Four Ways to Deal with the Shortage of Big Data Talents

Four Ways to Deal with the Shortage of Big Data Talents _ Data Analyst Examination

IDC said in a research report on the growth trend of big data that compared with other business intelligence (BI) tools, the growth rate of visual data discovery tools in the market is 2.5 times that of other tools. The cost growth rate of cloud-based big data and analytics (BDA) solutions will be three times that of other types of on-premises solutions.

However, in the next few years, the field of big data will continue to face the embarrassing situation of serious shortage of talents. IDC predicts that by 20 18, there will be 18 1000 in-depth data analyst positions in the United States alone, which will be five times as many as those related to data management or requiring interpretation skills. However, there are not enough qualified applicants in the market to fill these vacancies.

Gartner said that this year, the demand for big data will create 4.4 million jobs worldwide, but only one-third of the jobs can recruit suitable talents.

This is because big data analysis requires more skills than just using dashboards to monitor data flows. Talents in this field need to have high-level skills in data science to set corresponding search and parameters, so as to design filtering algorithms. Such talents need a master's degree or even a doctorate. Without relevant skills, it is impossible to obtain the corresponding industry qualification certification.

According to Burtch's survey in 20 13, nearly 90% of big data professionals have master's degrees or above in statistics, applied mathematics, operational research or economics and other related disciplines.

According to another survey by McKinsey Global Institute, it is estimated that by 20 18, the United States will face a shortage of about1500,000 big data experts.

So, if your company can't recruit relevant highly educated big data experts, how should your company deal with it? In the next part of this article, I will introduce you to four alternative methods to help your enterprise discover, cultivate and retain relevant big data talents.

1. Start with someone who really knows your business.

"I very much agree with the assessment of the shortage of big data skills," said Nick Hodek, director of Gartner's Information Management Research Office. "Many corporate customers don't even know what skills they need to start with, let alone how to learn these technologies. They don't realize what problems their enterprises will face and the analytical skills that need to be solved urgently. "

Companies usually think that they need a professional with a doctorate in advanced data science or mathematics, but Heudecker says an alternative is to find someone who is really familiar with your business and teach them relevant analytical skills.

It is more important to start from understanding the business of your enterprise than from understanding machine learning. Enterprises can teach employees data processing and statistics, or find someone with a degree in programming background. He said that enterprises can train these people more and let them join your company's big data and advanced analysis team.

2. Cultivate your own superstar.

Xiao Min, head of field engineering technology at Tamr, a leading big data software provider, said that in the past five years, he interviewed about 500 people and actually recruited about 40 to 50 people. He agrees that it is difficult to find the right big data analyst, but he also has his own way to find talents.

"My trick is to find talents who are not superstars at present but have the potential to grow into superstars. I have tried to hire many young people who have never been data scientists, but I can see that they have great potential in this field; Or those who have only intermediate or advanced level potential, have not done any work related to data science at present, but have the potential to grow into a powerful master in this field. " He said.

The potential he values is mainly academic qualifications, including academic qualifications and schools. The talents he inspected mainly came from statistics, computer science and other related majors, and sometimes included physics. Of course, physics may not be the first choice for data analysis, but Xiao said that he cooperated well with these people.

"First of all, if they have a degree in physics, they are very smart. They have been trained in mathematics courses, but modern physics courses still require them to do a lot of programming. Therefore, although they may not have received formal training in computer science, they already have the computer skills needed for the role of data scientists, and many of them are even good at it. " He said.

On the other hand, he is concerned about whether graduate schools applying for talents emphasize mathematics and science, such as MIT, Carnegie Mellon University, Stanford University, Brown University and Johns Hopkins University. "Some institutions have very high graduation thresholds, so people who graduate from these institutions work hard and have a good attitude." Xiao said: Editor: qxcpw24895.com.

3, looking for Excel experts

Jason Chavarry, manager of Hershey's talent analysis department, discovered big data talents in another unusual field: Microsoft Excel users.

"Excel can be said to be a fertile ground, from which many people gain the ability to own big data and are often consulted to help other jobs," he said.

He added that Excel is an entry-level channel for people to learn, especially in analyzing big data and discovering its basic functions. "Everyone uses a lot of basic functions. How do you make notifications or spreadsheets, and what rules do you create? Excel goes through everyone. You can use it for basic statistics, basic data analysis and visualization, "he added.

He added that Excel is an entry-level learning channel to learn the basic functions of big data analysis. "Each of us generally just learned many of its basic functions. For example, make a report or spreadsheet. But we can actually create some corresponding rules through it. Using its basic statistical functions, some basic data analysis and visualization are realized. " He added.

But Chavarry pointed out that projects of different sizes also need different tools. For the analysis project of 5000 lines of data, using tools such as SAS or R will undoubtedly be overkill, but using Excel is perfect. And if there are 200,000 rows of data, the function of Excel is obviously not powerful enough. At this time, you need big data software and programming knowledge, but it is not limited to a specific language.

"You really don't need to pay special attention to which language to use. If an employee can achieve it in one language, he must be able to achieve it in other languages. Therefore, your company is looking for talents with learning ability. " Chavali said.

4. Cultivate talents by yourself

In view of the scarcity of big data talents, the solution of most enterprises will be to cultivate talents themselves. According to CMO· Ashley Strapp of Talend, a big data software integration company, the company has achieved good results by establishing a mentor program for experienced experts to cultivate young talents.

"There is a kind of people who can act as a bridge between grafting their own business departments and emerging technologies." Ma Wei said. "Usually, people in business departments of enterprises have not realized the potential of new technologies for business progress. For some high technologies, they don't know how to use them."

Unfortunately, it is quite difficult to retain talents. Talend's customers say that they have trained some people to accept new technologies, and then this person is likely to be poached by other companies with a salary of 50% or even higher, so it is difficult for them to find suitable talents, and it is even more difficult to retain them after training.

So, how should enterprises retain these talents? Signing a short-term binding contract agreement may damage the relationship with employees. "The key is to let these professionally trained talents show that they can fully use and display their skills in your enterprise. If they stay in your company, they will have more valuable potential. In addition, companies need to set certain expectations instead of looking at contracts, "Strapp said.

Xiao also faces the same talent competition problem. He said that his Tamr company tried to inspire the team consciousness of the hired talents and encourage them to find value in the company. "When employees find colleagues who speak the same language as themselves, they usually realize that this is the team they are willing to cooperate with in the next few years. In view of the fierce market competition, we sincerely hope that employees can succeed in outside companies, otherwise we will not be able to attract better talents. " He said.

Heudecker also believes that companies should encourage talents, not bind them. "Your business may not need a team of doctors. Maybe only a person with a master's degree in statistics, computer science and business administration is needed. Investigate employees who may only have a bachelor's degree to see if they are interested in data analysis. Companies should provide inspiring basic training and methods to ensure that employees stay in the enterprise, because these skills are so urgently needed today. " He said.

Heudecker said that in the end, big data will become the new normal and the talent pool will also expand. "If we look at the infrastructure of big data, it is very similar to the RDBMS market in the 1980s. At that time, they were not widely used, but people were already deploying and building them. The same thing will happen in the field of big data. "

The above are the related contents of Bian Xiao's four ways to deal with the shortage of big data talents. For more information, you can pay attention to more dry goods sharing of global ivy.