Decentralized data asset management
Publish: 2021-04-16 05:13:33
1. According to Hou Jietai: the so-called centralization refers to subtracting the mean value of a variable from its expected value. For sample data, each observation value of a variable is subtracted from the sample average value of the variable, and the transformed variable is centralized
for your question, subtract the mean from each measurement.
for your question, subtract the mean from each measurement.
2. Decentralized digital wallet, generally speaking, is a wallet that has no central server, does not need to interact with the central server, and manages (stores, transfers, and accounts receivable) digital currency with private key. The zebra wallet I use is very good. It can be downloaded from the official website. The others are not clear
3. Based on the first large-scale commercial application developed by gxchain, gongxinbao's decentralized data exchange provides enterprises with a completely different solution from the previous centralized data transaction (such as data middleman and data black market). Based on blockchain technology, both sides of data transaction can directly carry out point-to-point data transaction and exchange, and have non buffered data, non buffered data, non buffered data and non buffered data It has the advantages of protecting privacy and data right, preventing counterfeiting and so on.
4.
Decentralized bookkeeping makes blockchain assets open, transparent and unable to cheat ~
the third feature of blockchain assets is decentralized bookkeeping
the transfer you give to others will not be delayed for several days because the bookkeeping institution is on holiday; Not because the bookkeeping institutions want to make profits, so they have to pay high fees; More will not be because of accounting institutions cheating, and suffer losses
because its bookkeeping is carried out by the whole network. The account book that you transfer to others will not be unified because of the loss of the account book data here or there, because the account book is jointly maintained by the whole network, and every node has a backup
5. Because the smart assets use the blockchain technology, and the blockchain technology is decentralized, using distributed accounting and storage, there is no centralized hardware or management organization, the rights and obligations of any node are equal, and the data blocks in the system are jointly maintained by the nodes with maintenance function in the whole system.
6. What are the characteristics of defining data as assets? We can judge by the following three standards: controllable, quantifiable and realizable
for how to help enterprises provide more accurate procts and services with high-quality data, rece costs and control risks through efficient data asset management, so as to enhance the core competitiveness of enterprises, Shenzhen Jitong will take you to understand the asset management of data center
first, data governance: governance without chaos, turning data into assets
the most sad thing for IT departments now is that it departments are not the owners of data, but they come to it departments when data problems arise: it's strange that data is inaccurate, unreliable and unsafe
in fact, data-driven is the core business of an enterprise, so data governance should not only be the responsibility of IT departments. It also needs the wide participation of business departments to provide continuous support for business decision-making, business definition, data quality process, and development priorities for the future state vision of the enterprise through inter departmental communication. The standard discussed together is not necessarily the best, but it is the most effective and appropriate one in the current work practice< Second, data asset management architecture: driving the maturity of enterprise architecture
"data driving everything" is not too much for the development of enterprises in the era of big data. In enterprises, it is not difficult for us to see that ERP, CRM, financial system, technical architecture, operation and maintenance of Data Center... All these resources are managed by special personnel. When data becomes the core asset of an enterprise, who is responsible for it
it should only be responsible for how to do. To change the structure, we should first change from people; The change of enterprises should start with the change of organization. When data becomes the core asset, enterprises should establish a professional data asset management entity or virtual organization with professional responsibility for data architecture and management, constantly improve the data architecture, improve the quality of data planning, design, development and delivery, and manage the IT system construction life cycle from the beginning to the end
Third, data sharing: the foundation of big data
sharing economy has opened a new era, and data sharing is the foundation of big data. All the tools based on the Internet solve the problem of trust. Without trust as the basis, there will be no sharing
first of all, we should solve the problem of data sharing within the enterprise. Before big data, enterprises used ESB, but people graally found that only enterprise bus can't solve the problem. Because the solution of service is to encapsulate complex problems with simple methods, but it seems that the perfect call does not solve the core problem of data
therefore, at the beginning of establishing a big data center, enterprises should avoid simply integrating data without effective management. For small and medium-sized enterprises, the agile way of big data is scenario driven. We must focus on the most fundamental business needs of enterprises, rather than big data for big data. Small and medium-sized enterprises need more flexible, faster and more cost-effective solutions.
for how to help enterprises provide more accurate procts and services with high-quality data, rece costs and control risks through efficient data asset management, so as to enhance the core competitiveness of enterprises, Shenzhen Jitong will take you to understand the asset management of data center
first, data governance: governance without chaos, turning data into assets
the most sad thing for IT departments now is that it departments are not the owners of data, but they come to it departments when data problems arise: it's strange that data is inaccurate, unreliable and unsafe
in fact, data-driven is the core business of an enterprise, so data governance should not only be the responsibility of IT departments. It also needs the wide participation of business departments to provide continuous support for business decision-making, business definition, data quality process, and development priorities for the future state vision of the enterprise through inter departmental communication. The standard discussed together is not necessarily the best, but it is the most effective and appropriate one in the current work practice< Second, data asset management architecture: driving the maturity of enterprise architecture
"data driving everything" is not too much for the development of enterprises in the era of big data. In enterprises, it is not difficult for us to see that ERP, CRM, financial system, technical architecture, operation and maintenance of Data Center... All these resources are managed by special personnel. When data becomes the core asset of an enterprise, who is responsible for it
it should only be responsible for how to do. To change the structure, we should first change from people; The change of enterprises should start with the change of organization. When data becomes the core asset, enterprises should establish a professional data asset management entity or virtual organization with professional responsibility for data architecture and management, constantly improve the data architecture, improve the quality of data planning, design, development and delivery, and manage the IT system construction life cycle from the beginning to the end
Third, data sharing: the foundation of big data
sharing economy has opened a new era, and data sharing is the foundation of big data. All the tools based on the Internet solve the problem of trust. Without trust as the basis, there will be no sharing
first of all, we should solve the problem of data sharing within the enterprise. Before big data, enterprises used ESB, but people graally found that only enterprise bus can't solve the problem. Because the solution of service is to encapsulate complex problems with simple methods, but it seems that the perfect call does not solve the core problem of data
therefore, at the beginning of establishing a big data center, enterprises should avoid simply integrating data without effective management. For small and medium-sized enterprises, the agile way of big data is scenario driven. We must focus on the most fundamental business needs of enterprises, rather than big data for big data. Small and medium-sized enterprises need more flexible, faster and more cost-effective solutions.
7. According to the current practice, the method of data asset management should include the following three steps: the first step is to do a good job in data governance and drive the maturity of enterprise architecture governance by data architecture; The second step is to build an enterprise level data sharing center to realize the loose coupling of data collection, sharing and application, and realize the rapid data modeling, analysis, sharing and application and visual management through the data sharing layer; The third step is to open up data through cross-border cooperation to realize the growth of main business driven by data asset strategy.
8. At present, most of the data center asset management methods mainly rely on manual input of information, and the management tools are relatively simple. With the increase of the scale of the data center, the number of equipment to be managed also increases. The traditional data center asset management methods can no longer meet the needs of business development, We now use the data center infrastructure management equipment and data center asset management equipment of Shenzhen Jitong intelligent company, which not only ensure the accuracy of data,
9. Today's data centers are different in size, density and complexity. There are thousands of assets in the data center. At the same time, the infrastructure is large and discrete; Large scale equipment and equipment change frequently, management cost, maintenance cost and labor cost increase; Repeated waste of investment, equipment failure, unknown loss of assets and other issues. Therefore, effective tracking of data center assets is a continuous and heavy workload task. If traditional means are still adopted, it is difficult to meet the increasingly complex requirements of data center room management. And the use of scientific asset management system, can effectively solve the above problems, so that managers of the data center assets at a glance. Let managers clearly understand: the accurate information of the whole data center room assets, equipment line connection and association relationship; Clearly grasp the quantity / location / status of IT assets to ensure manageability, integrity and traceability; The utilization of equipment, cabinet and other resources, rece excessive configuration or rendancy, and maximize the use of limited resources; Accurate, real-time understanding of IT asset inventory and location, data center status at a glance, efficient management.
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