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use these technologies to solve their own business problems. Yang Shunsheng: We are a real business of data Warehouse products, from our experience in contact with domestic enterprises, data warehousing technology in China has not been well developed, mainly in the following reasons: First, China's information infrastructure is relatively imperfect, such as the
Express is not high enough, Oracle 8i and express need to replicate metadata, if Oracle Discoverer (or Bo) need to access the rollup data, It is difficult to maintain the summary data in both Oracle and Express. Notably, the Oracle 9i, which has just come out, is an important feature of OLAP and data mining. Sybasesybase provides a
stressed the need for a data model. Why is the data model so important? First, we need to understand the history of Data Warehouse Construction. The development of data warehouse has gone through three steps: Simple report stag
Brief introduction The business environment is changing rapidly, and so is the type of business data. A successful Data warehouse solution is based on flexible design that adapts to changing business data. The architecture of data Wareh
analytical processing): Online Analytical Processing OLAP was proposed by E. F. codd in 1993.Definition by the OLAP Council: OLAP is a software technology that enables analysts to quickly, consistently, and interactively observe information from various aspects to gain an in-depth understanding of data, this information is directly converted from raw data. They reflect the real situation of the
ProcessingOLAP was proposed by E.f.codd in 1993.OLAP Council definition: OLAP is a software technology that enables analysts to quickly, consistently and interactively observe information from all aspects in order to achieve an in-depth understanding of the data, which is translated directly from the original data, and they reflect the real situation of the enterprise
/migration/after modifying the database account password in the Migration.cfg filesudo docker build-t Migrate-tool.5. run a staging database container (Note:/data/database the directory where you set up the Mount database/path/to/backup data Backup) This datasudo docker run-ti--rm-v/data/database:/var/lib/mysql-v/path/to/backup:/harbor-migration/backup migrate-to
management of metadata generated by tools and databases guarantees the establishment of a truly enterprise-class data warehouse. Warehouse Control Center is a data Warehouse metadata management tool for
Brief introduction DB2 Warehouse combines the powerful data support of IBM DB2 and a set of IBM Business Intelligence (Business Intelligence) products to provide a comprehensive business intelligence platform and its application tools, These components enable organizations to build and deploy analysis solutions for next-generation data warehouses. The article w
mining the data resources of the existing database effectively, and serving the needs of the senior management decision analysis of the enterprise. However, it is necessary to explain that the development of data Warehouse system is a process of continuous circulation and feedback, which makes the system grow and perf
managed primarily around a mirrored warehouse (registry). During the lifecycle of an app, whether a developer or CI system publishes an image, or if a tester or an OPS person downloads the image, it is done through a mirrored warehouse. A mirrored warehouse can use a public SaaS service, such as a Docker Hub. The advantage of public service is that it can be use
existing database system. It aims to effectively extract, integrate, integrate and mine the data resources of existing databases, it serves the needs of enterprise leadership management decision-making analysis. However, it should be noted that the development of a data warehouse system is a process that continuously
Microsoft's Parallel Data Warehouse (Parallel data Warehouse, abbreviated PDW) was released last year with SQL Server 2008 R2, designed to compete with Oracle Exadata and Teradata. PDW a true sense of the ability to mix workloads, users can extend
a common subject or business field. The following describes how to create an information package chart through information packaging technology to determine the topic and metadata in the data warehouse.3.4.1 information packaging technology1. Basic use of information packaging technology The information packaging method is a top-down design method, which focuses on one or more topics of an
dw solution, and teradata began to provide its dw product on suse-based OS-running hardware. The advantage of closed hardware is that it is out-of-the-box. It has been strictly tested by the manufacturer and has a high security level. Open Hardware requires the enterprise to possess powerful technical strength and can have a hardware, storage, A team with comprehensive knowledge and capabilities of the ope
Data WarehouseThe purpose of the Data Warehouse is to build an integrated data environment for analysis, providing decision support for the Enterprise (decision supports). In fact, the data wa
First, the Data WarehouseThe standard definition of the Data Warehouse concept is relatively high in the industry, as proposed by Bill Inmon, the father of the Data Warehouse, in the book "Building The Data
First, the Data WarehouseThe standard definition of the Data Warehouse concept is relatively high in the industry, as proposed by Bill Inmon, the father of the Data Warehouse, in the book "Building The Data
task, each business system is separated from each other, and data in Data Warehouse is organized according to certain subject domain. A topic is an abstract concept that refers to the focus that users are concerned with when using a data warehouse for decision-making, and a
first, the use of Sqoop data extraction1. Sqoop IntroductionSqoop is a tool for efficiently transferring large volumes of data between Hadoop and structured data storage, such as relational databases. It was successfully hatched in March 2012 and is now the top project of Apache. Sqoop has SQOOP1 and Sqoop2 two generations, and the final stable version of SQOOP1
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