BigDataFr recommends: Data Team for Data Driven Organization A data-driven organization will use the data as critical evidence to help inform and influence strategy. To be data-driven means cultivating a mindset throughout the business to continually use data and analytics to make fact-based business decisions. Becoming a data-driven organization is no longer a choice, but […]
Month: février 2016
[HBR – Harvard Business Review] BigDataFr recommends: Just Using Big Data Isn’t Enough Anymore
BigDataFr recommande: Just Using Big Data Isn’t Enough Anymore […]Big Data has quickly become an established fact for Fortune 1000 firms — such is the conclusion of a Big Data executive survey that my firm has conducted for the past four years. The survey gathers perspectives from a small but influential group of executives — […]
[LMI] BigDataFr recommande : IBM livre quatre outils cloud big data et analytiques
BigDataFr recommande: IBM livre quatre outils cloud big data et analytiques […] Les quatre offres (Graph, Compose Enterprise, Predictive Analytics et Analytics Exchange) ajoutées au portefeuille Cloud Data Services d’IBM visent essentiellement les développeurs et les data scientists. L’outil IBM Graph est un service de base de données graphique entièrement géré. Il est construit sur […]
[O’R] BigDataFr recommends: Insightful applications: The next inflection in big data
BigDataFr recommends: Insightful applications: The next inflection in big data […] In previous posts, I wrote about the need for insight generation and provided an example of an insightful application. I maintain that insightful applications are the key to businesses effectively exploiting big data in order to improve decision-making and address important problems. To better […]
[Capital] BigDataFr recommande : ITV de Bénédicte de Raphélis Soissan, fondatrice de Clustree
BigDataFr recommande: ITV de Bénédicte de Raphélis Soissan, fondatrice de Clustree […] Avec Clustree, son outil d’analyse de profils, cette mathématicienne chamboule l’univers cloisonné des ressources humaines et du recrutement. Elle nous raconte son aventure d’entrepreneuse à succès. Elle a créé l’une des pépites de la French Tech. Bénédicte de Raphélis Soissan, 28 ans, fondatrice […]
[Analyticsvidhya – Tip] BigDataFr recommends: Complete guide to create a Time Series Forecast (with Codes in Python)
BigDataFr recommends: Complete guide to create a Time Series Forecast (with Codes in Python) […] Time Series (referred as TS from now) is considered to be one of the less known skills in the analytics space (Even I had little clue about it a couple of days back). But as you know our inaugural Mini […]
[Institut Fabernovel – ITV Video – Transformation Numérique] RH et problématiques Big Data : avec Yves Grandmontagne, ex DRH Pfizer et Microsoft France
BigDataFr recommande: RH et problématiques Big Data : avec Yves Grandmontagne, ex DRH Pfizer et Microsoft France Extrait Quelle place pour la DRH dans la transformation numérique ? […] Ma conviction aujourd’hui concernant la transformation numérique, que ce soit d’un point de vue organisationnel, évolutions des métiers, évolutions de votes collaboratifs, ou que ce soit […]
[Huffington Post – Analysis] BigDataFr recommends: How to Do Big Data on a Budget?
BigDataFr recommends: How to Do Big Data on a Budget? […] To really make the most of big data, most businesses need to invest in some tools or services – software, hardware, maybe even new staff – and there’s no doubt that the costs can add up. The good news is that big data doesn’t […]
[Les Echos] BigDataFr recommande : Big data et Data Science, leurs usages dans l’entreprise
BigDataFr recommande: Big data et Data Science, leurs usages dans l’entreprise […] Compte tenu de la jeunesse du secteur, peu d’acteurs prennent le risque d’investir dans l’analyse de leurs données et laissent aux acteurs établis et financièrement stables la priorité dans le développement de cette compétence clé de l’ère concurrentielle qui s’annonce. Data Science et […]
[HAL] BigDataFr recommends: Týr: Efficient Transactional Storage for Data-Intensive Applications
BigDataFr recommends: Týr: Efficient Transactional Storage for Data-Intensive Applications […] As the computational power used by large-scale applications increases, the amount of data they need to manipulate tends to increase as well. A wide range of such applications requires robust and flexible storage support for atomic, durable and concurrent transactions. Historically, databases have provided the […]