olap functions

amount of customer data, and then automatically divide the customer into several groups (automatic category Detection), and display the consumption characteristics of each group, in this way, the decision makers can clearly determine the consumption habits of different customers, and develop promotion plans or advertising plans.If the above functions are implemented by information Bi applications alone, the decision makers need to perform a lot of

Abstract: Based on the Data Storage Technology of ODS in the middle layer of DB and DW, a real-time OLAP system for commercial systems is designed from the perspective of application. ODS is used to overcome the problem that DW is too bloated for decision-making and is not suitable for enterprises' real-time middle-level decision-making. Key words: Data Warehouse (DW), operational data storage (ODS), Real-Time Online Analytical Processing (

OLTP, also called online transaction processing ( Online Transaction Processing ), represents a very high-transactional system, typically a highly available online system, with small transactions and small queries as the primary evaluation of their systems, generally looking at the number of executions per second Transaction Execute SQL . In such a system, a single database tends to process Transaction more than hundreds of, or thousands of, of statements per second, with Select thousands of or

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

Optimizing the performance of online analysis processing is very important, and fortunately, some tools can help monitor and improve the operation of OLAP databases. Microsoft SQL Server Analytics Services (SSAS) provides a powerful engine for creating and managing data mining applications and online analytical processing systems, and you should carefully monitor and optimize OLAP databases and potential

SQL Server skills: how to monitor and optimize OLAP Databases It is very important to optimize the performance of online analysis and processing. Fortunately, some tools can help monitor and improve the operation of OLAP databases. The Microsoft SQL Server Analysis Service (SSAS) provides a powerful engine used to create and manage data mining applications and online analysis and processing systems. To ac

On-Line Analytical Processing (OLAP) system is the main application of Data Warehouse system, specially designed to support complex analysis operations, focusing on decision support for decision-makers and senior managers, and can quickly and flexibly carry out complex query processing of large amount of data according to the requirements of analysts. And in an intuitive and understandable form of the query results provided to decision makers, so that

transaction processing, is our usual database.OLTP often has a large number of concurrent additions and modifications that change at any time, contain large amounts of data, and have complex structures.When we load OLTP into the DW, it is generally no longer modified to update periodically as the data grows, rather than with frequently occurring transactions. The structure and security are also simplified to improve the efficiency of analytic queries rather than transactional processing.There i

analyzed, and MDX only supports a single model. Finally, take a look at the slices: this is the same as filtering in SQL. However, because the OLAP data is three-dimensional, multidimensional, to become a plane, you need to cut ah, cut ah, some do not need to show the dimension set fixed value (that is, cut). Note: When you do not specify any slices, the general implementation is to make the default member value of the dimension that does not appear

What is OLAP and OLTP Source: http://www.itisedu.com/phrase/200604230827105.html Http://www.huihoo.com/database/dw2.html Today's data processing can be roughly divided into two categories: online transaction processing OLTP (on-line transaction processing), Online Analytical Processing OLAP (on-line analyticalProcessing ).OLTP is the main application of traditional relational databa

The concept of online analytical processing (OLAP) was first proposed by the father of the relational database, E.f.codd, in 1993, and he also presented 12 guidelines on OLAP. OLAP has aroused a great deal of response, OLAP as a class of products and online transaction processing (OLTP) clearly distinguished. Today's

measure are located To write query statements in the MDX language. This logical model actually provides the following concepts: cubes, dimensions, hierarchies, levels, and members ). The schema file is an XML file for editing the schema. Form the logical model and the physical model of the database in this file. 3.2.2 logical structure of Schema 3.2.2.1 a cube is a collection area of dimensions and measurements. In cube, dimension and measure share a fact table. Example: 3.2.2.2 a measurement,

The concept of online analytical processing (OLAP) was first proposed by the father of the relational database, E.f.codd, in 1993, and he also presented 12 guidelines on OLAP. OLAP has aroused a great deal of response, OLAP as a class of products and online transaction processing (OLTP) clearly distinguished. Today's

(Reproduced from Peking University Gaoke website, http://www.pku-ht.com /) The concept of Online Analytical Processing (OLAP) was first proposed by E. F. codd, the father of relational databases, in 1993. He also proposed 12 principles for OLAP. The proposal of OLAP has caused a great deal of response. as a type of product,

First, Basic Concepts Dimension (Dimension): is a specific angle that people observe data, is a kind of attribute when considering a problem, attribute set constitutes a dimension (Time dimension, Geography dimension, etc.). Level of dimension: people looking at a particular angle of data (that is, a dimension) can also have various descriptive aspects of varying degrees of detail (Time Dimension: date, month, quarter, year). Member of the dimension: A value of the dimension that is a de

In DW/BI systems, relational databases are the best place to store and manage data. But the relational database itself is not intelligent enough. The relational database lacks the following features: Rich metadata to help users navigate the data and create queries. Powerful analytic calculations and functions, defined in context-sensitive query statements. Outstanding, consistent query performance in a variety of ad hoc queries.

For more information about the RANET. uilibrary. OLAP project, see my other article here. For whatever reason, sometimes we want to debug on the Silverlight client to view the request parameters sent to the server, so as to better locate the problem. The following method is based on RANET. uilibrary. OLAP project, add a debugging window to its client: Add silverliclient client DEBUG feature in RANET. uilib

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

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

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