大数据分析和数据挖掘区别_大数据分析和数据挖掘之间的区别，大数据的未来范围...

大数据分析和数据挖掘区别

There arises a confusion among most of the people between Big Data and Data mining. In this article, I will try to make you understand the difference between both and later on we will focus on the future scopes of Big data.

大多数人在大数据和数据挖掘之间产生了混淆。 在本文中，我将尝试使您理解两者之间的区别，以后我们将重点关注大数据的未来范围 。

Big data and data mining are two completely different things. The only similarity between them or we can say that the only thing that relates to big data and data mining is the use of huge data sets that serve business or other purposes. But both Data mining and big data analysis are used for two different operations.

大数据和数据挖掘是完全不同的两件事。 它们之间的唯一相似之处，或者我们可以说，与大数据和数据挖掘有关的唯一事情是使用可用于业务或其他目的的大数据集。 但是数据挖掘和大数据分析都用于两种不同的操作。

大数据分析 (Big Data Analytics )

This is a process mostly used by different companies to analyze larger data sets with the objective of discovering the information of their need. It is commonly done to know the market trends, the customer’s interests, their preferences, hidden patterns, and the uncovered correlations. This analytics usually lead to new business opportunities, improvement of operational efficiency, improves the marketing successful fulfillment of public demands (preferences of customers).

这是不同公司通常用于分析较大数据集的过程，目的是发现他们需要的信息。 通常要了解市场趋势，客户的兴趣，他们的偏好，隐藏的模式以及未发现的相关性。 这种分析通常会带来新的商机，提高运营效率，提高营销成功满足公众需求(客户的偏好)的能力。

Most of the companies nowadays depend on big data analytics to suggest them/advice them in making different kinds of business strategies.

如今，大多数公司都依赖大数据分析来建议/建议他们制定各种业务策略。

Big data analytics can also be used to analyze data that might not have been discovered yet by conventional business programs. This includes:

大数据分析还可以用于分析常规业务程序可能尚未发现的数据。 这包括：

• Analyzation of response e-mails of a public survey.

  一项公共调查的回复电子邮件的分析。

• Analyzation of data from different sensors connected to the Internet of things.

  来自连接到物联网的不同传感器的数据分析。

• Social media data aggregation and activity reports.

  社交媒体数据汇总和活动报告。

Big data analysis a very fruitful option for establishments and giving a good rise to the business of companies. But the problem that lies in the implementation such as:

大数据分析对于企业而言是非常富有成果的选择，并且可以很好地促进公司业务的发展。 但是问题在于实现，例如：

• Cost of hiring big data experts are quite high.

  聘用大数据专家的成本很高。

• It becomes a huge challenge to the management to handle such a big amount of data.

  处理如此大量的数据对管理层来说是一个巨大的挑战。

• Integration of Hadoop systems and data warehouse presents another great challenge.

  Hadoop系统与数据仓库的集成提出了另一个巨大的挑战。

Figure: Big Data Analytics

图：大数据分析

数据挖掘 (Data Mining)

Data mining is also defined as knowledge discovery. It is observing the data from a different viewpoint and preparing a summary containing useful information. The resultant information of data mining is usually used to reduce operational expenses. The software programs that are used in data mining are among the programs that are used in data analysis.

数据挖掘也被定义为知识发现。 它正在从不同的角度观察数据，并准备包含有用信息的摘要。 数据挖掘的结果信息通常用于减少运营支出。 数据挖掘中使用的软件程序属于数据分析中使用的程序。

Technically, we can say that data mining includes discovering patterns or relations in large areas of related databases.

从技术上讲，我们可以说数据挖掘包括在大范围相关数据库中发现模式或关系。

Data mining is done to assist the extraction of previously unknown patterns of data, including abnormalities present in data records, cluster analyzation of files containing data.

进行数据挖掘是为了协助提取以前未知的数据模式，包括数据记录中存在的异常，对包含数据的文件进行聚类分析。

Figure: Data Mining

图：数据挖掘

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大数据的未来范围 (Future Scopes of Big Data)

If you are still confused about your field and still in search of options, here are some reasons that will surely drag your attention towards BIG DATA.

如果您仍然对自己的领域感到困惑并且仍在寻找选择，那么有一些原因一定会把您的注意力吸引到BIG DATA上 。

DEMAND:

需求：

There is rising demand for analytics professionals in the corporate world nowadays.

如今，企业界对分析专业人员的需求不断增长。

Figure: Job trends in BIG DATA

图：大数据中的工作趋势

SALARY:

薪水：

As a high demand data analysis, need of skilled professionals are also rising, this is making Big data pay big bucks for the right skill, and it is not only limited to India its flowing over countries like Australia, U.K etc.

作为高需求数据分析，对熟练专业人员的需求也在增加，这使得大数据为正确的技能付出了高昂的代价，不仅限于印度，它流向澳大利亚，英国等国家。

PRIORITY:

优先：

It is among the top priorities of MNCs and other companies, ruling the whole market worldwide.

这是跨国公司和其他公司的头等大事，统治着整个全球市场。

Figure: Priority of BIG DATA

图：大数据的优先级

JOB TITTLES:

职位标题：

1. BIG DATA ANALYST

   大数据分析员

2. BIG DATA ENGINEER

   大数据工程师

3. BIG DATA ARCHITECT

   大数据架构师

4. BIG DATA ANALYTICS BUSSINESS CONSULTANT

   大数据分析业务顾问

5. BUSSINESS INTELIGENCE AND ANALYTIC CONSULTANT

   商务智能和分析顾问

Figure: Job analytics of BIG DATA

图：大数据作业分析

Conclusion:

结论：

Till now, I hope I am able to make you all understand the difference between BIG DATA ANALYSIS and DATA MINING, and futures scopes in BIG DATA. If you have any query or suggestion please do post it in the comment section, will surely focus on them. In my upcoming articles, we will be discussing more BIG DATA and upcoming trends of IT World, till then stay healthy and keep learning!

到现在为止，我希望我能使大家理解BIG DATA Analysis和DATA MINING之间的区别 ，以及BIG DATA中的期货范围 。 如果您有任何疑问或建议，请务必将其张贴在评论部分，一定会专注于它们。 在我即将发表的文章中，我们将讨论更多的大数据和IT世界即将出现的趋势，直到您保持健康并继续学习！

翻译自: https://www.includehelp.com/big-data/big-data-analytics-and-data-mining-future-scopes-of-big-data.aspx

大数据分析和数据挖掘区别