Post by Admin on Mar 13, 2014 8:32:30 GMT
Big Data is about the growing challenge that organizations face as they deal with large and fast-growing sources of data or information that also present a complex range of analysis and use problems these can include.
Having a computing infrastructure that can ingest validate , and analyze high volumes (size and / or rate) of data.
• Assessing mixed data (structured and unstructured from multiple sources.
• Dealing with unpredictable content with no apparer schema or structure.
• Enabling real-time or near-real-time collection, analysis and answers.
Big Data technologies increase a new generation of technologies and architectures, designed to economically wide variety of data, by enabling high – velocity capture, discovery, and/or analysis.
The data comes from everywhere: sensors uses to gather climate information, posts to social mediates, digital pictures and videos, purchase transaction records, and cell phone Gps signals to name a few is data is Big Data.
Ree vs Bigdata:-
Volume describes the amount of data generated by organizations or individuals.
Variety describes structured and unstructured data such as text, sensor data audio, video,click streams, log files and more.
Velocity describes the frequency at which data is generated, captured and shared.
Big Data – Hadoop:-
Handoop is the Apache open source software frame work for working with Big Data. It was Derived from Google technology and put to practice by yahoo and others. But, Bigdata is too varies and complex for a one-size-fits-all solution.
While Handoop has surely captured the greater name. recognition, it is just one of three classes of technologies well suited to storing and managing Big Data.
No. of components that were specifically designed to solve large-scale distributed data storage, analysis and retrieval tasks.
Ex: of Big Data:-
• Google process 20 PB a day.
• Way back machine has 3 PB + 100 TB/month.
• Face book has 2.5 PB of user data + 15 TB/day.
• e Bay has 6.5 PB of user data + 50 TB/day.