There are several Buzz words in the IT industry today say Cloud, Big Data, Analytics and on.
First one is the practice of using a network of remote servers hosted on the Internet to store, manage, and process data, rather than a local server or a personal computer. Prime focus of this cloud computing is bring down the operation cost to a minimum.
Second one, extremely large data sets(collection of data) that may be analysed computationally to reveal patterns, trends, and associations, especially relating to human behaviour and interactions.
Final word is the systematic computational analysis of data or statistics.
An important factor for Big data and analytics is Data.
Data are the facts and figures collected, analysed and summarised for presentation and interpretation.Data interpretation helps you make sense of the message.
Some people see data as facts and figures. But it’s more than that. It’s the lifeblood of your business. It contains your organisation's history.
Sometimes the data needed for a particular application are not available through existing sources. in such cases the data can often be obtained by conducting a statistical study.This study further classified to experimental and non experimental.
Experimental Study, a variable of a interest is first identified. Then one or more another variable is identified and controlled so that the data can be obtained how they influence the variable of interest.
For Ex. A pharmaceutical firm might be interested in conducting an experiment to learn how a new drug effects blood pressure. Blood pressure is the variable of interest in this study and the dosage level of the new drug is another variable that is hoped to have a casual effect on blood pressure. To obtain data abut the effect of the new drug, sample of individual is collected. the dosage level is controlled as different groups of individuals. Statistical analysis of the experimental data can help to determine how the new drug effects blood pressure.
Non-Experimental Study, make no attempt to control the variable of interest. Survey is the most common type of observational study.
For Eg: Restaurants use non experimental studies to obtain data about customer opinion on the quality of the food, quality of the service, atmosphere and so on.
First one is the practice of using a network of remote servers hosted on the Internet to store, manage, and process data, rather than a local server or a personal computer. Prime focus of this cloud computing is bring down the operation cost to a minimum.
Second one, extremely large data sets(collection of data) that may be analysed computationally to reveal patterns, trends, and associations, especially relating to human behaviour and interactions.
Final word is the systematic computational analysis of data or statistics.
An important factor for Big data and analytics is Data.
Data are the facts and figures collected, analysed and summarised for presentation and interpretation.Data interpretation helps you make sense of the message.
Some people see data as facts and figures. But it’s more than that. It’s the lifeblood of your business. It contains your organisation's history.
Sometimes the data needed for a particular application are not available through existing sources. in such cases the data can often be obtained by conducting a statistical study.This study further classified to experimental and non experimental.
Experimental Study, a variable of a interest is first identified. Then one or more another variable is identified and controlled so that the data can be obtained how they influence the variable of interest.
For Ex. A pharmaceutical firm might be interested in conducting an experiment to learn how a new drug effects blood pressure. Blood pressure is the variable of interest in this study and the dosage level of the new drug is another variable that is hoped to have a casual effect on blood pressure. To obtain data abut the effect of the new drug, sample of individual is collected. the dosage level is controlled as different groups of individuals. Statistical analysis of the experimental data can help to determine how the new drug effects blood pressure.
Non-Experimental Study, make no attempt to control the variable of interest. Survey is the most common type of observational study.
For Eg: Restaurants use non experimental studies to obtain data about customer opinion on the quality of the food, quality of the service, atmosphere and so on.
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