Big Data Training and Courseware

Gartner defines Big Data as “Big data are high volume, high velocity, and/or high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery, and process optimization.”

Put simply, “big data” describes huge amounts of information that is easy to obtain, but so massive that they challenge current computing technologies

Big data is the problem you have when you have information coming in from multiple sources (computers, satellites, mobile devices, cameras, microphones, and more). That information needs to be moved around, stored (we’re talking petabytes and exabytes, for example), and processed.

Big Data can come from many different sources such as computers, satellites, mobile devices, cameras, microphones, and more. It can be collected through social media or through open data sources. It can involve multiple, simultaneous data sources, which may not otherwise be integrated

Big Data can exist in a wide variety of file types, including structured data, such as SQL database stores, or unstructured data, such as document files or streaming data

Most organizations use just a fraction of the data available to them as it is either too expensive to process it or business has no expertise to extract the relevant information.

Businesses that effectively leverage Big Data (that was originally discarded or not processed due to technology limitations) get a competitive advantage over their competitors. Insights from Big Data help improve services and products, develop deeper customer relationships in a more agile and predictive manner and uncover new monetization opportunities.

Since storage costs of Big Data in many cases is not an issue, businesses may request their IT to extend retention period of some data feeds and come up with usage ideas later on. Specialized Big Data solutions can offer real or near real-time analytics. Overall, with Big Data, business agility is achieved and new features can be incorporated into applications quickly and easily.

See the answer to the above question.

As per Gartner’s definition, the three defining properties to Big Data are high volume, high velocity, and/or high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization

Hadoop is a distributed fault-tolerant computing platform written in Java. It’s modeled after shared-nothing, massively parallel processing (MPP) system design. Hadoop’s design was influenced by ideas published in Google File System (GFS) and MapReduce white papers. Hadoop’s core component, Hadoop Distributed File System (HDFS) is the counterpart of GFS. Hadoop uses functionally equivalent to Google’s MapReduce data processing system also called MapReduce (term coined by Google’s engineers). Hadoop is written in Java to ensure that HDFS is portable. One of the main focuses of Hadoop’s architecture was to “design for failure”.

According to Forbes magazine:

For a typical Fortune 1000 company, just a 10% increase in data accessibility will result in more than $65 million additional net income. Estimates suggest that by better integrating big data, healthcare could save as much as $300 billion a year — that’s equal to reducing costs by $1000 a year for every man, woman, and child. Retailers who leverage the full power of big data could increase their operating margins by as much as 60%.