cubos olap

Converting OLTP data to provide acceptable performance in an OLAP system requires the following procedures to be performed: Merging data You must be able to incorporate all relevant information about a specific project (product, customer, employee) from multiple OLTP systems into an OLAP system. The merge process must address the problem of coding differences between different OLTP systems. For example, a

In Oracle database systems, many people are not aware of what their business type is, and are beginning to blindly seek optimization methods, often using OLAP methods in OLTP, or OLTP methods used in OLAP. Such use, sometimes, performance without any improvement, or even greatly affect the performance, get counterproductive effect. So, before you optimize your system, figure out your business type.1. What i

from data warehouse is the biggest purpose of establishing data warehouse and using data mining. The essence and process of both are two things. In other words, data warehousing should be established first, and data mining can be carried out efficiently, because the data contained in the Data Warehousing itself is clean (No erroneous data involved) and complete, and integrated. Therefore, the relationship between the two may be interpreted as "Data Mining is a process and technology for finding

First, set OLAP, which can be accessed by machines in the LAN through the HTTP protocol. Then, use Excel to connect to OLAP through HTTP. The settings are as follows: 1. Create an OLAP site 1. Find the c: \ Program Files \ Microsoft SQL Server \ msas10.mssqlserver \ OLAP \ bin \ ISAPI Directory, which contains two fi

OLAP (on-line analysis processing) enables analysts, administrators, or administrators to quickly, consistently, and interactively access information from multiple perspectives, this gives you a better understanding of the data. OLAP is designed to meet decision-making support or specific query and report requirements in multi-dimensional environments. Its core technology is the concept of "dimension. Dimen

1. First of all, let's not take big data to say things, first analysis of OLAP and OLTP.OLAP: Online analytical Processing (OLAP) systems are the most important applications of data warehouse systems and are specifically designed to support complex analytical operations, with a focus on decision support for decision makers and senior management.OLTP: Online transaction processing (oltp,on-line Transaction p

MySQL and OLAP: analyticdb SQL query best practices for multi-dimensional analysis. the rough and fast solution is to use ROLAP (relational OLAP. Data is stored in MySQL after Dimensional Modeling. The ROLAP engine (such as the open-source Mondrian) is responsible for converting OLAP requests into SQL statements and submitting them to the database. The

The differences between online transaction processing (OLTP) and Online Analytical Processing (OLAP) are mainly distinguished by the following five points. User and system orientation: OLTP is customer-oriented, and OLAP is market-oriented for transaction and query processing. It is used for data analysis. data content: OLTP system manages current data. the OLAP

OLAP learning and instance Building Theoretical preparation: I. OLAP 1. What is OLAP? OLAP (on-lineanalysis processing) is a fast analysis technology that shares multidimensional information. OLAP uses multidimensional database technology to enable users to observe data from

Online transaction Processing OLTP (on-line transaction processing) primarily performs basic, daily transaction processing , such as the increase, deletion, modification, and checking of database records . For example, in a bank to access a payment, is a transaction transaction. The features of OLTP typically include:1. High real-time requirements;2. The amount of data is not very large;3. Transactions are generally deterministic, so OLTP is access to definitive data (e.g., deposit and withdrawa

Oltp:on_line Transaction processing online transaction processing Olap:on_line Analytical processing online Analytical processing OLTP, as its name suggests, focuses on business processes. OLAP is specially designed to support complex analysis operations, focusing on decision support for decision makers and senior managers, it is possible to quickly and flexibly perform complex query processing of large amounts of data, and provide the query results

a normalization of the star mode.. In snowflake mode, dimension tables in star mode are further layered. The original dimension tables may be extended to small fact tables to form partial "hierarchical" areas.It minimizes data storage and combines smaller dimension tables to improve query performance. The snowflake mode increases the number of tables that users must process and the complexity of some queries. But this can make the system more professional and practical, while reducing the gene