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What does the granularity in the data warehouse mean? Granularity is one of the most important aspects of data warehouse design. Granularity refers to the level at which the
Create | data How to create a successful data Warehouse (Warehose), the following story will tell you! The company's ' s ' Warehouse project began with a casual conversation between several executives on their way to LUN Ch. The people involved were the IT manager for decision support as as and as several members of
This article outlines the general process of using OWB to create a data warehouse. Oracle's OWB is one of the three most current ETL products. OWB can not only complete data extraction, conversion and loading, but also help users create ROLAP (relational online analysis Process) and MOLAP (multidimensional online) in Oracle database Analysis Process)
0x00 Preface The following content, is the author in the study and work of some summary, of which the concept of most of the content from the book, the practical content mostly from their own work and personal understanding. Due to the lack of qualifications, there will inevitably be many mistakes, I hope to criticize. Overview The Data warehouse contains a lot of content, which can include architecture, m
Data warehouse design purpose and data warehouse design purpose The purpose of data warehouse design or the criteria for measuring success: 1. The data
Tags: drop ora way and data test var sub glob In the recent study of Oracle statistics, the method for collecting statistics is as follows:Dbms_stats. Gather_table_stats (Ownname VARCHAR2,---owner name tabname VARCHAR2,---table name partname VARCHAR2 DEFAULT NULL,---The partition name to parse Estimat E_percent number DEFAULT NULL,---the scale of the sample block_sample BOOLEAN default FALSE,---whether block parsing method_opt VARCHAR2 DEFAULT ' for a
First, what is a data warehouse The traditional data warehouse concept is that data warehouse is a structured data environment for decision Support System (DSS) and on-line analysis app
Introduction to ETL technology: Introduction to ETL, data warehouse, and etl Data WarehouseETL is the abbreviation of Extract-Transform-Load. It is used to describe the process of extracting, transforming, and loading data from the source to the target. ETL is commonly used in data
1. The concept of Data Warehouse began in the 1980s S and first appeared in the book William H. Inmon, known as "the father of Data Warehouse. As people deeply recognize and constantly improve the research, management, and maintenance of large data systems, after summing up,
3 guys came to a business. The first (data Warehouse) was burly: He brought history and experience, and he could say that most of the words were true. But, in many ways, it is bloated and wasteful in other ways, and people are tired of the costs of the various outcomes. Apache Hadoop entered the same building, claiming to take over the entire market. He preaches big dat
Tags: OLAP online analytics for Data warehouse applicationsRelated articles:Data Warehouse Application (i): Data Warehouse model designData Warehouse Application (ii): Data extraction,
information and external information of the enterprise.(2) The storage and management of data is the core of the whole data Warehouse system. Data warehouses can be divided into enterprise-level data warehouses and departmental data
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
PHP-based data warehouse receiving Program (1): php-based data warehouse receiving program A friend asked me to help me develop a program for collecting news information a few days ago. I took some time to write a PHP version and recorded it as needed. When it comes to collection, it is nothing more than obtaining info
, reflecting the division of dimension layers, which can be a constraint for analyticdb queries. This is a difference between data warehouse and operational applications in data model design. The number of dimension table levels depends on the query granularity. In the actual business environment, the multi-dimensional
PHP-based data warehouse receiving Program (2): php-based data warehouse receiving program In the previous article, the Program for collecting data into the database based on PHP (ii) mentions the list data on the news information
Microsoft vs. Yahoo! The long-running purchase war may put many people tired of news. But today we see this about Yahoo! The technical news is worth reading: Size matters: yahoo claims 2-petabyte database is World's biggest, busiest. Yahoo! VP Waqar Hasan of disclosure Yahoo! The current data warehouse capacity is 2 Pb. It is used to analyze 0.5 billion of user access behavior every month and process 24 bil
should be detailed and clear, reflecting the division of dimension layers, which can be a constraint for analyticdb queries. This is a difference between data warehouse and operational applications in data model design. The number of dimension table levels depends on the query granularity. In the actual business envir
, reflecting the division of dimension layers, which can be a constraint for analyticdb queries. This is a difference between data warehouse and operational applications in data model design. The number of dimension table levels depends on the query granularity. In the actual business environment, the multi-dimensional
The life cycle approach provides a roadmap for the development of data warehouses, and the overall structure and steps of the life cycle approach are Define Business requirements Technical path Technical Architecture Design Selection and installation of products Data path Dimension modeling Physical design ETL Design and development Bi app Path
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