Implementation method of data platform landing

Let the data center really land is the top priority of realizing digital transformation . Enterprises do a good job in data management 、 After the preliminary work of system construction and talent allocation , The next thing to do is the key to the implementation of the data console .

Enterprises should first master the three core elements of data platform construction ： Choose the right data construction method 、 Clarify the construction ideas 、 Avoid the misunderstanding of data platform construction , Finally, realize digital transformation at low cost .

01

Data center design concept

As the most concerned technology platform of enterprises in the current digital economy era , From proposing to responding , And then become a necessary means for traditional industries to carry out digital transformation , Although there is still no unified definition , But the architecture design principle and construction concept behind it are always unchanged and universal , That is to change the previous data governance around “ Poly general ” My place

Rational way , formation “ Use Tongju ” Data construction mode , By reusing data assets , Realize the efficient innovation of front-end business . Under the guidance of this construction principle , According to the size and characteristics of the enterprise , Formulate a midrange construction method that meets the needs .

Three core elements of data platform construction

Starting from the use value of the data center , Its construction content should have three core elements , Be short of one cannot .

01 Data asset governance

When the enterprise market stock becomes smaller , When the traditional extensive business model can no longer bring economic growth to enterprises , Enterprise information construction has been put on the agenda . The electronic management system helps enterprises preliminarily realize organizational structure adjustment and information deployment . And then , The external market increment continues to be compressed , Simple marketing no longer works , The biggest advantage of the data center is to drive the front-end business to innovate quickly and reduce the internal cost .

Maintain data 、 The work of providing data services to drive business growth is often done by enterprises IT Department completion . Combine business features , With digital technology ,IT The Department can be “ Front ” The business unit continues to provide “ ammunition ”. among , The precipitation of data assets is crucial . therefore , In the early stage of data center construction , Traditional information management software and new data fusion technology are needed , Connect the internal and external data of the enterprise in series , Pass inventory 、 planning , Present all data resources ; Through big data development tools 、 Collating data , Including exploring data and blood relationship 、 Data security .

Data asset governance is inseparable from data model management , Model management can help the middle office unify the naming of data fields , Form a unified development specification , Achieve effective data recognition . After the above multiple data governance , Data assets that can be reused by enterprises . in addition , Due to different business and products , There are also differences in the data platform architecture built by each enterprise through software technology , There is no universal or standard data center architecture . Enterprises need to build their own information construction as the basis for the establishment of China Taiwan architecture , Comprehensive consideration of data volume 、 Business features .

02 Shared data services

After the underlying technical architecture of the data platform is built and the callable data assets are formed , We also need to build a data model according to the needs of the business department , In order to provide front-end business teams with uniformly deployable services 、 Shared intelligent data services . Shared data services can provide secure and reliable services for front-end services 、 Easy to operate 、 Uniform norms 、 Extend flexible technical support , For front-end users 、 Product development 、 Customer service 、 Marketing, etc. provide label extraction , So as to provide precision marketing 、 Provide data reference for different applications such as user portrait .

03 Data intelligence applications

The ultimate application direction of the data center is to provide enterprises with services to improve efficiency 、 cost reduction 、 The core driving force of innovative business . therefore , After completing the underlying technical architecture and data governance of the data center , Data intelligence application has become the touchstone to test the strength of China and Taiwan , Check whether the data center can pass the data capability , For example, real-time query capability 、 Batch processing capacity 、 Report presentation ability 、 Data security capabilities 、 Data management ability, etc , Help business personnel complete the intelligent extraction and application of data , Help enterprises grasp the trend of digital transformation and formulate development strategies .

Data Engineer 、 Business personnel can base on the interaction mode of the data center , Unified data processing flow , Realize the self-service processing of data in the middle office , Accelerate the progress of data-driven business . meanwhile , The association analysis of various data and the unification of analysis results provide a more objective analysis dimension for enterprises in the application of data intelligence .

The planning and design concept of data center

How to judge whether a platform is a data center ？
What kind of capabilities should the data center have ？
By looking for the answers to these two questions , Explore the design concept of middle platform architecture together . And in my opinion , To provide users with continuous business product innovation as the construction goal , The ability to convert various resources such as back-end management system into front-end services for continuous reuse , This is the meaning of the existence of the data center . to turn to 2B Business 、 Internet giants that provide technology export and industrial transformation solutions , Immersed in the tradition of information technology for many years IT manufacturer , Or a technology-based start-up company that continues to cultivate enterprise digital services , When developing digital transformation solutions, we need to think deeply about these two problems .

01 Sort out the basic business relationship , Provide overall thinking for the construction of China and Taiwan

When building a data center, enterprises need to consider their own business characteristics and data volume . Before building the data center , Enterprises need to sort out their internal business relations first , Determine the construction direction .

for example , The data department and business department need to cooperate , Sort out business types 、 Business domain boundary 、 Basic services required by various business areas , And the connection standards between business areas , Formulate or improve unified business capability standards 、 Operation mechanism 、 Business analysis method 、 Business execution framework and team organization structure to provide operational services .

The business panorama formed after combing the basic business relations can help the middle office architecture builders and front-end business personnel better understand the business standards 、 Business needs . The business panorama can not only guide the data Department to build a data center , It also provides implementation standards and control standards for building the data middle office architecture .

02 Pay attention to ability precipitation and maintain ductility

Construction of data center architecture 、 perfect 、 The application must focus on precipitation data capability , Zhongtai construction must be malleable , Provide more data support for future business development and new product research and development , So that enterprises can run continuously and quickly . However, the precipitation of enterprise data capability is not achieved overnight , We must go through from local optimization to global optimization 、 The process of gradual improvement in application .

Industry consumption attributes are different , The business focus of enterprises will also be different . For example, high inventory 、 The operation of high consumption clothing industry focuses on the supply chain . Under the operation mode of traditional garment enterprises , The data of front-line marketing is not updated in real time , Unable to provide timely data support for the supply chain . therefore , Integrate supply chain data , Achieve real-time update with marketing data , Become the first priority for the digital transformation of the garment industry . After completing the data update of supply chain and marketing , The marketing department of garment enterprises 、 Operations 、 Management departments and other non core business departments can gradually carry out digital transformation , Finally complete the overall change .

Other enterprises can also carry out digital transformation according to their business priorities , Start with the local , Build an appropriate 、 Scalable data center , So as to meet the data requirements arising from the extension of local business to comprehensive business in the future .

Despite the combing of early business relations and the standardization of digital strategy implementation standards , But whether the middle office architecture meets the final application needs of the enterprise , How much value can it contribute to the front-end business , It still needs to be evaluated in the business application process .

02

Data organization capacity building

Sustainable development is the goal of every enterprise participating in market competition , But when the enterprise develops to a certain scale , There will always be growth bottlenecks due to the limitations of the environment or their own conditions . Of course , This does not mean that the enterprise will never recover , Just solve the problem of inhibiting growth 、 Avoid performance decline 、 Tap new core competitiveness and development power , Enterprises can still achieve sustained growth again .

In the digital economy , New digital technology will become the main driving force for enterprises to enhance sustainable competitive advantage . Digital transformation has become a favorable starting point for enterprises to seek business breakthrough in the digital era . Whether the enterprise has the ability of data organization , Is an important consideration for the success of its digital transformation .

In the traditional management concept , The standard of enterprise success is to have correct strategic policy and excellent organizational ability . Organizational ability refers to the ability of a team to exert its overall combat effectiveness , Able to significantly surpass competitors in some aspects 、 Create higher value . Today, with the digital wave sweeping all industries , The key factor of enterprise success is no longer the organizational ability that is difficult to imitate , But the ability of data organization to freely control data management and application .

Enterprises in the process of digital transformation , It needs to be clear that the extraction process of data value is not a technical problem , But a thinking mode of data application , It's an organizational ability . From the management to the front-line team, we should think about where the data needed by the enterprise is 、 How to get the data 、 How data should be used . Solve this 3 The first problem is the exploration process for enterprises to give full play to the value of data . This process requires the coordination and linkage of multiple departments within the enterprise , Play their respective roles .

In the process of digital transformation , Enterprises need to do the following ： Enabling technological innovation 、 Business guidance , Handle the relationship between internal and external data , Make the underlying data architecture richer ; Establish a business unit 、 Technology Department 、 Data aggregation and dynamic correlation between market operation departments ; Build data capacity and data services between departments at the data level and business level ; In the case of uneven industry standards , Establish standardization 、 Unified data standards , Improve data quality .

The data organization ability of enterprises is embodied in the following aspects .

01 Enterprise's own data problems and status

Enterprises need to clearly understand the magnitude of their own data , Know the value of data and data application rate , Whether these data can form data assets conducive to enterprise development , Evaluate whether it is worth mining through digital technology . therefore , Enterprises need to be clear about data storage , Use organizational ability to precipitate it 、 Dig and use .

02 Connection and application capability of external data

Some involve changes in consumption scenarios 、 The application of dynamic data such as industry development trend analysis needs to be completed with the help of external data . therefore , Connect and get through external data 、 Realize internal and external data sharing , It is also a necessary organizational ability for enterprises in the process of development .

03 The ability to integrate data with business scenarios

There are a variety of data acquisition channels and application directions , for example C End consumption data can be obtained from various consumption scenarios ,B The end production data can be obtained from the information management system of workshop operation , And applied to business departments and management and operation departments .

Some data are important for improving internal production efficiency 、 Cost reduction helps a lot , Some data can help product development 、 The expansion of our business , Some data can be used to mine the value of customer cooperation , Some data can empower the marketing department , Even some data can complete the integration of upstream and downstream industrial chains , For mergers and acquisitions 、 Integrate 、 Provide reference and suggestions for investment . To give full play to the value of data, we need to think from the front-end application , First, think about what kind of data organization ability the enterprise should match , Then allocate resources 、 Equipped technology 、 Convergence capability , Including capital introduction 、 Brand building 、 personnel training 、 Technology introduction , So as to help enterprises further promote digital transformation .

03

Comparison of data construction methods

With the coming of big data Era , The integrated data construction method is no longer fully qualified for the data processing task of the big data industry , This provides growth opportunities for the innovation of domestic data construction methods . The emergence of data center conforms to the development of domestic digital technology and changes in the market environment .

Traditional integrated data construction

Now take a company as an example to review the traditional data construction methods . The company has existed for more than ten years , Unresolved data analysis needs , So I bought BI Tools ; later , The data volume of the company is increasing , And purchased big data platform tools ; later , The data is getting more and more complex , Governance is becoming more and more difficult , Then it is equipped with data management tools ; after , With the increasing requirements of data synchronization , The enterprise has purchased data synchronization tools . As time goes on , The company buys more and more data tools , These data tools have a single function , Unable to meet the changing application needs of business departments .

This is due to the fact that enterprises purchase information management systems , The products on the market are all single function products , Cannot provide a unified 、 Architecturable 、 Scalable information management system .

Although the integrated data construction method can solve some aspects of data management problems for enterprises , However, because the information management system of enterprise procurement belongs to different manufacturers , Different models , The definitions and solutions of the same business in the system are different , So each system can only solve its own problems , Data in the system cannot flow freely , Unable to connect by itself . For example, database 、ETL Tools 、 Data mining tools 、 Data analysis tools, etc , Both are traditional means for enterprises to manage information , But they come from different manufacturers , There are different models , It can only solve data storage alone 、 Data loading 、 data mining 、 Data analysis and other issues .

And such as , A bank has good technical strength , Large investment in information management , In business data 、 Operation data and other data application chain , It is equipped with at least seven or eight information management software . For banks , The biggest difficulty is that different products are used on different chains , The data standards between systems are inconsistent , Data islands are serious , And lack of customized data products , Finally, the direction deviation of data application , For example, data governance is perfect and correct , Data model construction is correct , But it is impossible to determine whether there is a problem with data synchronization or whether the underlying data is not cleaned . Because this integrated data construction method lacks a comprehensive record of data behavior , Data error cannot be traced , No one is responsible for the failure of the project , Therefore, enterprises have low satisfaction with information products .

in addition , Products imported from foreign information system software manufacturers generally have a high degree of information construction , Information segmentation products are perfect , But each company only focuses on the functional planning and design of its own products , It is not responsible for the overall application of data . such as ,ODS The sales company of the system only focuses on the optimization of its own products and service improvement , Software manufacturers selling data warehouses also don't care whether their products can be seamlessly connected with other information systems . Software manufacturers do not provide products from the perspective of data application , This leads domestic companies to encounter weak data connectivity after configuring foreign software systems 、 Data errors occur frequently 、 Low value of data application .

Desktop data construction mode in new data

Online shopping platform of an e-commerce giant 、 Many business systems such as payment platforms are served by databases . But as the “ double 11” The holding of phenomenal consumption activities , The geometric transaction volume puts forward higher requirements for the memory of the database , This means procurement expenditure of hundreds of millions of Yuan . therefore , This e-commerce giant incarnate technology R & D company, whose main market growth mode is business expansion and demand satisfaction , Start the road of independent research and development of databases . In the process , The value of platform architecture in data can be mined .

On the whole , The data complexity in various industries in China is very high 、 Data application space is very large , This also determines that it is no longer feasible to configure foreign information software systems .

In the digital age , As a powerful platform for enterprise digital transformation , It has changed the traditional way of data integration construction , It meets the needs of enterprise massive data value mining . For businesses , The primary value of the construction of data platform architecture is to trace the source when the data is wrong , Business Report 、 The data dictionary 、 Operation reports can be tracked through the middle office system 、 analysis 、 correct . This not only provides a clean data base for the data application of business units , It also frees technicians from dealing with simple tasks first .

04

How to build a data center

Data center is the business model from IT Time entry DT The inevitable product of the times , It is the inevitable result of changing from process driven to data driven . Data center oriented , Rely on data to prove or judge decisions , Form data service thinking , Finally realize the digital transformation of enterprises .

The data middle platform construction mode subverts the traditional data architecture construction mode , Starting from data information , Pay attention to the combination with the specific situation of the business department , Rational use of resources , Improve service efficiency .

Traditional data architecture construction ideas —“ Construction and treatment ”

The traditional data architecture construction mode does not pay attention to the combination with the specific situation of the business department , Just follow the data “ Construction and treatment ” The idea of — First build the data architecture , Then manage the data , Finally, consider the specific application of data . such as , Enterprises will start from IaaS（ Infrastructure as a service ） To different layers PaaS（ Platform as a service ） layer , To DaaS（ Data as a service ） layer , Until then SaaS（ Software as a service ） Floor, etc . It is inevitable that some enterprises will go in the wrong direction in the process of traditional data architecture construction . Some companies will first use cloud technology to move data to the cloud , Get the data through , Then manage the data , Make reports , Then develop various applications . This construction idea takes a long time , Enterprises may stop building because they can't see the value of the business for a long time .

Enterprises need a more agile way to build data architecture , Use the effect to test the scientificity of the construction method , That is, from the perspective of data application , Think about how to manage data .

New data platform construction ideas —“ Use governance construction ”

The new data platform construction mode is to sort out the data application direction , Promote data governance , Finally, build a complete data middle platform architecture , In order to quickly respond to the changing business needs of enterprises . The following figure shows the comparison between the construction ideas of the new digital platform architecture and the traditional data architecture , It shows the principle of data architecture construction .

Enterprises can plan the construction idea of data platform architecture from the following three points .

01 Sort out the strategic map 、 Business map 、 Application map

Some companies are building a data center , Unable to use data resources to mine the part that can generate revenue for the business , Can not achieve the expected effect of architecture construction . therefore , When an enterprise builds a data center , Relevant personnel need to sort out the data application , Solve all kinds of problems in the business department , So as to reduce the cost 、 Efficiency 、 The purpose of income generation . meanwhile , The enterprise digital team needs to build a strategic map according to the enterprise development plan , Build business map and application map according to business development direction and dimension , And clearly manage the data through the application map , Manage the entire data system .

02 To apply the map to deduce the data map , Determine the data governance route

After the enterprise has sorted out the application map , When allocating personnel and capital into development , Given the limited resources and manpower , You can first manage based on some data sorted out by the application map , To build a data map . In the process of enterprise digital transformation , It is often the enterprise leadership that decides the allocation of resources and the allocation of funds , And they often ignore the role of data analysis when making decisions . therefore , Enterprise CDO Need to communicate with the leadership , Determine the personnel allocation and resource supply of the data governance team , So as to successfully determine the data governance route .

CDO You can email 、 Transmit the determined data management route to the lower level by means of video conference or brainstorming , Make technicians and business personnel familiar with the contents and requirements of data governance , Improve the utilization value of data 、 Expand the impact of data .

03 Promote the construction of new data middle platform architecture with data application

Some companies are in the process of building a data center , Worried that the data center will cause new “ The chimney ”. Therefore, the construction of new data platform architecture should meet the requirements of openness 、 Extensibility 、 Long term characteristics . Based on the open data center architecture , Technical functions and application lists can be added or deleted with the development of business . This new data center architecture , It avoids the situation that the underlying data flow and application are affected by the continuous change of architecture to meet the needs of the front-end business department in the application process , High flexibility and scalability , It can help enterprises carry out data governance and application at any time , Truly realize digital transformation .

so ,“ Construction and treatment ” The traditional data architecture construction idea of has been unable to meet the needs of users , and “ Use governance construction ” The new data platform construction idea will be widely adopted by all kinds of digital transformation enterprises as the mainstream data architecture construction idea in the future .

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