如何高效启动大数据应用之旅？

In my previous article, I discussed what is big data? What are the differences between big data& data mining, what are the future scopes of big data? In this article, we will discuss how to get started with big data?

在上一篇文章中&＃xff0c;我讨论了什么是大数据 &＃xff1f; 大数据与数据挖掘之间的区别是什么 &＃xff1f; 大数据的未来范围是什么 &＃xff1f; 在本文中&＃xff0c;我们将讨论如何开始使用大数据 &＃xff1f;

As we all know that field of big data is very vast and as it is a new technology these days so, it can be quite challenging to start learning whoever wants to do so. So, in this article, I will try to show you a guided path to start the journey with big data and grab a good job of big data in companies. Here, in this article I have tried to describe & guide through step by step, hope, it will help you all, to get on the right track.

众所周知&＃xff0c;大数据领域非常广泛&＃xff0c;并且由于这是当今的一项新技术&＃xff0c;因此开始学习任何想这样做的人都可能会面临很大的挑战。 因此&＃xff0c;在本文中&＃xff0c;我将尝试向您展示一条指导性路径&＃xff0c;以开始使用大数据的旅程&＃xff0c;并抓住公司中的大数据工作。 在本文中&＃xff0c;我试图逐步描述和指导&＃xff0c;希望对您有所帮助&＃xff0c;以使您走上正确的道路。

脚步 (Steps)

The first and the most important step is to determine the right role according to our interests and skillset we have. Without determining our goal (position or role) for which we want to prepare it will be like "shooting in the dark".

第一步也是最重要的一步是根据我们的兴趣和技能确定合适的角色。 没有确定我们要为其准备的目标(位置或角色)&＃xff0c;就像“在黑暗中射击” 。

So, first we have to determine our role, now basically if we speak broadly the roles in the big data industry can be classified into two major categories:

因此&＃xff0c;首先&＃xff0c;我们必须确定我们的角色&＃xff0c;现在基本上&＃xff0c;如果我们大致讲大数据行业中的角色&＃xff0c;可以分为两大类&＃xff1a;

1. Big Data Engineering

   大数据工程

2. Big Data Analytics

   大数据分析

Let us discuss about the roles and requisites of big data analyst and big data engineer/ developer.

让我们讨论大数据分析师和大数据工程师/开发人员的角色和必要条件。

大数据工程师或开发人员的角色 (Role of Big Data Engineer or developer)

• As the word engineer suggests, you should know how to engineer the big data, means you should be able to see a different perspective or different outcome of the same data that all others are seeing as normal bulk or mess of data.

  就像工程师一词所暗示的那样&＃xff0c;您应该知道如何设计大数据&＃xff0c;这意味着您应该能够看到同一数据的不同视角或不同结果&＃xff0c;而其他所有人都将它们视为正常的批量或混乱数据。

• You have to figure out that the bulk of data and also have to figure out how the SQL database works effectively.

  您必须弄清楚大量数据&＃xff0c;还必须弄清楚SQL数据库如何有效地工作。

• You should be able to handle the bulk of data using technologies like Hadoop/Spark, programming languages etc.

  您应该能够使用Hadoop / Spark&＃xff0c;编程语言等技术处理大量数据。

BIG DATA开发人员/工程师的需求 (Requisites for BIG DATA developer/engineer)

1. Should have a good grip over SQL, core Java, JS, OOAD (object-oriented analysis and design).

   应该对SQL &＃xff0c; 核心Java &＃xff0c; JS &＃xff0c;OOAD有良好的掌握(面向对象的分析和设计)。

2. Should have preliminary knowledge of R and python

   应该具有R和python的初步知识

3. Mastering with different tools like Hadoop, MapReduce, Spark etc.

   精通Hadoop&＃xff0c;MapReduce&＃xff0c;Spark等不同工具

4. Having a good analytical problem-solving approach, problem- solving, code writing skills.

   具有良好的分析性问题解决方法&＃xff0c;问题解决能力&＃xff0c;代码编写能力。

Figure: Skillset for data scientist

图&＃xff1a;数据科学家的技能

Image source: https://www.experfy.com/blog/a-big-data-analyst-or-a-big-data-developer-what-do-you-want-to-becom

图片来源&＃xff1a;https://www.experfy.com/blog/a-big-data-analyst-or-a-big-data-developer-what-do-you-want-to-becom

大数据开发人员/工程师的需求 (Requisites for Big Data developer/engineering)

The collection of huge data (big data) needs proper analysis for giving expectable and desired results, so, for its proper analysis, there is a need for appropriate database management systems. The main purpose of big data analyzation is to improve or expand the business of companies.

大数据(大数据)的收集需要进行适当的分析以给出预期的结果&＃xff0c;因此&＃xff0c;为了进行适当的分析&＃xff0c;需要适当的数据库管理系统。 大数据分析的主要目的是改善或扩展公司的业务。

Tracking and using the different data of companies like transactions, searches, user profile information, user interest everything should be analyzed in order to extract fruitful outcome.

跟踪和使用公司的不同数据(例如交易&＃xff0c;搜索&＃xff0c;用户个人资料信息&＃xff0c;用户兴趣)&＃xff0c;应该对其进行分析&＃xff0c;以提取出丰硕的成果。

大数据分析的必要条件 (Requisites for BIG DATA ANALYST)

1. Good knowledge of maths and statistics.

   精通数学和统计学。

2. Good knowledge of tools and techniques used in big data storing, processing and analysis, such as Hadoop, Spark etc.

   熟悉大数据存储&＃xff0c;处理和分析中使用的工具和技术&＃xff0c;例如Hadoop&＃xff0c;Spark等。

3. You should have a focused mind and very clear concepts of maths, statistics and different Big Data technologies in order to become a good big data analyst.

   为了成为一名优秀的大数据分析师&＃xff0c;您应该有专心的头脑和非常清晰的数学&＃xff0c;统计学和不同的大数据技术概念。

Figure: Big data analytics

图&＃xff1a;大数据分析

Image source: https://www.experfy.com/blog/a-big-data-analyst-or-a-big-data-developer-what-do-you-want-to-become

图片来源&＃xff1a;https://www.experfy.com/blog/a-big-data-analyst-or-a-big-data-developer-what-do-you-want-to-become

Now, when we have an understanding of roles that suits our skills and interest, so now once we have decided on our role, we can begin with the learning process. As we all know that domain of Big Data is full with various technologies, so, its quite difficult to master them all, so, below I am attaching a Big data engineer/ analyst path flow chart.

现在&＃xff0c;当我们了解适合自己技能和兴趣的角色时&＃xff0c;那么一旦我们决定了角色&＃xff0c;就可以从学习过程开始。 众所周知&＃xff0c;大数据领域已经充满了各种技术&＃xff0c;因此很难完全掌握所有技术&＃xff0c;因此&＃xff0c;在下面我附上了大数据工程师/分析师的流程图。

Figure: flow chart for big data engineer path

图&＃xff1a;大数据工程师路径流程图

Image source: https://www.analyticsvidhya.com/blog/2017/03/big-data-learning-path-for-all-engineers-and-data-scientists-out-there/

图片来源&＃xff1a;https://www.analyticsvidhya.com/blog/2017/03/big-data-learning-path-for-all-engineers-and-data-scientists-out-there/

Conclusion:

结论&＃xff1a;

I hope this article might have helped you to clear up some of the mess running over your mind about how to start learning big data! So, now when once you are decided with your role you can follow the tree and also refer to some top certifications that I mentioned in my previous articles Big Data: an emerging trend on IT sector.

我希望本文能帮助您清除一些关于如何开始学习大数据的麻烦&＃xff01; 因此&＃xff0c;现在&＃xff0c;一旦确定了自己的角色&＃xff0c;您就可以沿用这棵树&＃xff0c;并参考我在之前的文章《 大数据&＃xff1a;IT部门的新兴趋势》中提到的一些顶级认证。

So, now wear your wings and get started, will see you in the next article. Till then Stay connected, be healthy and keep learning!

因此&＃xff0c;现在戴上翅膀开始使用&＃xff0c;将在下一篇文章中见到您。 直到保持联系&＃xff0c;保持健康并继续学习&＃xff01;

翻译自: https://www.includehelp.com/big-data/how-to-get-started-with-big-data.aspx