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 a department that had just Deci Ded to install a data
Linux version number: 14.04.1-ubuntu x86_64
Backup server address is: 172.29.71.59, backup root path is/home/backup
1.git Code warehouse automatic daily backup:
Server address: 172.29.71.111,git specified directory: 00.apps, Backup path is:/home/backup/codeserver_111
Step One:
cd/home/backup/codeserver_111
git clone--mirror Git@172.29.71.111:00.appsgit clone--mirror copies a git library that contains the latest remote branch as well as a history sub
the data mart layer. Its biggest role is to solve the performance problems in data warehouse modeling. It is difficult for dimensional modeling to provide an abstract method to fully describe the complex relationships between real business entities. 3. entity modeling Entity modeling is not a common method in data warehouse modeling. It comes from a genre of philosophy. In a philosophical sense, the
often caused.
Another disadvantage of the dimensional modeling method is that, if you only rely on dimensional modeling, data source consistency and accuracy cannot be guaranteed, and at the bottom of the data warehouse, it is not particularly suitable for dimensional modeling.
Therefore, from the perspective of the author, the field of dimensional modeling is mainly applicable to the data mart layer. Its biggest role is to solve the performance prob
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) Data Warehouse objects, data quality management, business
Data warehouse design purpose and data warehouse design purpose
The purpose of data warehouse design or the criteria for measuring success:
1. The data warehouse must make the information of the Organization easy to access.
2. The data warehouse must display information of
WMS is a professional Warehousing Management Software Based on the construction and implementation experience of warehouse logistics management. Compared with traditional inventory management software, it not only includes basic functions such as normal inventory management, such as warehouse receiving and inventory check, but also focuses on the management of warehouse
git modifies the remote warehouse addressThere are three kinds of methods:1. Modify the commandGit remote origin set-url [url]2. Delete First and then addGit remote RM origingit remote add origin [url]3. Modify config file directlygit remote warehouse managementTo participate in the collaboration of any Git project, you must understand how to manage a remote repository. A remote repository is a project
Migration provides an opportunity to re-examine existing objective-c applications, as well as the Swift code to better optimize the architecture, logic, and performance of your application. Directly, you will use the previously learned mix and match and the interoperability between the two languages for incremental migration work. The Mix-and-match feature makes it easy to choose which features and functions to use with Swift and which are still imple
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 application data source. is a strategic set of all types of data that is supported by the decision making process at all levels of the enterprise.
In simple terms, the previous data
According to the warehouse picking requirements, the batch information of the warehouse receiving will be matched by lazygc520 at 2013-08-0709: 39: 09. the edited database is divided into three tables, kw, vp, three tables starting with st. The first two tables represent warehouse receiving, and those starting with st represent
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 warehouses, but its objects are not limited to data warehouses. What is ETL?
ETL is the abbreviation of the three English words "Extract Transform Load". The Chinese meanin
package diagram can be expressed in a similar way.(4) This step can be used to construct a star chart based on the information packaging graph, as shown in 3-26. Then, based on the actual situation, connect the detailed category object to the Star Graph to obtain the snowflake model of the enterprise data warehouse. For example, in the AdventureWorks Business Database, products have been hierarchically classified through the table "ProductCategory",
What is warehouse filling and warehouse filling?The behavior of buying a stock or fund again after the price falls below the price of the stock or fund is called replenishment. Effect of warehouse filling: lower
To lower the unit cost, so that it is expected to rebound and throw out after the warehouse filling, the pr
Objective-C: odd tricks -- use Chinese to write Objective-C; -- use Chinese objective-c
Technical lust refers to technologies and products that are too clever and useless.Reprinted please indicate the source http://blog.csdn.net/uxyheaven/article/details/46391771
We can use macros to define basic operators and types.
# Define plus + # define minus-# define multi
Brief introduction
Data integration is a key concept in the Data warehouse. The design and implementation of the ETL (data extraction, transformation and loading) process is an extremely important part of the Data Warehouse solution. ETL processes are used to extract business data from multiple sources, clean up data, then integrate the data, and load them into the Data
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 data, speed, data, variety, and a bunch of V-words that don't make much sense outside
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, enriching, and concentrating the experience of multiple lines of enterprise information, A more precise definition is provided for the
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, modeling, and methodologies. For specific work
CentOS installs software very conveniently using Yum, and Yum automatically installs dependencies on the software. But the source repositories that CentOS comes from are relatively old and not so full, so we can add third-party repositories and install newer versions of the software.Epel is a repository maintained by the Fedora community with more than 10,000 software, and CentOS can install the Epel warehouse using yum install Epel-release, after ins
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