Learn as you want ---- manage our learning according to "procedural"

Sometimes, we are always thinking that the technology we have learned can guide our life and work. After listening to Mr. Bao's class tonight, I seem to be inspired.

The first lesson is about data centers for cloud computing and real-time data processing. Although there are many memories of the content, I personally feel that I have a good grasp of the future trend. I explained in detail why the server market is so important and why Huawei is so important to its server product line. In fact, in the future, IDC will occupy a large proportion of the trend, and the launch of the cloud will inevitably reduce users' Storage Investment and then decrease. A large number of files are stored on the remote server. The current conflicts are mainly about the user's perceived response time. In addition to the network and client response time, the data center's processing time accounts for 50-60% of the total. How to optimize and shorten this time can be achieved by technology. That is to say, the user's terminal may be different, but the IDC can greatly shorten the response time after optimization. This improves the network marketing success rate in the future.

Let's talk about real-time data processing. At present, our data analysis is based on comprehensive capturing, offline storage, and analysis. The arrival of the big data era, it is bound to require us to analyze and respond to data in real time to a level close to intelligence. This is the efficacy of machine intelligence. To give a simple example, when you are traveling outside, you will be given a promotion Promotion every time you swipe a card and convert traditional passive marketing into active marketing. This aspect has already been used in foreign countries, but it is still in the promotion stage in China. There is also cross-platform Data Mining and analysis. The generation of big data is no longer like the traditional PC-based, but PC, pad, phone... therefore, mobile Internet Data Mining and analysis are inevitable. This is believed to be a challenge to the future server processing.

Simple Beauty

The front is both technical and this part. My personal understanding is some of the processing methods we encounter when developing a program or system.

Sometimes I am also a perfectionist, which is not desirable at work, especially in system design. As Mr. Bao said, this is also true in our work, especially when we are doing something unprecedented or innovative, we need to do more simply. That is to say, it takes 20% of the time to complete the system. Then we spent 80% of our time optimizing our system.

Sometimes, the same is true for a job. Few people can complete a job at a time. One drawback of perfectionist is the constant frustration. In a job, we need to have the idea of engineering nodes, divide a very important job into several smaller points, and then finish the work. Review and reflection with the most time left. This is the core of improving our programming capabilities.

Finally, we also talked about entrepreneurship. Just remember one sentence. You cannot write one hundred good papers as well as start a business. It makes sense to let your technology make your system truly create value. For the first time, I heard that no one wants to be a CEO who only needs to pull venture capital and cannot make the company bigger!

Entrepreneurship requires a balanced team and a suitable person in every aspect of technology, market, and management. You need to know your own shortcomings and make up for them through a team.

There is also the definition of "codenon": Super "codenon" write programs are not executed by machines, but executed by people! Later, I figured out that if we manage our learning based on the "procedural" approach, you will find that there are not many things you need to learn, and you need to understand and master a lot of things. This is the strength of IT professionals.

More "procedural" thinking is applied to work and life, so that your life is simple and full! Come on!

This article is from the "Data Mining and Visualization" blog. For more information, contact the author!