The rudder, which is a part of the steering apparatus of a boat or ship that is fastened outside the hull, usually at the stern, is one of the most important parts of a vessel\u00b4s structure. The preparation process as well as the installation one, are crucial tasks to guarantee its strength, quality and future performance in the sea.<\/p>\n\n\n\n
A Data Warehouse, defined as digital containers of a wide variety of information in the forms of dataframes, dashboards, visualizations and reports, are designed to support business intelligence analytics and, usually, storage, and summarize large amounts of historical data of operational processes of organizations.<\/p>\n\n\n\n
The quantity of dashboards and visualizations contained into a Data Warehouse depends on the size and the complexity of the data used, and on the technical and managerial requirements of end-users.<\/p>\n\n\n\n
It is crucial that developers and data scientists define and prepare, carefully, the heart of a Data Warehouse: the most important dashboard that reflects the most important information contained. Why? Because it is essential to build and install the Data Warehouse’s rudder.<\/p>\n\n\n\n
In naval engineering, the rudder casting process consists of the preparation and installation of the rudder outside a vessel\u00b4s hull. After building the rudder part from steel, workers cast it in huge industrial ovens. Still hot, they immerse such a steel piece into a special chemical solution in order to increase its strength and durability. Finally, at the end of the process, they install the rudder into the proper site in the vessel\u00b4s hull.<\/p>\n\n\n\n
In data science, specifically within the construction process of a Data Warehouse, it is essential to define the center or the heart of it. Usually, data scientists define it as the most important dashboard or the one the contains the most significant and relevant information for end-users. The whole Data Warehouse, in future updates, will grow and expand around the data contained in the mentioned center.<\/p>\n\n\n\n
The center or the heart of a Data Warehouse will define its particular brand in terms of the usage and importance for end-users. Also, it will define the path for future improvements and updates. But the most important issue for defining it is because it will define the type of data that is absolutely relevant to show within the whole Data Warehouse, and, definitely, must not be missing in the tool.<\/p>\n","protected":false},"excerpt":{"rendered":"
In data science, specifically within the construction process of a Data Warehouse, it is essential to define the center or the heart of it.<\/p>\n","protected":false},"author":1183,"featured_media":200965,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[339,338,341],"tags":[10414,806,16541,16542],"contributors-categories":[15500],"class_list":{"0":"post-200851","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-data-science","8":"category-ibkr-quant-news","9":"category-quant-development","10":"tag-data-analytics","11":"tag-data-science","12":"tag-data-warehouse","13":"tag-rudder-casting-process-data-science","14":"contributors-categories-roberto-delgado-castro"},"pp_statuses_selecting_workflow":false,"pp_workflow_action":"current","pp_status_selection":"publish","acf":[],"yoast_head":"\n