当前位置:网站首页>2020十大最佳大数据分析工具,果断收藏
2020十大最佳大数据分析工具,果断收藏
2020-11-06 01:15:00 【InfoQ】
{"type":"doc","content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"营销的基本原理是一致的,每个人都喜欢洞察力,因为这些数字模式可以提供最安全的方法来确保企业采取正确的行动,更有效地运作,以及将其资源用在何处。数据已经成了战略的据点。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"blockquote","content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"“"},{"type":"text","marks":[{"type":"strong"}],"text":"95% 的企业数据都是非结构化的。"},{"type":"text","text":"”"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"——《福布斯》(Forbes)"}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"这种非结构化数据是最大的障碍。为了利用这些数据并消除障碍,大数据工具可能是一个方便的解决方法。以我们目前的速度,每天生成 2.5 百万兆字节的数据,为什么不把这些原始数据转换为有用的业务见解呢?"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"预计到 2027 年底,"},{"type":"link","attrs":{"href":"https:\/\/www.statista.com\/statistics\/254266\/global-big-data-market-forecast\/","title":"","type":null},"content":[{"type":"text","text":"大数据市场"}]},{"type":"text","marks":[{"type":"strong"}],"text":"将增长 13 亿美元"},{"type":"text","text":"。由于在商业中,数据分析有多种不同的有效用途,每个企业或行业垂直领域都在以某种方式充分利用数据分析。一些奇妙的好处是:"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"bulletedlist","content":[{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","marks":[{"type":"strong"}],"text":"对消费者行为进行分析和预测"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","marks":[{"type":"strong"}],"text":"规划新产品、服务和体验"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","marks":[{"type":"strong"}],"text":"确定产品和优惠的发布"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","marks":[{"type":"strong"}],"text":"改进工作流程"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","marks":[{"type":"strong"}],"text":"分析客户需求波动"}]}]},{"type":"listitem","attrs":{"listStyle":null},"content":[{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","marks":[{"type":"strong"}],"text":"促进销售或影响客户行为"}]}]}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"对于所有这些商业利益中,真正的问题是:“"},{"type":"text","marks":[{"type":"strong"}],"text":"最好的大数据工具是什么?"},{"type":"text","text":"”为了人类的福祉,为了获得竞争优势,我们要采用 3Vs 技术。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"无论是运营大数据还是分析大数据,都有四项关键技术需要重点关注:存储、分析、挖掘和可视化。每一项技术在分析海量的数据集时都扮演了至关重要的角色。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null},"content":[{"type":"text","text":"为了找到最好的大数据工具,我采取了平台兼容性、成本效率、分析任务的时间管理、所需的知识集、分析能力和可视化等措施。"}]},{"type":"paragraph","attrs":{"indent":0,"number":0,"align":null,"origin":null}}]}
版权声明
本文为[InfoQ]所创,转载请带上原文链接,感谢
https://www.infoq.cn/article/IEIa8zX2s0KpLYi34ocE?utm_source=rss&utm_medium=article
边栏推荐
猜你喜欢
随机推荐
使用Consul实现服务发现:instance-id自定义
html
自然语言处理-错字识别(基于Python)kenlm、pycorrector
为了省钱,我用1天时间把PHP学了!
解決pl/sql developer中資料庫插入資料亂碼問題
技術總監7年經驗,告訴大家,【拒絕】才是專業
对pandas 数据进行数据打乱并选取训练机与测试机集
如何选择分类模型的评价指标
车的换道检测
H5打造属于自己的视频播放器(JS篇2)
Ubuntu18.04上安裝NS-3
前端模組化簡單總結
Python + Appium 自動化操作微信入門看這一篇就夠了
用Keras LSTM构建编码器-解码器模型
7.3.2 File Download & big file download
安装Consul集群
普通算法面试已经Out啦!机器学习算法面试出炉 - kdnuggets
mac 下常用快捷键,mac启动ftp
文本去重的技术方案讨论(一)
OPTIMIZER_TRACE详解








