Big Data Analytics 简明教程
Big Data Analytics Tutorial
大数据：顾名思义，更大的数据被称为大数据。数据规模正在与日俱增。个人通过使用手机、平板和笔记本电脑处理数据，而组织处理业务数据；统计数据表明，在过去十年中，数据规模急剧增加。
Big Data; as its name implies, the data which is bigger is known as big data. The data size is increasing day by day. An individual deals with data using mobile phones, tabs, and laptops while an organisation deals with business data; statistically it has been noted that the data size has drastically increased in the past decade.
What is Big Data?
“大数据”一词通常是指数据集太大、太复杂，且无法通过普通数据处理系统有效管理的数据集。这些数据集可以来自各种来源，包括社交媒体、传感器、互联网活动和移动设备。数据可以是结构化、半结构化和非结构化类型的数据。
The term "Big Data" usually refers to datasets that are too large, complex and unable to be processed by ordinary data processing systems to manage efficiently. These datasets can be derived from a variety of sources, including social media, sensors, internet activity, and mobile devices. The data can be structured, semi-structured and unstructured type of data.
Big Data Analytics
分析大型和多维数据集的过程被称为“大数据”。它发现隐藏模式、未知关系、市场趋势、用户偏好和其他重要信息。它使用高级分析技术，例如统计分析、机器学习、数据挖掘和预测建模，从庞大的数据集中提取见解。
A process of analysing large and diverse data sets is known as "Big Data," It discovers hidden patterns, unknown relationships, market trends, user preferences, and other important information. It uses advanced analytics techniques such as statistical analysis, machine learning, data mining, and predictive modelling to extract insights from enormous datasets.
世界各地的组织都在收集有关其用户的交互、业务、社交媒体以及来自移动电话和汽车等设备的传感器的 TB 级数据。这个时代面临的挑战是理解这一海量数据。大数据分析正是针对这种情况提出的。
Organisations across the world capture terabytes of data about their users' interactions, business, social media, and also sensors from devices such as mobile phones and automobiles. The challenge of this era is to make sense of this sea of data. This is where big data analytics comes into the picture.
Where Big Data Analytics Used?
大数据分析旨在帮助组织制定更明智的业务决策、提高运营效率、改善客户体验和服务，并确保组织在各自的行业中保持在竞争世界中。大数据分析过程包括数据的收集、存储、处理、分析和成果可视化，以便制定战略业务决策。将从不同来源检索到的海量非结构化原始数据转换为对组织有用的数据产品构成了大数据分析的核心。
Big Data Analytics strives to assist organisations in making more informed business decisions, increasing operational efficiency, improving customer experiences and services, and making sure to sustain industries in a competitive world with their respective industries. The Big Data Analytics process involves data gathering, storage, processing, analysis, and visualisation of outcomes to make strategic business decisions. The process of converting large amounts of unstructured raw data, retrieved from different sources to a data product useful for organizations forms the core of Big Data Analytics.
总体而言，大数据分析使组织能够利用他们获得的大量数据，并将其转化为推动业务增长和创新的可操作见解。
Overall, Big Data Analytics enables organizations to harness the vast amounts of data available to them and turn it into actionable insights that drive business growth and innovation.
在本大数据分析教程中，我们将讨论大数据分析最基本的概念和方法。
In this big data analytics tutorial, we will discuss the most fundamental concepts and methods of Big Data Analytics.
Audience
本教程专为有志于学习大数据分析基础的软件专业人士编写。从事分析工作的专业人士也可以有效地利用本教程。
This tutorial has been prepared for software professionals aspiring to learn the basics of Big Data Analytics. Professionals who are into analytics, in general, may as well use this tutorial to good effect.
Prerequisites
在开始进行本教程之前，我们假设您之前有过在组织层面处理大量未处理数据的经验。
Before you start proceeding with this tutorial, we assume that you have prior exposure to handling huge volumes of unprocessed data at an organizational level.
通过本教程，我们将开发一个迷你项目，以便提供接触实际问题以及使用大数据分析解决该问题的经验。
Through this tutorial, we will develop a mini project to provide exposure to a real-world problem and how to solve it using Big Data Analytics.