Titre : | Data Lake and Digital Enterprise | Type de document : | projet fin études | Auteurs : | Oumaima EL HADDADI, Auteur | Langues : | Français (fre) | Catégories : | BIG DATA
| Index. décimale : | mast 283/19 | Résumé : | Through digital transformation and huge amount of data, decisional support systems are taking more and more importance in order to improve business goals as predictive models. At this stage, big data is becoming a key competitive differentiator of all organizations and influencing the evolution of scientific environments, so the arrival of big data has changed traditional treatments and creates new challenges related to velocity, volume and variety of data. To meet this challenge: the storage of different types of data and the provision of the necessary capacity for fast data processing, we are facing the Data Lake solution that is able to meet these challenges. More than that, most research concerning Data Lake finds problems in the management and exploitation of the latter. Therefore, in this project we will propose solutions to improve the Data Lake system. By the first we propose a virtual architecture of Data Lake, after that we create the conceptual model to extract the meta-data from the source (intern and extern). In addition, to solve the problematic of heterogeneous schemas we propose to create a data dictionary. |
Data Lake and Digital Enterprise [projet fin études] / Oumaima EL HADDADI, Auteur . - [s.d.]. Langues : Français ( fre) Catégories : | BIG DATA
| Index. décimale : | mast 283/19 | Résumé : | Through digital transformation and huge amount of data, decisional support systems are taking more and more importance in order to improve business goals as predictive models. At this stage, big data is becoming a key competitive differentiator of all organizations and influencing the evolution of scientific environments, so the arrival of big data has changed traditional treatments and creates new challenges related to velocity, volume and variety of data. To meet this challenge: the storage of different types of data and the provision of the necessary capacity for fast data processing, we are facing the Data Lake solution that is able to meet these challenges. More than that, most research concerning Data Lake finds problems in the management and exploitation of the latter. Therefore, in this project we will propose solutions to improve the Data Lake system. By the first we propose a virtual architecture of Data Lake, after that we create the conceptual model to extract the meta-data from the source (intern and extern). In addition, to solve the problematic of heterogeneous schemas we propose to create a data dictionary. |
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