Keywords: Data warehouse, data mining, Multidimensional OLAP, virtual warehouse, Concept Hierarchies, Bitmap Indexing meta data, multiple mining functions.E. RajakumarR. RajaChaudhuri, S., Dayal, U., "An Overview of Data Warehousing and OLAP Technology", ACM SIGMOD Rec...
and a resulting shift in the art of the possible. As an example of this, in this post we look at Real Time Data Warehousing (RTDW), which is a category of use cases customers are building on Cloudera and which is becoming more and more ...
Data Warehousingis a total architecture for collecting, storing, and delivering decision support data for an entire enterprise. Data warehousing is a subset of Data Analytics and is described point by point in this series of tutorials. William (Bill) H. Inmon has provided an alternate and useful...
At the heart of such data management lies thedata warehouse– a pivotal part of everyIT infrastructurethat transforms raw information into actionable intelligence. This article explores the fundamental aspects of data warehousing, offering a comprehensive overview of its definition and intricate workings. ...
A Data Warehousing Project is defined as an initiative that involves the development and implementation of a data warehouse system to store, manage, and analyze large volumes of data for business intelligence purposes. AI generated definition based on: Agile Data Warehousing for the Enterprise, 2016...
Design for Research Data Warehouses The art of data warehousing has taken the industry by storm, and many of the same principles can be applied to the health-care enterprise. Thedata warehouseallows for rapid querying and reporting across patients, which unexpectedly is not available in most tran...
Overview of data synchronization solutions,Data Management:Data Transmission Service (DTS) allows you to synchronize data between data sources in real time. Typical scenarios include active geo-redundancy, geo-disaster recovery, zone-disaster recovery, c
Overview of Materialized Views【每日一译】--20121203 Materialized views are schema objects that can be used to summarize, compute, replicate, and distribute data. They are suitable in various computing environments such as data warehousing, decision support, and distributed or mobile computing:...
OLAP cubes can be considered as the final piece of the puzzle for a data warehousing solution. An OLAP cube, also known as multidimensional cube or hypercube, is a data structure in SQL Server Analysis Services (SSAS) that is built, using OLAP databases, to allow near-instantaneous analysis ...
Data is the lifeblood of any organization. In today’s world, organizations recognize the vital role of data in modern business intelligence systems for making meaningful decisions and staying competitive in the field. Efficient and optimal data analytic