indexing in data warehouse

Basic concepts: 1. Multi-dimensional dataset: a multi-dimensional dataset is the main object in Online Analytical Processing (OLAP) and a technology that allows quick access to data in a data warehouse. A multi-dimensional dataset is a collection of data. It is usually constructed from a subset of a

Tags: targe LAN causes HTTP extensions three-month partial PST calculationIn short, the database is a transaction-oriented design, the Data Warehouse is a theme-oriented design.Databases generally store online transaction data, and data warehouses typically store historical data.Database design is to avoid redundancy a

Label:In short, the database is a transaction-oriented design, the Data Warehouse is a theme-oriented design.Databases generally store online transaction data, and data warehouses typically store historical data.Database design is to avoid redundancy as far as possible, generally adopt the rule of conforming to the pat

server|sqlserver| data The construction and analysis of SQL Server Data Warehouse (i) Basic concepts: 1. Cubes: Cubes are the primary object in online analytical processing (OLAP) and are a technology that allows fast access to data in a data

In general, two monitored operational components in a data warehouse environment are the use of data and data stored in the Data warehouse. Monitoring data in a

Data Warehouse is a comprehensive technology and solution based on data management and application. The successful implementation of data warehouses has a significant impact on the cultivation of a culture of knowledge sharing. Currently, the data

This article discusses two common methods in data warehouse model design. In the application environment of data warehouses, there are two types of load: one is to answer repetitive questions, and the other is to answer interactive questions. Dynamic query has obvious interactive features. This interaction process is often called

The common dwh architecture is as simple as figures 2 and 3. Generally, for an enterprise, the data lifecycle is 5-7 years, especially for detailed data. The lower the data granularity level, the shorter the lifecycle, the higher the data granularity and the longer the lifecycle. For the flow account

Cloud computing and data warehousing are a reasonable couple. Cloud storage can be scaled on demand, and the cloud can contribute a large number of servers to a specific task. The common function of Data Warehouse is the local data analysis tool, which is limited by calculation and storage resources, and is limited by

Just a few days ago, a user participated in a job interview for an enterprise. He applied for the DBA of the company and was responsible for data analysis. This company successfully completed the process. Until the person in charge of the company. The owner only gave him an interview question: Let's talk about the differences between the database and the data warehouse