BigDataFr recommends: Big Data and Business Intelligence: Debunking the Myths Big data is one of the most discussed, and possibly least understood, terms in use in business today. Big data is said to offer not only unprecedented levels of business intelligence concerning the habits of consumers and rivals, but also to herald a revolution in […]
Month: novembre 2015
[Data Science Central] BigDataFr recommends: Spark Or Hadoop: Which Is The Best Big Data Framework?
BigDataFr recommends: >Spark Or Hadoop: Which Is The Best Big Data Framework? Excerpt One question I get asked a lot by my clients is: Should we go for Hadoop or Spark as our big data framework? Spark has overtaken Hadoop as the most active open source Big Data project. While they are not directly comparable […]
[Data Science Central] BigDataFr recommends: Spark Or Hadoop: Which Is The Best Big Data Framework?
BigDataFr recommends: >Spark Or Hadoop: Which Is The Best Big Data Framework? Excerpt One question I get asked a lot by my clients is: Should we go for Hadoop or Spark as our big data framework? Spark has overtaken Hadoop as the most active open source Big Data project. While they are not directly comparable […]
[arXiv] BigDataFr recommends: Preconditioned Data Sparsification for Big Data with Applications to PCA and K-means #datascientist
BigDataFr recommends: Preconditioned Data Sparsification for Big Data with Applications to PCA and K-means Excerpt We analyze a compression scheme for large data sets that randomly keeps a small percentage of the components of each data sample. The benefit is that the output is a sparse matrix and therefore subsequent processing, such as PCA or […]
[Datasciencecentral] BigDataFr recommends: Is Data Science, Like Mathematics, a Universal Language? #datascientist
BigDataFr recommends: Is Data Science, Like Mathematics, a Universal Language? Excerpt I try to keep my eye out for articles written by data scientists in other countries, especially those we don’t hear from all that often. What I’m looking for is any difference in perspective about our field. Are the approaches to data problem solving […]
[Datasciencecentral] BigDataFr recommends: Is Data Science, Like Mathematics, a Universal Language? #datascientist
BigDataFr recommends: Is Data Science, Like Mathematics, a Universal Language? Excerpt I try to keep my eye out for articles written by data scientists in other countries, especially those we don’t hear from all that often. What I’m looking for is any difference in perspective about our field. Are the approaches to data problem solving […]
[arXiv] BigDataFr recommends: Preconditioned Data Sparsification for Big Data with Applications to PCA and K-means
BigDataFr recommends: Preconditioned Data Sparsification for Big Data with Applications to PCA and K-means Excerpt We analyze a compression scheme for large data sets that randomly keeps a small percentage of the components of each data sample. The benefit is that the output is a sparse matrix and therefore subsequent processing, such as PCA or […]
[datasciencecentral] BigDataFr recommends: 5 Warning Signs that Turn Off Data Science Hiring Managers
BigDataFr recommends: 5 Warning Signs that Turn Off Data Science Hiring Managers Excerpt As a hiring manager for data analytics positions, I often complain that there are not enough qualified resumes. Most of the resumes that do get passed on to me from recruiters quickly get filed away. Those job candidates belong to one of […]
[arXiv] BigDataFr recommends: Making problems tractable on big data via preprocessing with polylog-size output
BigDataFr recommends: Making problems tractable on big data via preprocessing with polylog-size output To provide a dichotomy between those queries that can be made feasible on big data after appropriate preprocessing and those for which preprocessing does not help, Fan et al. developed the ⊓-tractability theory. This theory provides a formal foundation for understanding the […]