银行最早于20世纪60年代使用大型机；许多仍然在用最初的应用程序因为转移出数据是有风险的。
Banks were the first to use mainframes in the 1960s; many are still using the original applications because it is risky to swap them out.
如果您的回答是常见，则面临着极高的失效数据异常风险，那么这个策略对于您的应用程序探查来说是一个很差的选择。
If your answer is that it is common, you run a greater risk of stale data exceptions, making this strategy a poor choice for your application profile.
接受用户输入或来自不受信任来源的任何其他数据是PHP开发人员在开发应用程序时可能承担的最常见风险之一。
Accepting user input or any other data from an untrusted source is one of the most common risks a PHP developer can take when developing applications.
近来的宕机和安全漏洞显示，将公司的所有或部分运营转向云端——大规模远距离存储数据集及应用之简称——并非没有风险。
Putting all or part of a company's operations on the cloud — shorthand for large, remotely hosted data sets and applications — isn't without risk, as recent outages and security lapses have shown.
数据保护包括降低僵尸网络(botnet)使用PaaS作为命令和控制中心直接安装恶意应用程序的风险。
Data protection includes risk mitigation of the PaaS as command and control centers to direct operations of a botnet for use in installing malware applications.
许多仍然在用最初的应用程序因为转移出数据是有风险的。
many are still using the original applications because it is risky to swap them out.
数据挖掘技术在银行领域可应用的范围非常广泛，如客户关系管理、风险分析与控制、资金匹配、金融产品的赢利分析等等。
The application domains of data mining in bank industry are wide, including client relationship management, risk analysis and profit analysis of financial products.
实际上，如果你不考虑对其它IT功能影响地应用数据加密，实际上增加了企业其它区域的风险。
In fact, if you apply data encryption without consideration for how it will affect other it functions, it can actually increase risks in other areas of the enterprise.
一种新的抽样方法是把数据挖掘技术中的分类、聚类及离群点挖掘等应用到审计风险管理中去。
A new sampling method is proposed, which USES the latest technologies of database. It applies classification rule mining, clustering rule and outlier mining to the management of Audit Risk.
数据挖掘技术在银行领域的应用有四个方面：银行客户关系管理、银行风险管理、银行信用等级评估、银行服务分析和预测。
The application of DM technique to banking consists of four components: customer relationship management, risk management, credit grade evaluation, and service analysis and forecasting.
数据加密用处不大，除非你把它应用于特定减轻风险或定位法律要件。
Data encryption is of little use unless you apply it to specifically mitigate a risk or to address a legal requirement.
并将CRM中关于客户关系的理念应用到数据仓库中，提出了如交叉销售、风险客户、客户流失等数据模型。
Furthermore, the concept of customer relationship in CRM is applied into data warehouse, and build the models of overlapped sales, risking customer and customer losing.
在改进研究的基础上建立了我国商业银行信贷风险评估体系，并选取了3家上市公司的2004年度数据对模型进行了应用分析。
Establishing our commercial bank credit risk evaluation system model and applies the model with 3 listed company's date of 2004.
我国金融市场由于缺乏足够的信用数据，直接利用股票市场数据来进行信用风险管理的KMV模型有着广泛的应用前景。
Considering the lack of credit date of financial market in China, KMV model, which can directly use data from stock market to measure credit risk, has extensive application.
如今，许多最著名的风险投资家和创业者都致力于向农场提供最新的计算机技术——数据分析、云计算、移动应用。
Some of the most well known venture capitalists and entrepreneurs are now focused on bringing the latest computing technologies — data analytics, cloud computing, mobile apps — to farms.
本文应用KMV公司信用风险管理的基本理念，利用我国1981 ~ 2002年国债债务的相关数据，对国债的信用风险进行了研究。
We did the study according to the basic models of credit risk management in KMV co. Ltd, and the relevant data of national bond from 1981 to 2002 in China.
这些密集的数据集是通过把散弹射击的方法应用在小规模病人而得到的。，但它带来一个有显著风险度的过于合适模型，导致假联系。
The very dense data sets that result from shotgun approaches on small numbers of patients carry a significant risk of model overfitting, leading to spurious associations.
同时，针对风险评估中的某些重要问题给出了应用数据包络分析方法研究的具体建议。
In addition, some Suggestions about by using data envelopment analysis method to research them are suggested.
一种新的抽样方法是把数据挖掘技术中的分类、聚类及离群点挖掘等应用到审计风险管理中去。
It applies classification rule mining, clustering rule and outlier mining to the management of Audit Risk.
利用上市公司披露的信息数据库为平台，将神经网络方法应用于财务风险识别。
In this paper we apply neural network prediction method to financial risk detection on the basic of the database of listed companies' released information.
应用贝叶斯方法研究了火工品买卖方风险问题，在先验分布和历史数据下，给出了买卖方风险的计算公式。
This paper discusses the risk research of pyrotechnics for the buyer and seller with the Bayes method. Under the historical data and prior distribution, the formulation of risk is obtained.
由于网络上的数据包括信用卡、银行账户以及其他有价值的个人身份相关信息，风险是很高的，但是成为一个受信任的应用发布者将会得到很多回报。
With data on the line that can include credit card, banking and valuable personally identifiable information, the stakes are high, but the reward for trusted app publishers is significant.
由于网络上的数据包括信用卡、银行账户以及其他有价值的个人身份相关信息，风险是很高的，但是成为一个受信任的应用发布者将会得到很多回报。
With data on the line that can include credit card, banking and valuable personally identifiable information, the stakes are high, but the reward for trusted app publishers is significant.
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