大數(shù)據(jù)分析和數(shù)據(jù)挖掘區(qū)別

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.

大多數(shù)人在大數(shù)據(jù)和數(shù)據(jù)挖掘之間產(chǎn)生了混淆。 在本文中，我將嘗試使您理解兩者之間的區(qū)別，以后我們將重點(diǎn)關(guān)注大數(shù)據(jù)的未來范圍 。

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.

大數(shù)據(jù)和數(shù)據(jù)挖掘是完全不同的兩件事。 它們之間的唯一相似之處，或者我們可以說，與大數(shù)據(jù)和數(shù)據(jù)挖掘有關(guān)的唯一事情是使用可用于業(yè)務(wù)或其他目的的大數(shù)據(jù)集。 但是數(shù)據(jù)挖掘和大數(shù)據(jù)分析都用于兩種不同的操作。

大數(shù)據(jù)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).

這是不同公司通常用于分析較大數(shù)據(jù)集的過程，目的是發(fā)現(xiàn)他們需要的信息。 通常要了解市場(chǎng)趨勢(shì)，客戶的興趣，他們的偏好，隱藏的模式以及未發(fā)現(xiàn)的相關(guān)性。 這種分析通常會(huì)帶來新的商機(jī)，提高運(yùn)營效率，提高營銷成功滿足公眾需求(客戶的偏好)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，大多數(shù)公司都依賴大數(shù)據(jù)分析來建議/建議他們制定各種業(yè)務(wù)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:

大數(shù)據(jù)分析還可以用于分析常規(guī)業(yè)務(wù)程序可能尚未發(fā)現(xiàn)的數(shù)據(jù)。 這包括：

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

  一項(xiàng)公共調(diào)查的回復(fù)電子郵件的分析。

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

  來自連接到物聯(lián)網(wǎng)的不同傳感器的數(shù)據(jù)分析。

• Social media data aggregation and activity reports.

  社交媒體數(shù)據(jù)匯總和活動(dòng)報(bào)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:

大數(shù)據(jù)分析對(duì)于企業(yè)而言是非常富有成果的選擇，并且可以很好地促進(jìn)公司業(yè)務(wù)的發(fā)展。 但是問題在于實(shí)現(xiàn)，例如：

• Cost of hiring big data experts are quite high.

  聘用大數(shù)據(jù)專家的成本很高。

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

  處理如此大量的數(shù)據(jù)對(duì)管理層來說是一個(gè)巨大的挑戰(zhàn)。

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

  Hadoop系統(tǒng)與數(shù)據(jù)倉庫的集成提出了另一個(gè)巨大的挑戰(zhàn)。

Figure: Big Data Analytics

圖：大數(shù)據(jù)分析

數(shù)據(jù)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.

數(shù)據(jù)挖掘也被定義為知識(shí)發(fā)現(xiàn)。 它正在從不同的角度觀察數(shù)據(jù)，并準(zhǔn)備包含有用信息的摘要。 數(shù)據(jù)挖掘的結(jié)果信息通常用于減少運(yùn)營支出。 數(shù)據(jù)挖掘中使用的軟件程序?qū)儆跀?shù)據(jù)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.

從技術(shù)上講，我們可以說數(shù)據(jù)挖掘包括在大范圍相關(guān)數(shù)據(jù)庫中發(fā)現(xiàn)模式或關(guān)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.

進(jìn)行數(shù)據(jù)挖掘是為了協(xié)助提取以前未知的數(shù)據(jù)模式，包括數(shù)據(jù)記錄中存在的異常，對(duì)包含數(shù)據(jù)的文件進(jìn)行聚類分析。

Figure: Data Mining

圖：數(shù)據(jù)挖掘

.minHeight{min-height: 250px;}@media (min-width: 1025px){.minHeight{min-height: 90px;}} .minHeight{min-height: 250px;}@media (min-width: 1025px){.minHeight{min-height: 90px;}}

大數(shù)據(jù)的未來范圍 (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.

如果您仍然對(duì)自己的領(lǐng)域感到困惑并且仍在尋找選擇，那么有一些原因一定會(huì)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，企業(yè)界對(duì)分析專業(yè)人員的需求不斷增長。

Figure: Job trends in BIG DATA

圖：大數(shù)據(jù)中的工作趨勢(shì)

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.

作為高需求數(shù)據(jù)分析，對(duì)熟練專業(yè)人員的需求也在增加，這使得大數(shù)據(jù)為正確的技能付出了高昂的代價(jià)，不僅限于印度，它流向澳大利亞，英國等國家。

PRIORITY:

優(yōu)先：

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

這是跨國公司和其他公司的頭等大事，統(tǒng)治著整個(gè)全球市場(chǎng)。

Figure: Priority of BIG DATA

圖：大數(shù)據(jù)的優(yōu)先級(jí)

JOB TITTLES:

職位標(biāo)題：

BIG DATA ANALYST

大數(shù)據(jù)分析員

BIG DATA ENGINEER

大數(shù)據(jù)工程師

BIG DATA ARCHITECT

大數(shù)據(jù)架構(gòu)師

BIG DATA ANALYTICS BUSSINESS CONSULTANT

大數(shù)據(jù)分析業(yè)務(wù)顧問

BUSSINESS INTELIGENCE AND ANALYTIC CONSULTANT

商務(wù)智能和分析顧問

Figure: Job analytics of BIG DATA

圖：大數(shù)據(jù)作業(yè)分析

Conclusion:

結(jié)論：

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!

到現(xiàn)在為止，我希望我能使大家理解BIG DATA Analysis和DATA MINING之間的區(qū)別 ，以及BIG DATA中的期貨范圍 。 如果您有任何疑問或建議，請(qǐng)務(wù)必將其張貼在評(píng)論部分，一定會(huì)專注于它們。 在我即將發(fā)表的文章中，我們將討論更多的大數(shù)據(jù)和IT世界即將出現(xiàn)的趨勢(shì)，直到您保持健康并繼續(xù)學(xué)習(xí)！

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

大數(shù)據(jù)分析和數(shù)據(jù)挖掘區(qū)別

總結(jié)

以上是生活随笔為你收集整理的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...的全部內(nèi)容，希望文章能夠幫你解決所遇到的問題。

如果覺得生活随笔網(wǎng)站內(nèi)容還不錯(cuò)，歡迎將生活随笔推薦給好友。