How is the data the most accurate?

With the application of big data, the indicators of big data technology have gradually attracted more attention. Especially for traditional industries, how to effectively use big data technology to assist innovation and improve operational efficiency is also a problem that must be considered.

In the actual production environment, in order to make effective use of big data, we must first have an overall cognitive ability of various technical indicators of big data technology, which involves how to define accuracy, fineness, completeness, stability and speed. These indicators are also of direct significance for realizing the data value of big data.

The so-called "quasi" involves many elements in big data, including data association description, data latitude, semantic analysis, algorithm design and so on. Simply put, the greater the amount of data, the higher the latitude of the data, the clearer the problem description, and the higher the accuracy. Of course, whether big data is "accurate" is also directly related to algorithm design.

"Fine" and "Full" respectively represent the depth and breadth of big data. "Fine" is mainly reflected in whether the depth of data mining can meet the needs of applications and whether new values can be discovered through data mining. Deep learning has made continuous progress in "fineness", and "fineness" requires higher computing power. To achieve "all", we must first focus on data collection, which is also directly related to the construction of the Internet of Things.

"Steady" and "fast" are important indicators to measure the availability of big data. "Steady" not only represents the stable system running ability, but also represents the consistent performance of the results. The definition of "fast" directly affects the running efficiency of the whole system. To be stable, we must first deal with different types of data in different ways, and to be fast involves calculation methods. For example, in the adoption of big data platforms, Spark is often significantly faster than Hadoop.

Finally, whether the big data system can be accurate, detailed, complete, stable and fast is related to many factors. In addition to using data sets for verification, another way to judge is to implement landing application practice, which can also continuously improve the design of big data platform.