The reliability of Big Data

The era of Big Data is underway. Compared to Small Data, machine learning, computerized databases and other modern technologies makes it possible for Big Data to do handle massive data and reveal information in a way that individual bits of data can't. Random sampling's accuracy depends on ensuring randomness when collecting data from samples. Analyzing only a limited number of data points means errors may get amplified, which may reduce the accuracy of the overall results potentially. Meanwhile, Big Data gathers and analyzes massive data to produce some excellent results that we could never know when we are limited to smaller quantities, like address various societal ills, offer potential of new insights into diverse fields. But as the data comes from an environment of uncertainty and rapid change, bigger data may not a better data. Increasing the volume of data may lead to inaccuracy, but in return for relaxing the standards of allowable errors, which produces more valuable information and better results. This article elaborates the reliability of Big Data. Based on our analysis we have constructed a model to analyze the reliability of Big Data.