG Skills and Jobs Index 2018

Feed: Hazelcast Blog. Author: David Brimley. 2018 In-Memory Data Grids resurgent IMDG (In-Memory Data Grids) have been around for well over a decade now and sit in a product sector that slightly overlaps NoSQL functionality. IMDGs initially came to the market in the early nougties when web sessions needed to scale past one sticky web-server, these were the days of what was then known as Tangosol Coherence. Since then the main use case for IMDGs has become general in memory caching and compute, where the IMDG sits between a slower persistent store like an RDBMS/Mainframe (or even a NoSQL Database) ... Read More
HITRUST™ on Amazon Web Services (AWS)
Feed: News & Blog – Logicworks. Author: Logicworks; The HITRUST CSF™ is growing in popularity — it’s used by 26.4% of healthcare companies as their cybersecurity framework for HIPAA compliance, according to the 2018 HIMSS Cybersecurity Survey.While HITRUST certification is a competitive differentiator for healthcare software and services companies in 2018, it will likely be table stakes in the next 1-3 years. The big health insurance companies are asking all of their vendors for proof of HITRUST certification, and it’s wise to begin thinking about it now — before lack of HITRUST certification hurts your business.Last week, VP of Product ... Read More
Protect Your Cloud from the Notorious Nine
Feed: Arisant » Arisant Answers. Author: admin; Although the first cloud users typically adopted the technology to simply extend storage, clouds for various purposes are now forming, forever changing the IT troposphere. There are now public, private, and hybrid clouds that offer software services, database services, infrastructure services, and many more. Cloud services are gaining popularity because they’re cost-effective, efficient, dynamic, easy to set up, and easy to maintain. However, cloud services also present some challenges, the biggest of which is security. What are the threats? In the research document “The Notorious Nine,” the Cloud Security Alliance identified the top ... Read More
Achilleas Mantzios: Ten Tips for Going into Production with PostgreSQL

Feed: Planet PostgreSQL. Going into production is a very important task that must be carefully thought and planned beforehand. Some not so good decisions may be easily corrected afterwards, but some others not. So it is always better to spend that extra time in reading the official docs, books and research made by others early, than be sorry later. This is true for most computer systems deployments, and PostgreSQL is no exception. System Initial Planning Some decisions must be taken early on, before the system goes live. The PostgreSQL DBA must answer a number of questions: Will the DB run ... Read More
Blog Post: Is Redshift giving you the Blues? ER/Studio has the cure.
Feed: Blog. Author: Ron Huizenga; In my 35 years of data modeling many data platforms have come and gone, while others continue to change. For many, maintaining pace with the frequency of change in data platforms is an ongoing challenge. For a modeling vendor such as ourselves, immediately adding new features to correlate to every single change to the multitude of different platforms is virtually impossible , so we prioritize by considering several factors including customer demand and market viability of new platforms and features. We realize that different customers require different platforms and features at varying rates, which is ... Read More
Where is the value in package peer review?
Feed: R-bloggers. Author: rOpenSci - open tools for open science. (This article was first published on rOpenSci - open tools for open science, and kindly contributed to R-bloggers) If you read my reflection #1 on rOpenSci Onboarding, then you know I see value in the Onboarding process. A LOT of value even. This post is about where that value lies. This question has important corollaries which I will explore here based on my experience as a reviewer of bowerbird: How is a package peer reviewer’s time best spent? When is the best time in a software package’s life cycle to ... Read More
MariaDB strengthens its position in the open source RDBMS market
Feed: DB-Engines.com Blog. Author: Matthias Gelbmann. MariaDB has reached a new all-time high in the DB-Engines Ranking, climbing to rank 14, up from rank 18 one year ago and from rank 25 three years ago. That is roughly a tripling of its popularity score in the last three years ... Read More
Predicting community engagement on Reddit using TensorFlow, GDELT, and Cloud Dataflow: Part 3

Feed: Google Cloud Big Data and Machine Learning Blog. Author: Google Cloud Big Data and Machine Learning Blog Team. By Sergei Sokolenko, Cloud Dataflow Product Manager In Part 1 of our blog series we previewed TensorFlow models that combined traditional natural language processing (NLP) techniques such as entity and topic extraction, and deep learning techniques such as embeddings to predict with 92% accuracy which Reddit community (subreddit) a news article would land for discussion, and estimated the popularity score and volume of comments such post would generate. Part 2 of the series went into detail of developing and tuning these ... Read More
AutoML Vision in action: from ramen to branded goods

Feed: Google Cloud Big Data and Machine Learning Blog. Author: Google Cloud Big Data and Machine Learning Blog Team. By Kaz Sato, Staff Developer Advocate, Google Cloud Take a look at the three ramen bowls below. Can you believe that a machine learning (ML) model can identify the exact shop each bowl is made at, out of 41 ramen shops, with 95% accuracy? Data scientist Kenji Doi built an AI-enabled ramen expert classifier that can discern the minute details that make one shop’s bowl of ramen different from the next one’s. Ramen bowls made at three different Ramen Jiro shops ... Read More
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