Datasets For Data Analytics

This time, we share the 13 most commonly used open source tools in the Hadoop ecosystem, including resource scheduling, stream computing, and various business-oriented scenarios. First, we look at resource management.

There are many methods for processing and analyzing large data in the new methods of data processing and analysis, but most of them have some common characteristics. 　　That is, they use the advantages of hardware, using extended, parallel processing technology, the use of non-relational data storage to deal with unstructured and semi-structured data, and the use of advanced analysis and data visualization technology for large data to convey insights to end users. 　　Wikibon has identified three large data methods that will change the business analysis and data management markets. Hadoop Hadoop is a massive distribution of processing, storing, and analyzing ...

As we all know, predictive analysis has always been the "prerogative" of statisticians and data scientists in the "Ivory Tower", and they are far from day-to-day business decision makers. Big data will change that. As more and more data streams are put online and integrated into existing BI, CRM, ERP, and other critical business systems, predictive analytics will eventually become a focus of attention. Although most customer service representatives and field sales representatives have not yet felt the impact, companies such as IBM and MicroStrategy have begun to move. Big Data: Predictive analysis is no longer the prerogative of statisticians to think ...

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 ...

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 ...

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 ...

If only a large amount of structured data, then the solution is relatively simple, users to buy more storage equipment, improve the efficiency of storage devices and other solutions to such problems. 　　However, when people find that the data in the database can be divided into three types: structural data, unstructured data and semi-structured data and other complex situations, the problem seems to be less simple. Big Data hits when the type of complex data hits, then the impact on the user IT system will be another way to deal with. Many industry experts and third party investigation agencies through a ...

The sky has fallen again. This time it was "big data" that formidable IT department. As gossip rumors, no matter where you go, the discussion of "big data" is everywhere. Search for this phrase in Google, search results more than 1.3 billion. It even has a special entry in Wikipedia. The deluge of data has led many to conclude that businesses will be overwhelmed. This is not to say that the amount of information inside the enterprise will not grow. On the contrary, the enterprise's internal information is also difficult to escape the growth of the fate. 　　Because big data is always a problem. Despite persistent claims that the torrent of data will lead to ...

Gartner presented the BI concept in 1989. Gartner further upgraded the BI concept to advanced analysis (Advanced Analytics) in 2008. 2011, McKinsey explained the concept of large data. The names are different, but the problems they are trying to solve have never changed. However, now large data analysis technology can deal with more than 20 years ago, a larger, more diverse, real-time (Volume, produced, Velocity) data, that is, large number ...