Data Warehouse Uses

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 ...

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 ...).

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 ...

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 ...

It seems that the word "big data" hangs on everyone's lips. The discussion around big data has almost completely overwhelmed the traditional http://www.aliyun.com/zixun/aggregation/8302.html "> Data Warehouse." Some big data enthusiasts even boldly predict that in the near future, all enterprise data will be hosted by a system based on Apache Hadoop, and the Enterprise Data Warehouse (EDW) would eventually die out. Anyway, the traditional data Warehouse ...

Most data warehousing projects will bring huge investment. For example, the Nordbanken bank, a European lender, spent 100 million euros to build a data warehouse system for data unification across regions and business units. However, in the face of the same business challenges, another European bank, UniCredit, has taken a radically different approach. "Our philosophy is to look for space in other projects, as long as there are any other projects," UniCredit chief financial officer Criscito Ambrisi said in an interview.

This method allows the architect to complete the build locally to provide the expected workload and overflow to the on demand cloud HPC to cope with the peak load. Part 1th focuses on how system builders and HPC application developers can extend your systems and applications most efficiently. Processor cores with custom extensions and shared memory the external HPC architecture of the internet is rapidly being replaced by on-demand clustering, which leverages off-the-shelf general-purpose vector collaboration processors, converged Ethernet (each link Gbit or higher), and multicore headless ...

Cloud computing and data warehousing are a reasonable couple. Cloud storage can be scaled on demand, and the cloud can contribute a large number of servers to a specific task. The common function of Data Warehouse is the local data analysis tool, which is limited by calculation and storage resources, and is limited by the designer's ability to consider the new data source integration. If we can overcome some of the challenges of data migration, the problem can be solved by moving a data warehouse and its data analysis tools from dedicated servers in the datacenter to cloud-based file systems and databases. Cloud data management is often involved in loading and maintaining text in Distributed File systems ...

2013 Teradata Big Data Summit was held in Beijing International Hotel recently. Industrial and Commercial Bank of China, deputy general manager of the Ministry of Information Technology, made a speech at the meeting, introduced how ICBC is using data and information to enhance the level of management and business value. ICBC has now become China's largest commercial bank. According to Zhang, ICBC in Beijing and Shanghai have built data centers, the current branches and affiliated institutions are fully to the direction of electronic development. From the statistical data, the first half of 2012, ICBC mobile phone Bank new customers to increase customer turnover rate to 18%, the turnover of 300% year-on-year growth.