Big data may well be the next big thing in the world. The first organizations to embrace it were online and startup firms. Firms like Google and face book were build around big data from the beginning. The big data is appropriate if the data layered or data must be placed in a sequence.S eparate files for each data set. Big data require the huge storage or space to save it. The big data information that cannot be analyzed with traditional computing techniques. The big data characteristics are volume, velocity and variety. Volume in which we define the quantity of any data set.If quantity of data set is good then that should be adjustable in storage and also minimal chances to error occur in data. Velocity can be define the speed of the data if speed of any data set like bill payment if the data will be organize form then speedy perform the bill payment action. High frequency stock trading algorithms reflect market changes within microseconds. Machine to machine process exchange data between billions of device. Variety in which we define the data type. What is data type in that data set . That data is in textual form ,audio form , video form including log files and social media. We want the big data is more efficient can perform quick results and no error occurs in any type of data if that data is in textual form or any other form. We have not concern what the type of data we just want minimal storage consume and generate quick results and efficient in every point of view. If any type of error occur in that data we should already define the algorithms to solve that problem or resolve that problem and also minimize that problem. The big data does not comprise of traditional structured corporate information but also includes media files like audio, video and pictures unstructured text CAD/CAM files, HD graphics etc.
Big data analytics
The word Engineering is the more clearly to define us that word can explain a lot of things or concepts. Engineering is more widely used in the world. In everything the word engineering must be used like electronic machines for example TV remote, fan etc. That machines how can working properly because of engineering used in that machines. The engineering concepts can be build in that machines. That’s why those machines are properly working. Engineering concept include the collection of tools, procedures, methodologies and accumulated knowledge about the development of any system. Engineering concepts is to trick someone into giving them what they want. The engineering preys on qualities of human nature. We want the engineering become a part of our daily life. A lot of work done in our daily life whenever engineering are used in daily life. Human nature is to actually trust others until they prove that they are not trust worthy. If someone tells that they are a certain person, we usually accept that statement. The engineering may enter the building and pretend to be employee that how the engineering should apply on their system according to the law of engineering. They may be dressed in a uniform or become a part of the contract cleaning crew. The engineering are a multiple view in every field. For example in electronic field the engineering will be different and in other field the engineering must be different. The engineering concepts can be changed in every field. The engineering should applicable in that field if the engineering in which we can apply on that field according to the field.
Big data analytics based error correction and detection
A sensor network is a system of one or more sensors that detect collect and possibly respond to things or events. Large number of sensor nodes which are densly deployed either the phenomenon or very close to it. Inter connected sensor nodes exchanging sensed data by wired or wireless processing. The sensor architecture should contain these things in any power supply like visible light sensor, IR light sensor, humidity sensor, expansion port, internal antennas, reset option, user defined push, USB for programming and UART also external antenna and 3 LEDS. Provides meta data describing sensors, sensor platforms, sensor taking interfaces sensor generated data. Including companies in sensor networks are energy monitoring, logistics, environmental monitoring, public spaces mamgement, intelligent buildings, traffic control and public transportation, health and personal assistance care monitoring and industrial processes. We can face these future challenges efficient energy harvesting, security and privacy, hardware constraints and interoperability. In efficient energy harvesting the system should consume less power during some time. Lack of power used. In security and privacy can contain or can be defined as security must be high can build or attached high constraints because of not any can hack your future policies. And also privacy should high not any one can use your system or enter in your system to check your constraints in which you are add in your system. Therefore security and privacy must be high. In hardware constraints your production cost must be low. And performance of your hardware constraints should high. The performance criteria should ask you what’s your performance constraints how much time consume for your system. Repair option should be include in your hardware constraints. If in your hardware may problem occur you are applicable to resolve that problem? Your IP sensor network standard is also high and the network of things.05-14-16
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