Database And Data Warehouse

Intermediary transaction SEO diagnosis Taobao guest Cloud host technical Hall The purpose of the data Warehouse is to build an integrated data environment for analysis, and to provide decision support for enterprises (Decision Support). In fact, the data warehouse itself does not "produce" any data, at the same time does not need to "consume" any data, data from the outside, and open to external applications, which is why called "Warehouse", not called "factory" reasons. Therefore, the basic structure of the data warehouse mainly contains the data inflow and outflow process, can be divided into three layers-source data ...

The purpose of data warehouse is to build an integrated data environment oriented to analysis, and to provide decision support for enterprises (Decision-support). In fact, the data warehouse itself does not "produce" any data, at the same time does not need to "consume" any data, data from the outside, and open to external applications, which is why called "Warehouse", not called "factory" reasons. Therefore, the basic structure of the data warehouse mainly contains the data inflow and outflow process, can be divided into three layers-source data, data Warehouse, data application: From the graph can be seen data warehouse data from ...

The intermediary transaction SEO diagnoses Taobao guest stationmaster buys cloud host technology Hall the article before--the website data analysis Some questions 2 mainly collates the bi related question, this article mainly wants to organize some data warehouse related question. Because I recently looked back at some data warehouse information and books, want to put forward as well as the current problems to come up (blog about data Warehouse related content Please refer to the website Data Warehouse this directory), at the same time they also have the knowledge of the data warehouse under the reorganization and understanding, and for a long time ...

I think the data Warehouse can help the enterprise to deal with the data problem in three ways: first, in an enterprise Data warehouse, you divide your data according to the subject area, which is often more stable. 　　Organizations that want to understand the "big data" concept need to make a choice between the traditional data warehouse concept and the existing Data Warehouse architecture, or the increasingly popular open source Hadoop distributed processing platform, or the combination of the two. Those who want to move from simple BI reports to deep data mining and predictive analytics ...

Internet giants Google and Facebook have achieved huge value by managing and analyzing big data, prompting CIOs to ask whether emerging technologies can create brilliant results within their own businesses. The idea is partly encouraged by industry analysts predicting that big data will grow at breakneck speed. Wikibon predicts that by 2015 the big data market will jump from $5 billion trillion in 2012 to more than $30 billion trillion, up to $53.4 billion in 2017 (where you can ...).

Integrated equipment (appliance) and large data analysis features have been the focus of attention in the latest 2012-year Data Warehouse Magic Quadrant report of Gartner, where major data warehouse vendors have increased their input in their offerings. This article will be the current industry's major manufacturers and products to make a comparison, end users can also be based on their own needs to evaluate the data Warehouse products. After acquiring Aster Data Bae last year at a price of 263 million dollars, Teradata's product line gets ...

Storing them is a good choice when you need to work with a lot of data. An incredible discovery or future prediction will not come from unused data. Big data is a complex monster. Writing complex MapReduce programs in the Java programming language takes a lot of time, good resources and expertise, which is what most businesses don't have. 　　This is why building a database with tools such as Hive on Hadoop can be a powerful solution. Peter J Jamack is a ...

Over the past three years, the Hadoop ecosystem has expanded to a large extent, with many major IT vendors introducing Hadoop connectors to enhance the top tier of Hadoop or the Hadoop release that the vendor uses. 　　Given the exponential growth in the deployment rate of Hadoop and the growing depth and breadth of its ecosystems, we wonder whether the rise of Hadoop will lead to the end of traditional data warehousing solutions. We can also put this issue in a larger context to discuss: to what extent, large data will change ...

Recently, the world-renowned 12th annual Teradata Data Warehouse and Enterprise Analysis Summit held in Suzhou, chapter of "The ultimate interpretation of the value of data" as the theme, in-depth discussion of how enterprises to fully utilize the latest data warehouse and enterprise analysis technology, with the help of data sources to provide insight to quickly formulate the best business decisions, grasp the business opportunities. At the press conference, Teradata dynamic Enterprise Data Warehouse platform 6690 (Active EDW 6690) platform began to supply, provide the latest generation of hybrid storage, further enhance the capacity of data warehousing, help ...

As two of the most popular technologies in the field of information management, the hardware architecture of database integration machine and large data technology is basically the same, but the software system has the essential difference, which leads to the different characteristic performance. With the rapid growth of enterprise data and the continuous improvement of users ' requirements for service level, the traditional relational database technology has shown obvious lack of ability in production practice for a long time. How to obtain high availability of massive data at reasonable cost has become a major challenge in modern it field. In order to meet this challenge, in recent years, it market ...