Data mart

About: Data mart is a research topic. Over the lifetime, 559 publications have been published within this topic receiving 8550 citations.

Method and device for managing data warehouse and data mart

Abstract: The present disclosure relates to a method and a device for managing a data warehouse and a data mart. The management method of the data warehouse and the data mart comprises the following steps: extracting and processing the production data of the data source into a Hadoop cluster environment; storing the data in the data warehouse cluster according to a first data storage structure; in the Hadoop cluster environment, creating corresponding Hadoop cluster users according to service division or organizational structure, wherein each Hadoop cluster user processes its own data model on a data mart cluster according to a second data storage architecture, and the data of the data mart cluster originating from the data warehouse cluster.

The Digital Analytic Patient Reviewer (DAPR) for COVID-19 Data Mart Validation

Abstract: ObjectiveTo provide high-quality data for COVID-19 research, we validated COVID-19 clinical indicators and 22 associated computed phenotypes, which were derived by machine learning algorithms, in the Mass General Brigham (MGB) COVID-19 Data Mart. Materials and MethodsFifteen reviewers performed a manual chart review for 150 COVID-19 positive patients in the data mart. To support rapid chart review for a wide range of target data, we offered the Digital Analytic Patient Reviewer (DAPR). DAPR is a web-based chart review tool that integrates patient notes and provides note search functionalities and a patient-specific summary view linked with relevant notes. Within DAPR, we developed a COVID-19 validation task-oriented view and information extraction logic, enabled fast access to data, and considered privacy and security issues. ResultsThe concepts for COVID-19 positive cohort, COVID-19 index date, COVID-19 related admission, and the admission date were shown to have high values in all evaluation metrics. For phenotypes, the overall specificities, PPVs, and NPVs were high. However, sensitivities were relatively low. Based on these results, we removed 3 phenotypes from our data mart. In the survey about using the tool, participants expressed positive attitudes towards using DAPR for chart review. They assessed the validation was easy and DAPR helped find relevant information. Some validation difficulties were also discussed. Discussion and ConclusionDAPRs patient summary view accelerated the validation process. We are in the process of automating the workflow to use DAPR for chart reviews. Moreover, we will extend its use case to other domains.

Agent Based Architecture in Distributed Data Warehousing

Abstract: The distributed data warehousing is mainly based on how the data is used in the dynamic data distribution on a set of servers. Currently Query cycling process is used in distributed data warehousing for searching the relevant information from a large database. In this Process of query cycling, if the searching query is not in the required data mart then this agent will automatically redirects that request to the other data marts for searching queries, until it found. But the network load and execution time is more and the data management also needs the collaboration and interaction between the machines in order to reply the user queries. So in our approach we will use multi agent based architecture in distributed DWH. The data distribution is different from the classical one which depends on the data use. The distribution consists in distributing data when the server reaches its maximum storage capacity limit. And we will use an individual buffer for storage of results. Now, Client has no need to be connected with dispatcher all the time to get result. The result will be stored in its own buffer by dispatcher.

Data model transformations: relational to dimensional

Abstract: The paper extends the Conceptual Dimensional Fact Model to support the modeling of data marts by formalizing patterns of graph transformations from a relational data base schema to a data mart schema, and by standardizing all visual representations using the Idef1X standard notation and a single supporting case tool. The proposed modeling and automation approach has the potential to significantly speed up prototyping, improve quality of design documentation, and allow verification by developers and validation by users.