1 the introduction
The most popular thing in the Internet industry is ABC:
A) artificial intelligence B) BIG DATA C) CLOUD
In alibaba’s economy, THE BIG DATA is DT Dt.alibaba.com/. We use BIG DATA to empower business and create value.
And we say data center, in fact, Ali put forward only two: business center and data center. The purpose of the data center is to complete the four links of data collection, construction, management and use, so that the process of data from production to use becomes silky smooth, not only does not make data assets become burdiness, but also maximizes the potential value of data.
The author is in the big front-end team of Data Center, which not only provides data services for Ali economy, but also focuses on creating its own data center for cloud enterprises. It is at the forefront of front-end technology, business model and product design. Listen to me slowly.
2. Intensive reading
Full link data capability
From the point of view of capability, the data center processes all aspects of data and tracks data from the beginning of data generation. It not only gets through the whole link of data collection, storage, processing, query and consumption, but also enables services in the following ways: Research and development data management platform and monitor data quality, research and development of the business staff product direct services such as data analysis of large, medium and small businesses to provide a unified data services standardized data using the process, the algorithm of the data analysis of service ability, will support data services within the cloud build China customer’s own data, research and development the BI platform to complete the final step of data decision.
Full link data technology
From the perspective of technical architecture, starting from the underlying data acquisition technology, the company gradually builds up data computing and management capabilities, data services, data platforms, data applications and data security.
From the perspective of users, companies’ demands for data can be summarized as follows:
- Where data comes from and how it is fully digitized: corresponding to the full-link data acquisition service.
- How to get the data you want: Data computing, modeling, and management services.
- How to use data: Unified Data Services Platform.
- How to Use Data to make business decisions: BI platform.
- How to secure data: Data security services.
For Alibaba, there are several additional considerations:
- How to make data service horizontally support all business lines: data service platformization, data intelligent service platform and BI platform.
- How to make data services universally beneficial to every enterprise: Data services fully in the cloud.
- How to make data service more valuable: Open up the data system of Ali economy, so that data produce chemical reaction with each other.
Of course, there are challenges, starting with the data barrier, and convincing other teams to let you manage their data is not easy. The second is the value challenge, how to prove the value of the existence of data center, and achieve visible value-added business. Finally, the technical challenge, for the front end, the construction of dozens of data products, the construction of hundreds of thousands of data reports, need a good enough data product building platform to support; The next generation of exploratory analysis of data analysis products also puts forward new requirements for BI engine; Data visualization is far more complex than ordinary visualization. It is not only about performance and readability under big data, but also about understanding the business and making charts that show the value of data analysis.
Whether it is data construction or data visualization, it is another good track in the front-end vertical field, which not only has heavy business value, but also the front-end technology challenge in the new data field. And with the continuous expansion of the influence of data center, our front-end technology will bring more and more influence to the industry.
How do you build and manage data
If you want to use data well, you must first manage it well. In the era of big data, enterprises must establish their own standard data warehouse system to do full link management for data collection, operation and maintenance scheduling, so that big data can become good data and good data can play a value.
Dataphin data warehouse construction platform.
The construction of data warehouse needs to start from the physical space and logical space, that is, the bottom table, through the collection, cleaning and structuring of data, to produce a set of standard data definition.
The so-called normative data definition is the data specification with consistent caliber, algorithm and name, which reduces data ambiguity and improves data search efficiency and accuracy. After that, data modeling means further abstraction of data, which may be abstracted into a Cube model. In this way, at the top level of cognition, all data are cubes of different dimensions, which is convenient for unified understanding.
Finally, the data assets are produced by on-line and off-line scheduling calculation.
How to look at data
Or export an Excel file carefully savour, or as double eleven media big screen as dazzling, or as stock traders like closely staring at the screen, or anytime and anywhere mobile phone browsing. Where to read, how to read and what to read determine the same data can bring different effects and produce different values.
Steady: Double Eleven large screen, from zero to 24 points can be held, every egg, every number beat, silky smooth, this is not playing VCR, every frame is real data display. Compatibility: it is the browser compatibility of business staff users, it is the compatibility of multi-end users, and it is also the large data capacity of BI analysis results. Tolerance, the front end of the show.
“How to look at data” this is exactly the mission and responsibility of data front-end people. Different people, different ends, different needs, this is exactly the challenge to the data front end. And let the user create value through the data, it is also the value of data front-end.
How to analyze data
Under the wave of big data, a variety of data products will be born, and the way of productization can lower the threshold of data application. We hope that everyone can become a data analyst, and BI (business intelligence) products arises at the historic moment, as an important field of big data, BI products with big data meet the needs of the business analysis, support enterprises to carry out the digital transformation, driven into a data-driven decisions from experience, and then bring the excess returns.
QuickBI data analysis tool.
The situation where everyone is a data analyst is growing.
According to Gartner’s prediction of BI product development trend in 2020:
- By 2020, organizations that provide users with access to internal and external data curation catalogs will get twice the business value from analytics investments.
- By 2020, the number of data and analytics specialists in business units will grow at three times the rate of IT specialists, forcing companies to rethink their organizational models and skills.
- Natural language processing and session analytics will increase the use of analytics and business intelligence products from 35 percent to more than 50 percent among new users, especially front-line workers, by 2021.
Rapidly increasing market size.
According to the “Evaluation Report on the Development Level of China’s Big Data Industry” released by China Electronics Information Industry Development Institute, it is expected that the scale of China’s core big data industry will exceed 570 billion yuan in 2019, and the growth rate of the market size will remain around 35% in the next 2-3 years. In the future, the potential market size of BI business intelligence will reach tens of billions of yuan.
Big data and the front-end.
Front-end career development in addition to improving their skills and technical reserves, it is also particularly important to choose the appropriate industry direction and research field. If use the relationship between the road and the car to metaphor, compared the front-end skills to the car, every industry is a road, some way is a country road, some way is the urban and rural roads, and big data worthy industry is the industry of the highway, the traffic is better, the road is more wide, if you have a nice car, why not to a speeding on the motorway?
What are the front-end challenges under big data? Take BI for example, the four directions of BI field: data set, rendering engine, data model and visualization all have many technical points that can be done deeply. Each piece needs several years of in-depth technical experience to be done well, and a large number of talents are required to cooperate. You can also read the Close reading Front End and BI to learn more about BI.
We are the big front end of data
“The front end is not because we use JavaScript, but because we are at the front end of the business, solving problems on the business side, so we are the front end.”
BI analysis of products, data visualization, product building.. We’ve moved beyond the traditional concept of the front end. We do big data table optimization, Web Excel, SQL editor, intelligent visualization. In the data center, we have the natural advantage of complex business scenarios and large amounts of data, forcing you to challenge yourself more to solve business problems. If you love challenge and technology, please join us.
Here you can happily write business code using React, TypesScript, and try out the latest and coolest new React Hooks features. Our team is always on the cutting edge of technology and eager to innovate. You don’t have to worry about your partner’s code style, because we have strict code rules; You don’t have to worry that everyone’s code is an island, because we review every line of code rigorously; You don’t have to worry about your growth space, we have regular technology sharing, small competitions within the team, and enough complex business scenarios to support; You don’t have to worry about wasting away at work. Afternoon tea and lots of snacks are waiting for you!
4 summarizes
Big data front-end talent gap in more than 100 people, because the business growth is very, very fast, before the Spring Festival conditions relax, special approval urgent call!
If you are interested in us, please send your resume to [email protected]! A unique opportunity to respond faster than you can imagine!
The discussion address is: intensive reading “I in Ali Data Center big front end” · Issue #224 · dt-fe/weekly
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