Data Warehouse Terms

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 ...

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 ...

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 ...

Apache Hadoop is the foundation of a new generation of data warehouses. Hadoop is used by companies as a strategic role in their current warehousing architectures, such as extraction/transformation/loading (ETL), data staging, and unstructured content preprocessing. I also see Hadoop as a key technology in a new generation of large-scale parallel data warehouses in the cloud, and Hadoop complements today's warehousing techniques and low latency streaming platforms. At IBM, we look forward to the next few years, Hadoop and data warehousing technology can be more perfect for each other ...

In the large data age, the Hadoop distributed processing architecture brings new life and challenges to it, data management, and data analysis teams. 　　With the development and expansion of Hadoop ecosystem, enterprises need to be ready for the rapid upgrading of technology. Last week, the Apache Software Foundation just announced a formal GA for Hadoop 2.0, a new version of Hadoop that will bring a lot of change. With HDFs and java-based MapReduce as core components, the early adopters of Hadoop ...

This is the fund's most important profit source for the first quarter. The Shanghai Composite Index rose 30.34% in the first quarter, two to May 14, and up 11.24%. and the market average price at the end of last year for 7.32 Yuan, a quarter of 10.61 yuan, May 14 when the 11.5 yuan, the increase of 45% and 8.39% respectively. It can be said that the Shanghai Composite index was markedly weaker in the first quarter than stocks, and in the two quarter it began to be stronger. Therefore, the nature of the first quarter of the market should be a large number of new funds to promote the stock market, and the two quarter, especially since May, is to fund the generation ...

The traditional business intelligence system only serves for the decision person, and is affected by the security factor, the analysis data can only be reflected in the local user terminal, but manifests the way almost is the ordinary computer. With the rapid development of computing and Internet technology, the mobility and activity space of sales, market and decision makers are more and more, more and more managers involved in decision-making, the real-time and interactive requirements of information transmission are more and more high, which puts higher demands on business intelligence. The development of the next generation business intelligence requires that it not only can provide strategic decision for senior decision-makers, but also can ...

It has been almost 2 years since the big data was exposed and the customers outside the Internet were talking about big data. It's time to sort out some of the feelings and share some of the puzzles that I've seen in the domestic big data application. Clouds and large data should be the hottest two topics in the IT fry in recent years. In my opinion, the difference between the two is that the cloud is to make a new bottle, to fill the old wine, the big data is to find the right bottle, brew new wine. The cloud is, in the final analysis, a fundamental architectural revolution. The original use of the physical server, in the cloud into a variety of virtual servers in the form of delivery, thus computing, storage, network resources ...

Big data is changing the IT world completely. So, what kind of data can be discussed? According to IDC, global data will increase 50 times times over the next decade. In 2011 alone, we will see large data creation of 1.8ZB (i.e. 1.8 trillion GB). This is equivalent to every American writing 3 tweets a minute, and still writing for 26,976 years. Over the next decade, the number of servers managing the Data warehouse will increase by 10 times times to cater for 50 times times larger data growth. There is no doubt that large data will challenge the enterprise's storage architecture and data ...

It can be said that big data is one of the hottest trends in the IT industry today, and it has spawned a new batch of technologies to deal with big data. And new technologies have brought the latest buzz words: acronyms, professional terms, and product names. Even the phrase "big data" itself makes a person dizzy. When many people hear "big data", they think it means "a lot of data", and the meaning of large data does not only involve the amount of data. Here are a few popular words that we think you should be familiar with, sorted alphabetically. ACID ...