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Big data was praised as the “new oil” by The Economic Journal in 2017 because of its hidden value. Data-oriented work has also become one of the aspirations of many people, especially data analysis.
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“By 2020, corporate spending based on big data analysis will exceed us $500 billion, and big data will help global enterprises earn about US $1.6 trillion in revenue dividends in the next four years.”
— INTERNATIONAL well-known data company IDC \
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For many people, however, it is still a vague concept that feels remote. In fact, this is not the case. Linkedin mentioned in its 2016 Report on The Hottest Jobs in China that the global shortage of basic data talents has increased to 15 million. For companies and individuals, mastering data-related skills holds the future. \
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Data analysis = Future skills? = Catch it early?
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Some people might ask, “I don’t want to be a data analyst, so don’t I have to learn this skill?” The answer, of course, is:
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It is almost all walks of life “cure-all”, promotion and salary increases, the reason is:
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(1) Business decision-making needs are inseparable from data analysis, especially data analysis thinking.
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In recent years, the author from the original simple data report forms in the maintenance of the development, modeling of all walks of life business solutions to problems, exposed to more core technology in the field of data analysis and thinking, more and more feel data analysis, should the business problem is an effective tool, can be “live in the future” thinking, through the data to analyze the real thing and recognition ability, As stated below:
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“Think analytically, rigorously and systematically about business problems and come up with solutions that impact that data.”
— Michael O ‘Connell, Senior Director of Analytics at TIBCO
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Therefore, in the wave of big data and artificial intelligence, as long as companies have business decision-making needs, they cannot do without data analysis as a “tool”. If you do not understand data, you will miss a hot position to a large extent. Even if you entered a big platform such as Ali, Didi and Tencent a few years ago, you will be killed on the beach by newcomers in the wave of big data.
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(2) In addition to full-time data analysts, there are more positions that require data analysis skills \
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Think back to the scenes we come into contact with every day in our daily life: from wechat moments and SMS promotion, commodity recommendation from e-commerce platforms such as Taobao and Jd.com, content push from media such as Toutiao and Tiktok, and even travel route optimization, all of which rely heavily on data-based decision results. No matter where you are in the company, from full-time data analysis, marketing, sales operations, to customer service, you need to master data analysis skills.
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In addition, the Ministry of Education approval of Peking University in 2016, such as one of the few schools have relevant professional “big data analysis”, that is, trained analysts, until in 2020 May be out of work, and now into the line, or study data analysis skills, and is also a veteran, the first step, over time, The future is definitely the leader in the industry.
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“Learning is like rowing upstream; if you do not advance, you will drop back.” In this wave of big data, do you choose to swim upstream or enter turbulence? I’m sure you know what you’re doing.
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Data analytics = Scarce skills today? = high salary?
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While big data brings great commercial value, it also faces great demand for talents. According to the “Big Data Talent Report” released by Digital Link Search, there are only 460,000 big data talents in China at present, and the shortage of big data talents will reach 1.5 million in the next 3-5 years.
The data talent gap is bigger than you think. So it’s no surprise that data talents are getting a hateful treatment in the job market. You can find a “high-paying” career without the benefit of a degree but with the added benefit of data analysis skills.
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Not to mention data-dependent platforms such as Alibaba, Didi and netease have doubled the number of job hunting options and a wider range of “money” options.
(The data comes from data analysis job recruitment data such as Hook, Liepin, 51Job and Zhaopin) \
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In addition to high salaries, the hot demand for data analysis is also reflected in the following aspects:
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1) Wide industry applicability: At present, the data analysis job gap is mainly concentrated in the three giant industries: mobile Internet, computer software and finance, accounting for 64% of the total, while the atypical data industry, subtle and rapid rise. It shows that data analysis is a universal skill in all industries, and everyone can expect a good income level. \
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2) Diversity in career development. The initial development direction can be subdivided into BI expert, model algorithm expert and business analysis expert. There is no lack of such classic cases in the circle: technical posts accumulate data analysis thinking and skills, and transfer to product manager, operation manager, management manager, and even Sales at the company level, and they are all outstanding in the same period.
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3) Getting started isn’t hard, and it gets better with age. Many data analysts are not all trained, some from the economy, management, chemistry, and even English majors, the entry of data analysts is not as difficult as we imagine, on the contrary, it is a high salary, the market is in short supply, the hot job with large development space. If you post a job change on a major recruitment website like Hook or Liepin, you will be locked in by HR and headhunters within hours.
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In a short period of two or three years, research reports from various industries show that big data will be the core asset of each company now and even in the future, and its commercial value will be higher and higher, and demand will exceed supply for a long time. I believe that as long as you have a basic introduction to data analysis and a good command of business knowledge, the career path will be relatively smooth.
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Read here perhaps you have now overcome psychological difficulties, decided not to be an onlooker, but the leader of The Times, as a zero-based white or a master with a certain foundation, how should I go further and further on the road of data analysis?
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Novice xiao Bai + Silicon Valley authority learning platform = Get data analysis skills
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Because of the scarcity of high salaries, a new group of talent gap dividend, quick talent can grasp the opportunity. For starters, Udacity is an efficient and reliable choice for data analysis.
Udacity’s [data Analyst] nanodegree, launched in partnership with global data leaders such as Kaggle X Tableau, has trained more than 20,000 data analysts worldwide.
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Udacity is a silicon Valley cutting-edge technology learning platform founded by Sebastian, the founder of Google’s self-driving car. Its nanodegree program is a learning certification program created by Udacity in collaboration with tech industry leaders such as Google, Amazon, Facebook, AND AT&T. To help students to become the sought-after talents who can drive enterprise innovation and change.
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If you join the course, you will be able to quickly get started, master data analysis and become a rare talent through efficient and systematic learning curve, skill map closely following market demand, and close and timely q&A guidance. * * * * * * * * * * * * * * * *
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One of the features of this course is to learn by challenging famous silicon Valley enterprises’ actual combat projects, so that you can deeply master skills through hands-on practice, add valuable practical experience to your resume, and capture the heart of famous enterprises’ HR. Examples of practical events you can challenge are:
Project 1: Air quality in Beijing, Shanghai and Guangzhou \
To obtain PM 2.5 data of 5 big cities such as Beijing, Shanghai and Guangzhou, analyze the change trend of air quality, and learn the data analysis process from questions to visual analysis conclusions.
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Project 2 explores the behavior rules of bike-sharing users
Use Python to analyze shared bike trips and user data, and analyze information such as hottest paths and most typical users. Write interactive code to query data, using descriptive statistical analysis.
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Project 3 explores real data from movies/gun control/sports events
Get selected real data sets from TMDB, HOSPITAL management systems, and FBI databases, and use NumPy and Pandas to experience the entire analysis process to analyze real world issues such as what top-grossing movies have in common and what teams are likely to win games.
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Project 4 reveals what won the battle of Ice and Fire
Get game of Thrones war data, analyze the factors that influence the outcome of the war, review the analysis process from questions to visuals.Find the battle winning formula hidden in words!
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By the end of the course, you will have a strong knowledge base and have accumulated experience as you have honed your field projects. Actual combat project experience can be written resume, for job interview extra points!
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The above is only the “data analyst” nano degree part of the actual project content. Udacity also has a special “7-day value trial class”. To ensure the quality of tutoring, seats are limited while stocks last.
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Add a Udacity Learning Planner and add the “Course Selection Test” to get priority access to the course selection test, the full course outline, and a limited number of value entry points on a first-come-first-grab basis.
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If you are interested in data analysis, but you are not sure whether you are really suitable for it or whether you can finish it, you are advised to join the 7-day trial and let a professional tutor take you hand in hand to complete your first data analysis project!
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