One of the previous articles-the Data warehouse multidimensional data model already provides a brief description of the definition and structure of an overly-dimensional model, as well as the concept of the fact table and the dimension table (Dimension table). Multidimensional data model, as a new logical model, gives the new organization and storage form of data, and the advantage of the analysis is the effective operation and processing based on the model, which is
Overview
One of the most flexible controls in our library is the grid control. viblend DataGrid for Silverlight is the first fully functional OLAP grid for Silverlight. it brings together the features of traditional data grid controls, hierarchical grids and Excel-like tables. viblend DataGrid for Silverlight supports both data bindings and complete Unbound mode. you can visualize a database table, bind
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,
Outstanding Features
Allows for rapid, direct analysis of comprehensive financial, mathematical and statistical functions and computational functions
Combine the flexibility of relational databases with the high performance of multidimensional storage to provide a web-enabled platform, easy access to enterprise-wide information enabling rapid application development and data modeling enables multiple users to simultaneously read and write to "what if" applications to support third-party analys
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
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
Introduction to OLTP and OLAP
Data processing can be broadly divided into two broad categories: online transaction processing OLTP (on-line transaction processing), online analytical processing OLAP (On-line Analytical Processing). OLTP is the main application of the traditional relational database, mainly basic, daily transaction processing, such as bank transaction. O
Kylin is a set of OLAP systems developed by ebay, and unlike Mondrian, it is a MOLAP system that is primarily used to support data analytics businesses in the big data ecosystem, It mainly uses the Precomputed method to cache the user-defined multidimensional cubes into hbase (HBase is currently only supported), which is used for both Mondrian and Kylin, and finds that the two systems are a trade-off between time and space, Mondrian is a ROLAP system
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
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
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 (
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
throughput is often dependent on the number of disks, this time, Cache basically no effect, the database read-write type is basically db file scattered read with direct path read/write . Should try to use more than the number of disks and relatively large bandwidth, such as 4Gb the fiber interface.In the OLAP system, partitioning technology and parallel technology are often used.The importance of partitioning technology in the
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
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
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