Tuesday, 11 February 2014
BigData Training - Chennai [ Apache Hadoop]: Hadoop Best Practise
BigData Training - Chennai [ Apache Hadoop]: Hadoop Best Practise: Hadoop is a free Java framework for distributed applications and intensive data management. It enables applications to work with thousands...
Hadoop Best Practise
Hadoop is a free Java framework for distributed applications and intensive data management. It enables applications to work with thousands of nodes and petabytes of data
With Hadoop, companies discover and put into practice new techniques for analysis and retrieval of data, techniques previously impossible to implement for reasons of performance, cost and technology. As a result, Hadoop is an option that is gaining popularity to treat, store and analyze large volumes of raw data, semi-structured or unstructured data from the most disparate data sources.
More than one billion users of Facebook generated about 2,500 million updates, about 300 million images and links. This makes the social network to process more than 500 terabytes of content daily.
Hadoop is used in three different ways: as a data warehouse for web analytics, to store distributed database, and finally for backups of these MySQL database servers.
In addition, Hadoop is used for thousands of simultaneous requests, mining operations, social analysis, and management of resources.
The main strength Hadoop lies in its scalability.
With Hadoop, companies discover and put into practice new techniques for analysis and retrieval of data, techniques previously impossible to implement for reasons of performance, cost and technology. As a result, Hadoop is an option that is gaining popularity to treat, store and analyze large volumes of raw data, semi-structured or unstructured data from the most disparate data sources.
More than one billion users of Facebook generated about 2,500 million updates, about 300 million images and links. This makes the social network to process more than 500 terabytes of content daily.
Hadoop is used in three different ways: as a data warehouse for web analytics, to store distributed database, and finally for backups of these MySQL database servers.
In addition, Hadoop is used for thousands of simultaneous requests, mining operations, social analysis, and management of resources.
The main strength Hadoop lies in its scalability.
Wednesday, 5 February 2014
BigData Training - Chennai [ Apache Hadoop]: Big Data: A new competitive advantage
BigData Training - Chennai [ Apache Hadoop]: Big Data: A new competitive advantage: The utilization of Big Data is turning into a vital path for heading organizations to beat their companions. In most businesses, secured c...
Big Data: A new competitive advantage
The utilization of Big Data is turning into a vital path for heading organizations to beat their companions. In most businesses, secured contenders and new participants apparently equivalent will influence data driven techniques to improve, contend, and catch esteem.
Big Data will help to create new growth opportunities and entirely new categories of companies, such as those that aggregate and analyse industry data. Many of these will be companies that sit in the middle of large information flows where data about products and services, buyers and suppliers, consumer preferences and intent can be captured and analysed. Forward-thinking leaders across sectors should begin aggressively to build their organisations’ Big Data capabilities.
In addition to the sheer scale of Big Data, the real-time and high-frequency nature of the data are also important. For example, ‘nowcasting,’ the ability to estimate metrics such as consumer confidence, immediately, something which previously could only be done retrospectively, is becoming more extensively used, adding considerable power to prediction. Similarly, the high frequency of data allows users to test theories in near real-time and to a level never before possible.
In healthcare, data pioneers are analyzing the health outcomes of pharmaceuticals when they were widely prescribed, and discovering benefits and risks that were not evident during necessarily more limited clinical trials. Other early adopters of Big Data are using data from sensors embedded in products from children’s toys to industrial goods to determine how these products are actually used in the real world. Such knowledge then informs the creation of new service offerings and the design of future products
Big Data will help to create new growth opportunities and entirely new categories of companies, such as those that aggregate and analyse industry data. Many of these will be companies that sit in the middle of large information flows where data about products and services, buyers and suppliers, consumer preferences and intent can be captured and analysed. Forward-thinking leaders across sectors should begin aggressively to build their organisations’ Big Data capabilities.
In addition to the sheer scale of Big Data, the real-time and high-frequency nature of the data are also important. For example, ‘nowcasting,’ the ability to estimate metrics such as consumer confidence, immediately, something which previously could only be done retrospectively, is becoming more extensively used, adding considerable power to prediction. Similarly, the high frequency of data allows users to test theories in near real-time and to a level never before possible.
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