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❶ Based on java jsp asp php vb Android system graduation project and implementation paper source code download

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❷ How about the digital transformation of finance

The black swan of the "COVID-19 epidemic" is becoming a touchstone to test the digital capabilities of enterprises. Through a mobile phone, a computer, and a screen, during this extremely long holiday, a few companies with digital capabilities not only kept their operations running in an orderly manner, but even relied on their agile response capabilities to explore ways to turn crises into opportunities. For example, Anta Group, which has been on the road to digital transformation in recent years, relied on front-end and back-end digital platforms to launch a new sales model of "all-staff shopping guides" and easily achieved daily sales exceeding 10 million. However, due to the lack of digital foundation, more companies are helpless in the face of repeated delays in resuming offline work, and can only passively bear the impact of the epidemic.

Before the epidemic, digital transformation was just a slogan and an idea for many companies. So, after this epidemic, companies mustwill accelerate on the road to digital transformation. But how should we take the road to digitalization? It is still a difficult problem for many companies.

Financial digitization is the entry point for enterprise digitization

Digitalization is the use of digital technology to holographically reconstruct the colorful real world in the computer virtual world. When it comes to enterprise operations and management, enterprise digitalization means simulating the entire process of actual enterprise operations in the computer world, and feeding data back to the real world to guide future decisions and behaviors and promote business growth. In this way, digitalization not only means digitizing the company's front-end sales and logistics, but more importantly, matching the company's back-end finance, procurement, and internal resource allocation with the new front-end business model. In this process, financial digitalization can be said to be the best entry point for enterprises to achieve comprehensive digitalization.

Looking back at the historical process of enterprise informatization and digitalization, finance plays an important role in every enterprise transformation process. Whether it is the computerization of accounting or the ERP popularization movement, finance is the engine that promotes the comprehensive transformation of enterprises and is an important starting point for enterprise optimization and upgrading. On the one hand, this is because the financial system is connected to corporate executives at the top and every employee at the bottom; it is connected to procurement and operations on the left, and marketing and services on the right; it is connected to accounting reports in the front, and analysis and decision-making in the back. The financial system itself has the characteristics and three-dimensional data structure to connect various departments and management processes, which are its natural advantages in leading enterprises to carry out comprehensive digital transformation at all levels. On the other hand, financial management is the lifeline of corporate management. Almost all corporate management levels and competitiveness are reflected in finance. The financial system holds a large amount of core data of the enterprise, and these data serve as important indicators and decision-making basis for measuring and judging the operating performance of the enterprise, and are an important basis for the enterprise to realize informatization and digitalization.

Therefore, although digital transformation technology continues to subvert traditional enterprises, financial management as the core cannot be changed. The financial system bears the important responsibility of leading enterprises to fully move toward digitalization. If an enterprise wants to realize digital transformation, the first step is to realize financial digitization.

The implementation strategy of financial digitization

Financial digitization has two meanings: one is the comprehensive application of digital technology represented by "big wisdom moves cloud things" and blockchain; the other is the The financial model, including organization, process and work model, will undergo all-round changes so that the financial system can better support the business development of the enterprise. The Internet business model is a capital economy dominated by the consumer side and centered on the model. Nowadays, many companies have applied new ideas of online and offline integration on the business side. However, the financial support system still adopts the traditional model that is separated from transactions, with post-account reporting as the main line, and risk management and control as the goal. The process is complex and inefficient. Obviously, It can no longer meet the management requirements for quick response from the front end and must be reshaped.

We believe that enterprises should adopt the following two strategies to guide financial model changes and promote the process of financial digitalization:

Connect the entire process

The core of digitalization is connection, that is, the use of new generation information technology to realize the connection between various departments within the enterprise, the connection between the enterprise and users, the connection between the enterprise and upstream and downstream suppliers, and even the connection between the enterprise and the entire society in the future. Specific to the field of financial digitization, it is necessary to completely connect financial processes with business processes and management processes to realize the "Internetization" of the entire process. Based on the Internet, we should open up internal and external connections, reconstruct financial processes, and make back-end financial and Front-end transactions can be performed simultaneously online.

Under the traditional financial model, financial processes and transactions are separated, resulting in a large number of redundant process links. Taking cost control as an example, many companies have designed many control processes in order to achieve process control. For example, companies often need to set up pre-budget application and budget approval processes to ensure the correct use of budgets. When a transaction occurs, whether it is business personnel, approval leaders or financial personnel, everyone must repeat a lot of post-event work, resulting in inefficient and inefficient management. High cost. At the same time, in the traditional financial system, financial accounting confirms profits and losses according to the requirements of the accrual basis, and accounts are recorded based on invoices. Business occurrence and business accounting are separated. Financial processing lags behind business activities in time, causing the information provided by financial accounting to be historical. , lack of foresight. At the same time, financial accounting regularly produces and delivers information based on the requirements of accounting period assumptions. In full market competition, there is a huge contradiction between the fixed time of financial accounting information transmission and the timeliness of decision-making. The superposition of these two factors makes traditional financial information lag behind and unable to meet the needs of users for real-time decision-making.

To fundamentally solve the above problems, enterprises first need to connect finance and transactions, reconstruct financial processes and eliminate a large number of redundant links by connecting financial processes, business processes and management processes. Secondly, all financial processes, business processes and management processes must be Internetized, so that all transactions on the business end can occur online, so that all businesses on the financial end can be processed in real time based on online transactions, thereby realizing the transformation of post-event accounting and reimbursement into when the business occurs. Accounting and reporting, transforming manual accounting processing into online automatic real-time processing.

Connect all data

The foundation of digitalization is data. To achieve financial digitization, it is necessary to open up the real-time flow and sharing of data in all directions, processes, and fields, and to achieve the true integration of information technology and financial management.

In essence, traditional finance is standards-oriented and disclosure-oriented, not business-oriented or management-oriented. ERP systems mainly serve process operations, which brings two problems: First, financial information is objective but not necessarily true. . Financial accounting is based on the content of invoices, but invoices cannot reflect the essence of the business. Financial data is divorced from business essence. All these lead to the distortion of ERP financial information and the inability to meet management needs. Second, the financial information is a single monetary measurement information, rather than a comprehensive and comprehensive economic information of the enterprise. Although monetary measurement information is comprehensive to a certain extent, non-monetary information is often crucial to management. These problems in the financial information support system make financial information one-sided, distortion, difficult to meet the needs of business management.

At the same time, traditional enterprise information systems are composed of a series of independent professional packaged software systems. These systems are independent of each other, forming a chimney-like architecture, resulting in a large number of information islands. A large amount of financial data and business data are repeatedly and messily scattered in various enterprise information system platforms, making data collection and data conversion difficult.

To this end, enterprises must break through data barriers, change the path to obtain basic data, and promote data flow. On the one hand, it is necessary to open up business and financial data and eliminate information islands; on the other hand, it is necessary to make management accounting no longer rely solely on financial accounting to provide information, but to be able to automatically collect and collect data directly from the transaction side and from different business systems in real time. Process, enrich data sources, improve data quality, develop data insights, and ultimately enable data to empower business development.

The path to realizing financial digitization

The path to realizing financial digitization is the path to building a digital platform. Whether it is the connection of processes, online processing of business, or the connection, acquisition, transmission of data, or the development of data insights, they all need to be based on modern information technology and can be implemented in automated, Internet-based, and intelligent information systems. Building a financial digital platform requires long-term planning and gradual advancement by enterprises. The construction content includes three parts: intelligent sharing system, data middle platform and data application system.

1. Use the intelligent sharing system as a bridge to connect front-end transactions and back-end finance, and realize internal and external communication.

In the process of building a financial digital system, the financial sharing platform is the vanguard. The process of implementing digitalization in the system must be done through two lines: external and internal. All transaction processes are recorded externally, all business lines are opened internally, and the entire business is connected through a unified system to open up internal and external connections and interconnection. This system is the industry finance and taxation intelligent sharing system.

The core of the Sharing Center is sharing, and the premise of sharing is "connection". This means that the sharing center can become a natural technology platform that connects the entire process of business, finance, and management, and promotes the integration of industry and finance. The industry finance and taxation intelligent sharing system is a revolutionary replacement of traditional financial sharing in the Internet+ era. Its essence is based on the new generation of information technology to realize the digitization of the company's wider business (from accounting, accounting to accounting, procurement, taxation, etc.), and to subvert and upgrade the company's financial system, business processes, and business models. By building an intelligent sharing center that integrates industry, finance and taxation, the enterprise has formed a business transaction layer between the backend and the frontend, a more flexible and powerful business support center, which can connect a large number of transaction processing and services between the frontend and the backend, and realize the needs of the enterprise. The digitization of a wider range of businesses (from accounting and accounting to reporting, procurement, taxation, etc.) has greatly improved operational efficiency, quickly responded to customer needs, and achieved deep integration of finance, business and taxation.

The Anta Group mentioned at the beginning of this article is a beneficiary of the industry’s financial and taxation intelligent sharing system. In 2018, Anta joined hands with Yuannian Technology to launch a financial joint ventureThe construction of a sharing center will create an automated, intelligent and digital sharing system under the "supply chain + wholesale + retail" business model of the sporting goods industry, so that sharing can drive the group's internal system transformation and support the rapid development of the group's business. The efficient implementation of Anta's "all-employee marketing" during this epidemic is inseparable from the agile response of its shared system to front-end transactions.

2. Use the data center as a platform to connect all data and realize centralized data governance and data management.

To achieve financial digitization, it is necessary to reconstruct the enterprise IT system architecture, and the core of reconstructing the enterprise IT system architecture lies in the "centralization" of the enterprise IT system.

Data center has received unprecedented attention since 2019. At a previous forum held by Yuannian Technology, more than 80% of companies stated that they were already building or planning to build a data center. The outbreak of the epidemic will inevitably further increase the demand for data governance and data middle platform construction among enterprises.

The data middle platform breaks the traditional chimney information architecture of the enterprise by building a layer of middle platform between the enterprise's business front desk and management backend, and deploys various information systems based on the same platform. A series of front-end application systems. Based on the data middle platform, enterprises can open up and aggregate multi-source data, realize data assetization and integration of internal and external data, share and reuse it to front-end application systems, and realize specific data applications. Based on the in-depth exploration and application of the new generation of information technology, the data center will not only completely solve the problem of enterprises' information islands, improve the efficiency and quality of data collection and data conversion, but also eradicate the phenomenon of duplication of enterprise IT system construction and provide data storage and data management convenience.

Data governance is the only way to realize the capitalization of data, and it is also one of the highly regarded values ​​of the data center. Data governance is a long-term development and optimization process. It improves the quality of all types of data, including structured and unstructured data, through master data, metadata, data quality management, etc., and transforms a large amount of messy data hidden in the data tomb. It is a clear, organized, and contextual data asset. It should be emphasized that in terms of specific applications, data governance in the big data era should build governance capabilities at each stage from data production to application for the entire life cycle of data.

3. Use management accounting and data analysis systems as the main position for developing data applications and realizing data empowerment.

The ultimate goal of financial digitalization is to use data to empower enterprise business development. It can be said that all the work we do to achieve digitalization is to achieve the final data application.

The front-end application system of data is the last piece of the jigsaw puzzle of the enterprise digital platform, and it is also a key part of the closed loop of enterprise data flow. Currently, the rapid development of intelligent technology and big data technology has provided huge help for data applications. The major management accounting systems built based on these new generation information technologies include budget management, cost management, performance management, management accounting reporting and other systems, as well as various data analysis systems.Systems, including scenario analysis, financial analysis, business analysis and other systems, can carry out business applications based on the data sets and data models of the data center, and are the main position of data applications.

For financial personnel, data applications can help perceive the present and predict the future. Perceiving the present: merging historical data with current data, mining potential clues and patterns, and perceiving the development status of events; predicting the future: correlation analysis of full data, streaming data, and offline data, determining and regulating situations and effects, and starting from the perspective of data Explain the development and evolution rules of events from different angles, and then predict the development trend. To give an example: Based on the accumulation and analysis of massive historical data, companies can build more complete forecast models based on application scenarios, such as project input-output forecasts.

Take this epidemic as an example. For most companies, the issue that management is most concerned about is what impact the epidemic will have on corporate performance, what measures companies can take to deal with it, etc. Enterprises that have built management accounting or data analysis systems can easily conduct accurate data analysis from these large amounts of real-time changing data to provide management with timely and effective decision-making basis.

At the beginning of this new decade, an epidemic sweeping the world has announced to us that the next ten years will be strange and changeable. There is a high probability that the unstable, uncertain, complex and ambiguous market environment will be with us for a long time. And digitalization is the certain future we glimpse in this fog. Starting digital transformation immediately starting with the financial system is a strategic move for enterprises to improve their "anti-fragile" capabilities!

❸ How to learn Python

Share the Python learning route: The first stage: Python basics and Linux database

This is the introductory stage of Python, and it is also important to help zero-base students lay a solid foundation. stage. You need to master Python's basic syntax rules and variables, logic control, built-in data structures, file operations, advanced functions, modules, commonly used standard library templates, functions, exception handling, mysql usage, coroutines and other knowledge points.

Learning goals: Master the basic syntax of Python, have basic programming skills; master basic Linux operating commands, master the advanced content of MySQL, complete bank ATM system practice, English-Chinese dictionary, lyrics parser, etc. project.

The second stage: web full stack

This part mainly learns web front-end related technologies. You need to master html, cssJavaScript, JQuery, Bootstrap, web development basics, Vue, FIask Views, FIask templates, database operations, FIask Configuration knowledge.

Learning objectives: Master the technical content of web front-end, master the web back-end framework, be proficient in using FIask, Tornado, and Django, and be able to complete data monitoring back-end projects.

The third stage: data analysis + peopleArtificial Intelligence

This part is mainly about learning knowledge points related to crawlers. You need to master data crawling, data extraction, data storage, crawler concurrency, dynamic web crawling, scrapy framework, distributed crawlers, crawler attack and defense, data structure, Algorithms and other knowledge.

Learning objectives: Be able to master crawlers, data collection, data organization and algorithm advancement, and artificial intelligence technology. It can complete phased projects such as crawler attack and defense, image mosaic, movie recommendation system, earthquake prediction, and artificial intelligence projects.

Stage 4: Advanced Advancement

This is an advanced knowledge point of Python. You need to learn the project development process, deployment, high concurrency, performance tuning, Go language basics, introduction to blockchain, etc.

Learning objectives: Can master automated operation and maintenance and blockchain development technology, and can complete automated operation and maintenance projects, blockchain and other projects.

After learning according to the above Python learning roadmap, you can basically become a qualified Python development engineer. Of course, if you want to quickly become an elite talent recruited by companies, you need to have good teachers to guide you, and you also need to accumulate practical experience in more projects.

For those who are interested in Python development, you might as well start by reading the Python development tutorial! There are a lot of Python teaching videos on site B, ranging from basic to advanced. They are quite good. The knowledge points are explained in detail, and there is also a complete learning road map. You can also check it out for yourself, download it and try it out.

❹ What preparations are needed to learn Python

The following is the learning route of the Python full-stack development course. You can study in a planned manner according to this course outline:
Phase 1 ：Python development basics
Python full-stack development and artificial intelligence basic knowledge of Python development. Learning content includes: Python basic syntax, data types, character encoding, file operations, functions, decorators, iterators, built-in methods, and common modules. wait.
Phase 2: Python advanced programming and database development
Python full-stack development and artificial intelligence Python advanced programming and database development knowledge learning content includes: object-oriented development, Socket network programming, threads, processes, queues, IO multi-channel model, Mysql database development, etc.
Phase 3: Front-end development
Python full-stack development and artificial intelligence front-end development knowledge learning content includes: Html, CSS, JavaScript development, Jquery&bootstrap development, front-end framework VUE development, etc.
Phase 4: WEB framework development
Python full-stack development and artificial intelligence WEB framework development learning content includes: Django framework basics, Django framework advanced, BBS+Blog practical project development, caching and queue middleware ,Flask framework learning, Tornado framework learning, Restful API, etc.
Phase 5: Crawler Development
Python full-stack development and artificial intelligence crawler development learning content includes: Practical crawler development.
Phase 6: Full-stack project practice
Python full-stack development and artificial intelligence full-stack project practice learning content includes: enterprise application tool learning, CRM customer relationship management system development, Luffy Academy online education platform Development etc.
Stage 7: Data Analysis
Python full-stack development and artificial intelligence data analysis learning content includes: financial quantitative analysis.
Stage 8: Artificial Intelligence
The artificial intelligence learning content of Python full-stack development and artificial intelligence includes: machine learning, data analysis, image recognition, natural language translation, etc.
Stage 9: Automated Operation & Development
Python full-stack development and artificial intelligence automated operation & development learning content includes: CMDB asset management system development, IT audit + host management system development, distributed host Monitoring system development, etc.
Stage 10: High-concurrency language GO development
Python full-stack development and artificial intelligence high-concurrency language GO development learning content includes: GO language basics, data types and file IO operations, functions and object-oriented, and concurrency Programming etc.

❺ Ethereum London upgrade! The master on the Ouke Cloud Chain launched EIP-1559 special data to take the pulse of "ecological fluctuations"

On August 5, the London hard fork of the Ethereum mainnet was upgraded and officially activated at the blockchain height of 12,965,000. Ethereum The EIP-1559 proposal then takes effect.

Since being proposed in March 2019, the EIP-1559 proposal has caused huge controversy in the Ethereum community - opponents believe that this proposal "treats the symptoms but not the root cause", "does little harm and is extremely insulting". Strong", while supporters said the proposal will "optimize user experience" and "reduce the inflation rate of Ethereum." With the London hard fork taking effect, the EIP-1559 proposal is officially written into the DNA of the Ethereum network.

What impact and fluctuations will this proposal bring to ecological users, miners, DeFi, and ecological value feedback? On August 5, Ouke Cloud Chain Master officially launched the EIP-1559 special data. Here, you can be the first to know about the wind direction changes brought about by the London hard fork!

What is the EIP-1559 proposal?

In March 2019, Ethereum founder Vitalik Buterin and Ethhub founder Eric Conner jointly proposed the EIP-1559 proposal, hoping to change the transaction fee mechanism of Ethereum, make the fee market more stable, and ease the network congestion problem.

EIP-15Proposal 59 proposes that in the future fee market, users need to pay a fixed basic fee for each transaction. If they need to speed up transaction confirmation, they can pay tips to the miners. The tips will belong to the miners and all the basic fees will be destroyed. On the special page of Chain Master EIP-1559, we have made a detailed analysis of the details and impact of the proposal. Under the new transaction fee mechanism, the Ethereum ecosystem has ushered in a "transaction reform."

What data is there in the EIP-1559 topic?

Based on the data on the Ethereum full node chain, Ouke Cloud Chain Master launched EIP-1559 special data, covering hard fork countdown, data overview, miner income, transaction fees, tip distribution statistics and other data, showing the data fluctuations before and after the EIP-1559 proposal takes effect, providing data reference for users to judge the development trend of the Ethereum ecosystem.

On the EIP-1559 special page, the first thing you see is the data overview of the Ethereum ecosystem. Basic data such as price trends, latest block highs, current Ethereum supply, Ethereum burn, etc. are all summarized here.

Below the data overview is a series of data indicators made by the masters on the Ouke Cloud Chain for this upgrade.

What impact will the EIP1559 proposal have on miners?

The new transaction fee mechanism has brought the most direct impact to miners, so among the opposition to the EIP-1559 proposal, an important group is the miners.

In the column of miners’ income and transaction fees, the chain master provided a line chart and two bar charts to visually display the impact of the EIP-1599 proposal on miners.

The line chart takes the effective time of the EIP-1559 proposal as the axis, showing the changing trends of miners' income, transaction fees, and ETH prices before and after this major event, and provides two pricing methods: ETH and USDT. Unit, visually showing the impact of the EIP-1559 protocol on these three data.

The bar graph shows the histogram of miner income and transaction fee respectively. The former shows the miner income under the original mode and the block income and handling fee after EIP-1559 takes effect. The latter provides The total handling fee under the original mode and the basic fee and tip data after EIP-1559 takes effect.

Based on this part of the data, miners and ecological users can make rational judgments and market behaviors in advance.

Will ETH experience deflation? Will the ecology get better?

Regarding the EIP-1559 proposal, some people believe that it can reduce gas fees, and by destroying a certain amount of ETH, it can offset the newly issued ETH to a certain extent, thereby bringing about a deflationary effect. Some people believe that gas fees cannot be reduced in the long run, and deflation is difficult to achieve.

In order to verify these judgments, the chain master provides3 charts to show ETH supply and destruction data.

"ETH Supply" shows the difference and changes in the estimated supply and actual circulation in the form of a line chart, which can verify the impact of the EIP-1559 proposal on Ethereum inflation.

"ETH burned amount" shows the changes and correlations between ETH price, gas utilization, basefee, number of transactions and ETH burned amount in the form of a line chart + bar chart. Using this data, we can analyze the correlation between the amount of ETH destroyed and ETH price, number of transactions and other data, and objectively analyze the significance of the EIP-1559 proposal.

In addition to the basic fee, how much tip should be given to miners in the future?

After the EIP-1559 proposal came into effect, tips have become the most frequently used data by users of the ETH ecosystem.

In the "Tip Statistics" column, the chain master provides 3 data charts, which respectively display tip distribution statistics, number of tip transactions and specific data table presentation.

The tip distribution statistics table displays the average tip number and tip data of the last 1,000 blocks in the form of "line chart + box chart"; the number of tip transactions is shown in the form of "stacked column chart (transaction Quantity) + line chart (ETH price)" form, showing the dynamic relationship between the number of tip transactions and the price of ETH in the last 1,000 blocks; and the data table presentation table gives the last N days after EIP-1559 took effect. average data.

Will miners boycott after the London hard fork?

After the EIP-1559 proposal takes effect, the transaction fees paid to miners are expected to decrease. Will this lead to miners surrender or rebellion, and thus affect the stability of the Ethereum ecosystem?

In response to this point, the chain master launched the "on-chain data" line chart, which combines ETH price, network computing power, block size, unit computing power income and other data, and marks the London hard score The timeline of the fork shows the correlation of each data and the changes before and after the hard fork.

By observing this chart, you can intuitively understand the impact of this hard fork on the Ethereum ecosystem.

Summary

With the official launch of the London hard fork of Ethereum, the Ethereum network has ushered in a summer breeze. Ecological participants such as miners, users, and DeFi protocols growing on Ethereum will all be affected.

Is this summer wind fast or slow, good or bad, hot or cool? Before we feel its impact personally, the masters on the Ouke Cloud Chain launched the "EIP-1559 Special Topic" to gain insight into the on-chain data in advance and act as a "wind meter" for this summer storm. It not only brings benefits to ecological participants Many conveniences have further improved the big data infrastructure of the Ethereum ecosystem and opened up the development space and imagination of blockchain big data.

This article comes from the Financial World Network

❻ How to judge the climate based on the temperature and precipitation charts

Step 1. Determine the hemisphere: During the year, the lowest temperature in January is in the northern hemisphere; the lowest temperature in July is in the southern hemisphere.

Step 2: Use temperature to determine the heat zone and narrow the range. (Note that the temperature in the coldest month is used to judge!!!)

If the temperature in the coldest month of the year is ≥15℃, it is one of the four tropical climate types (tropical rainforest climate, tropical Monsoon climate, savanna climate, tropical desert climate)

If the temperature of the coldest month of the year is ≥0℃, it is a Mediterranean climate, a subtropical monsoon climate, or a temperate oceanic climate. There are 3 types in total. (Pay special attention to the fact that although the temperate maritime climate is a temperate zone, the average temperature of the coldest month is greater than 0℃)

If the temperature of the coldest month of the year is ≤0℃, it is a temperate monsoon climate or a temperate continental climate. There are 2 types in total. Other polar climates are generally not tested, so don't worry about it.

Step 3: Look at the precipitation to determine the final climate type. There are four types of precipitation:

Annual rain type (precipitation occurs every month and is relatively uniform), including tropical rainforest Climate, temperate maritime climate. , they were distinguished in the previous step using the temperature of the coldest month.

Summer rain type (summer, with more precipitation during the hottest period), includes tropical monsoon climate, tropical grassland climate, subtropical monsoon climate, and temperate monsoon climate. Here it is only necessary to distinguish between tropical monsoon climate and savannah climate. The months with the most precipitation in the tropical monsoon climate are around 600㎜, while the months with the most precipitation in the savannah climate are between 300㎜~400㎜.

Winter rain type (more precipitation in winter, the coldest time), Mediterranean climate

Dry rain type (less precipitation every month), tropical desert climate, temperate continental climate .

ps: You must strictly follow the steps and do not skip steps, otherwise it is easy to make mistakes!