Is Big Data Analyst Easy to Learn? Where is it better to sign up?

What does a data analyst do:1. Support various routine or temporary data analysis needs;

2. Provide analysis and suggestions related to various businesses;

3. Dig deep into the valuable information of users or products through modeling;

4. Communicate and coordinate with various departments and propose various new data analysis projects or programs;

5. Continuously improve the work of data collection, processing, analysis, reporting and other processes.

Grow into oneExcellent data analystIt not only requires a solid technical foundation, but also requires long-term industry accumulation, which cannot be achieved quickly. If you want to learn quickly, you need to start with the following important points:

Databases

If you go for an interview for a data analyst position, more than 95% of the time you will be asked about the database.

python and rPython and R are the mainstream data analysis scripting languages, and mastering one of them is enough to cope with most of the data analysis work.

Data visualizationData visualization is an important part of a data analyst's job. The most important visualization tool is the well-known ExcelIf you can make clear and easy-to-understand graphs in Excel, you will be considered at least qualified.

To be a good data analyst, you need to have a bachelor's or master's degree in applied mathematics, statistics, and quantitative economics. So it's better to learn through this kind of big place.

With the popularity of big data, or under the influence of big data, many enterprises have begun to really value data and really expect to mine value from data. Even many companies are already using data as a strategy to gain a competitive advantage. The realization of the true value of data does not matter how fast the development of computing efficiency and storage is.

There must be an "analyst", and it can be said that the data analyst is not only the overall designer of the "data edifice", but also the worker who builds the "data edifice".

Data analysts are the most scarce talents, and I believe that they will be one of the most sunrise industries in the next 10 years. So now many friends want to transform into data analysts, and many graduates are also preparing to become data analysts. But a lot of people don't know what it really takes to be an analyst?

To step into a data analyst, you may only be able to start as a "worker" (which means that for a long time, your work content may be boring, and you may be doing less "technical" work), and slowly when you become a "skilled worker", and with the accumulation of industry-related knowledge and various skills, you will gradually embark on the road of "data designer". Start working in a "high-level" or more technical job.

1. Spend at least three months mastering the technique.

If you want to be a "worker", or even a familiar worker, you also need a lot of skills, because data analysts are also technical jobs. I think you'll need to spend at least 3 months learning some of the basics.

1. Spend 1 month learning database knowledge.

2. Spend 1-2 months learning basic statistical knowledge.

3. Spend 1 month learning some linux knowledge.

4. Spend 1 month to learn the most basic data mining model:

5. It takes 1 month to master the operation of a basic mining software.

Analysts must have an attitude of continuous learning, so they must maintain an attitude of continuous learning in their follow-up work. Insist on learning all kinds of knowledge, not just at the skill level.

2. Select the industry you are interested in.

If you are already working, choose this industry or related industry. In this way, you have industry experience and business knowledge that you will have an advantage. Because you are more aware of the "pain points" of the business

As a result, you have a relatively good idea of what kind of data you should provide to the business.

If you are a student, analyze your interests and combine them with the more popular industries now (referring to the fact that data is also relatively hot in this industry).

Through the Internet learning, talk about the business model, data content, and analysis points of this industry. If you have the opportunity, you can go to some peer salons or share to have a clear understanding of what data analysts or peers in this industry are usually doing.

Compared with their own in-person knowledge reserves, more targeted supplementary knowledge. A sentence of encouragement with classmates at school: "Everything you learn in school is useful, but the school doesn't tell you how to use it!" ”

3. Start looking for opportunities.

For students who transfer across industries, when you are ready for the above. Start looking for a chance:

1. Internal transfer.

2. Choose small and medium-sized companies. Start first, then practice.

At present, the implementation of the national big data strategy has reached a critical period of landing, and the innovation and development of the big data technology industry, the deep integration of big data and the real economy, as well as the security management and legal regulation of big data have entered the critical stage. At present, the demand for big data talents in the entire IT industry is still relatively large, and the employment situation of graduate students in related directions is still relatively good in recent years.

You can learn it from scratch

Zero-based can learn big data, as for whether it is good to learn or not, it must depend on the personal situation, everyone's learning ability to understand the ability, if the person with strong learning ability should learn should feel that it is not difficult to learn, no matter what he learns, it is actually the same, it takes effort to get the harvest, my child does not have the foundation to go to the halo big data.

OK. Getting started is relatively straightforward. Data analysis does not require a strong science and engineering background, but those with a background in marketing, finance, finance or retail will have a more open analytical mind.

The salary package is high. The average monthly salary for a big data analytics position with 1 or 2 years of work experience can reach the level of about 13k. The salary of the position is positively correlated with experience, and the older you are, the more valuable it is.

The industry is adaptable. Data is applied in almost every industry, and not only in the connected IT industry.

Personally, I think it is difficult to learn big data with 0 foundation, but now many training institutions say that they can learn big data with 0 basis, you can take a look at it on the Internet.

It is very difficult to learn big data from scratch, because big data training involves the knowledge of mathematics, statistics and computer programming, if you do not have a science and engineering background, if you graduate from pure liberal arts, it will be very difficult to learn, after all, the competition is so strong now, many people who want to change careers with a science and engineering background are very hard, and those who have no foundation have to work harder.

It depends on your mindset. If you really want to learn well, you should understand the course, the content to be learned, the techniques to be mastered, and find a good teacher to take you. But if you're just on a whim, think about it.

I'm also 0 foundation, I'm still a liberal arts student, and I also plan to learn the data analysis and mining of Gami Valley Education in September, and I'm still on a field trip, and I'm going to audition, you can find a partner to work with, so that it's easier for everyone to learn together.

Hello, yes, the data on the Internet is growing by 50% every year, and it will double every two years, and more than 90% of the world's data is only generated in the last few years. According to IDC**, the world will have a total of 35 zettabytes of data by 2020. The Internet is the outpost of the development of big data, with the development of the times, people seem to be accustomed to their lives through the network for data, easy to share and record and recall, through the continuous innovation of all walks of life, big data will gradually create more value for human beings, now zero-based learning words know that the magic has 12 years of teaching experience and resource library, I believe that as long as you work hard to learn there is no difficult problem.

You can learn, there is nothing difficult in the world, only afraid of people with hearts. However, at present, the training institutions are foolish and mixed, some institutions are quite so-so in terms of tool teaching, and most of the teachers in training institutions have not done business analysis projects at all, and many ways of thinking may mislead you. Jiudaomen is more formal, it is under Cassia Ming, and it specializes in data analysis services and often gives training to enterprises.

Big data analysts need to learn: JA-VA, big data basics, Hadoop system, Scala, Kafka, Spark, etc.; Data analysis and mining: Python, MySQL, MongoDB, Redis, data processing, data analysis, etc.

What does a big data analyst do

1.The data is processed.

There are many tools for data processing, but basically all of them can't avoid the two core Excel + SQL.

2.Learn about the business.

If you want to help you make decisions, you must first understand what the other person is doing. How to understand the business? Look at the performance of the business through data, communicate with the demand side, participate in the meeting of the demand side, and rotate to the demand side.

These contents can be recorded with flowcharts + documents to help you understand the business process and details.

3.Communicate information visually.

It is necessary to effectively convey information to the demand side, and it is necessary to use a reasonable way to convey information. Visualization is a common and effective way, and most of the requirements can be accomplished by using Excel here, but it is more recommended to master a BI tool.

Data analysts need to learn statistics, programming skills, databases, data analysis methods, data analysis tools, etc., and also be proficient in using Excel, be familiar with and proficient in at least one data mining tool and language, have the ability to write reports, and have a solid SQL foundation.

1. Mathematical knowledge.

Mathematics is the basic knowledge of a data analyst. For junior data analysts, it is enough to understand some basic content related to describing statistics, have a certain ability to calculate formulas, and understand common statistical model algorithms is a plus.

2. Analytical tools.

For junior data analysts, playing with Excel is a must, pivot tables and formulas must be proficient, and VBA is a plus. In addition, it is better to learn a statistical analysis tool, SPSS as a starting point.

For senior data analysts, the use of analytical tools is a core competency, a basic must for VBA, at least one of them must be proficient in the use of SPSS SAS R, and other analysis tools (such as MATLAB) as appropriate.

3. Programming language.

For junior data analysts, they can write SQL queries, and if necessary, write Hadoop and Hive queries, which are basically OK. For senior data analysts, in addition to SQL, it is necessary to learn Python to obtain and process data with half the effort. Of course, other programming languages are also possible.

Data analysts can be engaged in: IT system analysts, data scientists, operations analysts, and data engineers.

The Big Data Analyst exam needs to be registered at an institution authorized by the Education and Examination Center of the Ministry of Industry and Information Technology.

Big Data Analyst Profile:

Big data analyst refers to the process of scientific analysis, mining, display and use for decision support of big data based on various analysis methods.

Application conditions for data analyst at the beginning level:

College degree or above in statistics, mathematics, economics, management or related majors; Have more than one year of work experience; Be of good character; Be physically and mentally healthy; Discipline. Pass the primary written test, computer-based test, report assessment, and all the results are qualified. You need to ask He Zhi to prepare the following materials:

An electronic photograph of the applicant; I have both sides of the front; My academic certificate; Fill in 1 copy of the training registration form; Prepare the above information and send it to the relevant big data analyst admissions teacher of the registration unit; At the same time, the relevant registration fee shall be paid.

The Role of the Big Data Analyst:

Big data analysts can make enterprises have a clear understanding of the current situation and competitive environment of the enterprise, risk evaluation and decision support, and can make full use of the value brought by big data. Therefore, big data analysts are no longer simple IT staff, but core people who can participate in the development of enterprise decision-making.

Data analysis can be said to have a long history, and Mr. Bookkeeper can also be called a data analyst in a sense, analyzing current accounts, receivables, expenses, etc., but this is not big data analysis, just statistics based on their own data, so to understand the responsibilities of big data analysts, we must understand the difference between data analysis and big data analysts.