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Last updated : Mar 16, 2012
不在本期内容中
这一条目不在当前版本的技术雷达中。如果它出现在最近几期中,那么它很有可能仍然具有相关参考价值。如果这一条目出现在更早的雷达中,那么它很有可能已经不再具有相关性,我们的评估将不再适用于当下。很遗憾我们没有足够的带宽来持续评估以往的雷达内容。 了解更多
Mar 2012
采纳 ? 我们强烈建议业界采用这些技术,我们将会在任何合适的项目中使用它们。
If the rate at which business is changing is an indicator of change in requirements, then the days of doing upfront database design are gone. Instead, projects should follow evolutionary database techniques and continue to change their database schemas as new requirements are implemented over the course of the project. Deployment of database changes should also be automated so that the application release that relies on those changes does not have to wait for manual deployment of the database changes. Automated database deployment ensures that application and database changes can be deployed automatically. Evolutionary database and automated database deployments ensure highly productive teams a path to continuous delivery.
Jul 2011
采纳 ? 我们强烈建议业界采用这些技术,我们将会在任何合适的项目中使用它们。
Jan 2011
采纳 ? 我们强烈建议业界采用这些技术,我们将会在任何合适的项目中使用它们。
The industry has seen significant changes to the way we use and store data over the past few years. Agile development practices have lead to greater emphasis on evolutionary database design, requiring new tools that support migration of schemas in line with changes to the domain model of an application. As storage space consistently becomes cheaper and data access speeds increase, many organizations are investigating the use of multiple schemas to hold data for different purposes, e.g. transactional and analysis schemas. Incremental data warehousing is becoming increasingly popular as the cost of moving data between a transactional data store and an analysis environment is less than the value of having access to near real-time reporting of critical business data.
Aug 2010
采纳 ? 我们强烈建议业界采用这些技术,我们将会在任何合适的项目中使用它们。
Jan 2010
试验 ? 值得一试。了解为何要构建这一能力是很重要的。企业应当在风险可控的前提下在项目中尝试应用此项技术。
已发布 : Jan 11, 2010
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