Safety is a “bottomless pit”. No person in charge of safety in an enterprise will say that his system is 100% safe, and safety is not particularly good to measure and quantify, especially to quantitatively evaluate who is better than who and how much better. Sometimes I think, or feel confused, “with all these protective ..
Part I: Architecture and Components I. Development of Data Platform 1.1 Background Introduction With the advent of the data age, the increase of data volume and data complexity has promoted the rapid development of data engineering. In order to meet various data acquisition/calculation requirements, many solutions have emerged in the industry. However, most of the ..
Agile big data is to build a series of common platform tools and a whole set of big data application life cycle methodology under the guidance of agile concept principles to support lighter, more flexible and lower threshold big data practice. This article explains what we understand as “agile big data” from a theoretical perspective. ..
Introduction: this article will discuss an important and common big data infrastructure platform, namely “real-time data platform”, in two parts.In the last design chapter, we first introduce the real-time data platform from two dimensions: viewing the real-time data platform from the perspective of modern data warehouse architecture and viewing the real-time data processing from the ..
Song of Agility I count, therefore I exist | DBus Everyone Plays with Streaming Think of me as a database | Moonbox Yan Worth Last Ten Kilometers | Davinci Introduction: RTDP (Real-time Data Platform) is an important and common big data infrastructure platform. In the last part (design part), we introduced RTDP from the perspective ..
Classification by Learning Method Supervised learning Have a training set (Contains data and its classification) and test sets (There is no classification of data) From binary classification (support vector machine) to multivariate classification Enhance learning The results of machine learning will be rewarded and punished accordingly. The goal of machine learning is to maximize rewards ..