Financial Datasets For Data Mining

Do you need a lot of data to test your app performance? The easiest way to do this is to download data samples from the free data repository on the web. But the biggest drawback of this approach is that the data rarely has unique content and does not necessarily achieve the desired results. Here are more than 70 sites with free large data repositories available. Wikipedia:database: Provide free copies of all available content to interested users. Data can be obtained in multiple languages. Content can be downloaded together with pictures. Common crawl to establish and maintain a human being ...

Do you need a lot of data to test your app performance? The easiest way to do this is to download data samples from the free data repository on the web. But the biggest drawback of this approach is that the data rarely has unique content and does not necessarily achieve the desired results. Here are more than 70 sites with free large data repositories available. Wikipedia:database: Provide free copies of all available content to interested users. Data can be obtained in multiple languages. Content can be downloaded together with pictures. Common crawl to establish and maintain a human being ...

Today, some of the most successful companies gain a strong business advantage by capturing, analyzing, and leveraging a large variety of "big data" that is fast moving. This article describes three usage models that can help you implement a flexible, efficient, large data infrastructure to gain a competitive advantage in your business. This article also describes Intel's many innovations in chips, systems, and software to help you deploy these and other large data solutions with optimal performance, cost, and energy efficiency. Big Data opportunities People often compare big data to tsunamis. Currently, the global 5 billion mobile phone users and nearly 1 billion of Facebo ...

Big data hit many years ago, the industry was discussing a topic: How to deal with massive data? In particular, some need to store a large number of user data industry, finance, telecommunications, insurance and other popular industries. Users almost every hour of the day, are likely to produce a large number of data, these industries storage equipment, must be the data generated during the period of meticulous record, in order to prevent loss, but also must do backup, but also have to do off-site disaster recovery backup, which is not finished, business interruption events can not exceed the number of time range, Otherwise it is a major accident, so must be through the IT system assurance industry ...

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 ...

The new concept stock market is always the most sensitive. After the Bigdata, cloud computing, mobile Internet, the subject of large data investment has aroused great concern in the industry recently. HC Research noted that from the end of 2011 to the beginning of 2012, National Gold Securities, Guotai, Galaxy Securities and other domestic institutions, recommend "large data concept stocks", and predicted that it will become a new line of investment in 2012. What is the performance of large data in the A-share market? Big data as the IT industry's new favorite and rely on what to support performance? Stand in the industry's perspective, observe the big data ...

The new concept stock market is always the most sensitive. After the Bigdata, cloud computing, mobile Internet, the subject of large data investment has aroused great concern in the industry recently. HC Research noted that from the end of 2011 to the beginning of 2012, National Gold Securities, Guotai, Galaxy Securities and other domestic institutions, recommend "large data concept stocks", and predicted that it will become a new line of investment in 2012. What is the performance of large data in the A-share market? Big data as the IT industry's new favorite and rely on what to support performance? Stand in the industry's perspective, view ...

Just a few weeks ago, the launch of Apache Hadoop 2.0 was a huge milestone in the field of Hadoop, as it opened up an unprecedented revolution in the way data is stored. Hadoop retains its typical "big data" base technology, but does it fit into the current database and data Warehouse usage? Is there a common pattern that can actually reduce the inherent complexity of usage? The general pattern Hadoop uses is originally conceived for companies like Yahoo, Google, Facebook, etc.

Just a few weeks ago, the launch of Apache Hadoop 2.0 was a huge milestone in the field of Hadoop, as it opened up an unprecedented revolution in the way data is stored. Hadoop retains its typical "big data" base technology, but does it fit into the current database and data Warehouse usage? Is there a common pattern that can actually reduce the inherent complexity of usage? The general pattern Hadoop uses is originally conceived for companies like Yahoo, Google, Facebook, etc.

Reasons for implementing large data Strategy (a) large data has become important strategic resources large data is as important as natural resources, human resources and strategic resources. The United States suggests that big data is strategically comparable to industrial-era oil. The large data industry in the United States has entered a large-scale commercialization phase and has penetrated into many fields such as economy, politics, education, security and social management. The Obama team applied large data analysis to the campaign, digging through the massive data collected and stored over the last two years, searching for and locking potential voters, using digital strategies ...