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In this short note, we shall briefly summarize this own follow-up research as well as the impact on research and practice, in the three areas of data quality, data warehouse process engineering, and automated model management. We end with some ongoing research questions and open challenges.
A data warehouse is a system that aggregates data from multiple sources into a single data store to help support analytics, business intelligence and AI.
7 lis 2022 · This article presents a detailed overview of the roles of data warehouses and data lakes in modern enterprise data management. We detail the definitions, characteristics and related works for the respective data management frameworks. Furthermore, we explain the architecture and design considerations of the current state of the art.
14 sie 2024 · A data warehouse, is a centralised repository and information system used to develop insights and guide decision-making through business intelligence. A data warehouse stores summarised data from multiple sources, such as databases, and employs online analytical processing (OLAP) to analyse data.
15 gru 2017 · As a result of research, the concept of data warehousing (DW) was introduced as a large data repository, in which data can be stored in a well structured manner as well as to help in analyzing the stored data.
18 wrz 2024 · Data Warehousing: A Solution for Business Pain Points. •. Main Data Warehouse Characteristics. •. Key Components of a Data Warehouse. •. Understanding the Benefits of Data Warehousing. •. The Foundation of Your Data Warehouse. •. Data Warehouse Tools and Utilities. •. Examples of Well-Known Data Warehouses. •. Data Warehouse vs. Data Lake. •.
27 kwi 2021 · A data warehouse is a structured organization of all available data (ideally) in the company. Using data warehouses, data scientists can answer important business questions and analyze the business performance.
