BigDataFr recommends: 12 Types Of Data IT Can’t Afford To Overlook Your organization probably already has more data than it knows what to do with. Yet, it’s quite likely you’re overlooking, disregarding, unaware of, or unable to access important information that could directly affect analyses and business outcomes. It doesn’t matter what your universe of […]
Author: Big Data
[HAL]] BigDataFr recommends: Scalable Algorithms for Nearest-Neighbor Joins on Big Trajectory Data
BigDataFr recommends: Scalable Algorithms for Nearest-Neighbor Joins on Big Trajectory Data Keywords: Nearest neighbor, Trajectory join, Big trajectory data, MapReduce. Abstract […] Trajectory data are prevalent in systems that monitor the locations of moving objects. In a location-based service, for instance, the positions of vehicles are continuously monitored through GPS; the trajectory of each vehicle […]
[O’R] BigDataFr recommends: 3 ideas to add to your data science toolkit
BigDataFr recommends: 3 ideas to add to your data science toolkit I’m always on the lookout for ideas that can improve how I tackle data analysis projects. I particularly favor approaches that translate to tools I can use repeatedly. Most of the time, I find these tools on my own—by trial and error—or by consulting […]
[Datasciencecentral] BigDataFr recommends: A methodology for solving problems with DataScience for Internet of Things – Full – #iot
BigDataFr recommends: A methodology for solving problems with DataScience for Internet of Things – Part 1 and 2 […] This two part blog is based on my forthcoming book: Data Science for Internet of Things. It is also the basis for the course I teach Data Science for Internet of Things Course. I will be […]
[Mc Kinsey] BigDataFr recommends: People analytics reveals three things HR may be getting wrong
BigDataFr recommends: People analytics reveals three things HR may be getting wrong Bill James, the factory watchman turned baseball historian and statistician, once observed, “There will always be people who are ahead of the curve, and people who are behind the curve. But knowledge moves the curve.”1 Some companies are discovering that if they employ […]
[informationweek] BigDataFr recommends:How To Hire Analytical Workers: 10 Traits To Seek
BigDataFr recommends: How To Hire Analytical Workers: 10 Traits To Seek Does your organization have more data than it knows what to do with? The race is on in corporations everywhere to make sense of all the information flooding in. Knowing this, businesses that are investing in business intelligence, Big Data, analytics, and data science […]
[CIO] BigDataFr recommends: Big Data and elections: The candidates know you – better than you know them
BigDataFr recommends: Big Data and elections: The candidates know you – better than you know them With the presidential nominating conventions looming, the candidates are getting ready to add to the hundreds of millions they’ve already spent to tell you about themselves – but only what they want you to know about themselves. Meanwhile, they […]
[ZDNet] BigDataFr recommande : Vers une compréhension artificielle des sentiments humains
BigDataFr recommande: Vers une compréhension artificielle des sentiments humains […] Un tweet avec photo pour râler de la vétusté d’une cabine pour un vol transatlantique et hop, le responsable client de la compagnie rebondit pour voir comment améliorer le confort de vol du passager. Simple comme un petit message ? Pas tout à fait. Pour […]
[Les Echos] BigDataFr recommande : Marseille, menacée par Daech, renforce son réseau de surveillance
BigDataFr recommande : Marseille, menacée par Daech, renforce son réseau de surveillance […]Les Marseillais tentent de faire face aux nouvelles menaces qui pèsent sur eux. Jeudi, une vidéo de Daech a pour la première fois mentionné la métropole méditerranéenne parmi les prochaines cibles de l’organisation terroriste. Sur les réseaux sociaux, les habitants ont plutôt régi […]
[arXiv] BigDataFr recommends: Representation of functions on big data associated with directed graphs
BigDataFr recommends: Representation of functions on big data associated with directed graphs Subjects: Classical Analysis and ODEs (math.CA) […] This paper is an extension of the previous work of Chui, Filbir, and Mhaskar (Appl. Comput. Harm. Anal. 38 (3) 2015:489-509), not only from numeric data to include non-numeric data as in that paper, but also […]