IaaS: Infrastructure-as-a-Service
The first layer is called IaaS, sometimes called Hardware-as-a-Service. A few years ago, if you wanted to run some enterprise applications on your office or company website, you needed to buy a server or other expensive hardware to control Native apps to get your business running.
But now with IaaS, you can outsource the hardware elsewhere.
IaaS companies provide off-site servers, storage, and networking hardware that you can rent.
Save on maintenance costs and office space, companies can utilize the hardware to run their applications at any time.
Some of the big IaaS companies include Amazon, Microsoft, VMWare, Rackspace, and Red Hat. But these companies have their own specialties. For example, Amazon and Microsoft don't just give you IaaS, they also rent their computing power to you. host your website.
PaaS: Platform-as-a-Service
The second layer is the so-called PaaS, sometimes called middleware. All of your company's development can take place at this layer, saving time and resources.
PaaS companies provide various solutions for developing and distributing applications online, such as virtual servers and operating systems.
This saves you money on hardware and makes it easier to collaborate between scattered studios. Web application management, application design, application virtual host, storage, security and application development collaboration tools, etc.
Some of the big PaaS providers are Google App Engine, Microsoft Azure, Force.com, Heroku, Engine Yard. Recent startups include AppFog, Mendix and Standing Cloud
SaaS: Software-as-a-Service
The third layer is also called SaaS. This layer is the layer that is in contact with your life every day,
most of which are accessed through a web browser
. Any application on a remote server can be run through the network, which is SaaS.
The services you consume enter these categories entirely from web pages like Netflix, MOG, Google Apps, Box.net, Dropbox or Apple's iCloud. Although these web services are used for business and entertainment or both, this is also part of cloud technology.
Some SaaS applications for commerce include Citrix's GoToMeeting, Cisco's WebEx, Salesforce's CRM, ADP, Workday and SuccessFactors.
DaaS is Data-as-a-service (data as a service), which is another new service concept after IaaS, PaaS and SaaS.
The main technologies it contains include data virtualization, data integration, SOA, BPM, and PaaS.
1.1 Data
Data (Data) is a physical symbol of payload or record information arranged and combined according to certain rules. It can be numbers, words, images, sounds, or computer codes, etc.
The point of data is to convey information. The reception of information begins with the reception of data, and the acquisition of information can only be obtained by interpreting the context of the data. The data background is
Information preparation for specific data by the receiver, that is, when the receiver understands the laws of physical symbol sequences and the directional target or meaning of each symbol and symbol combination, the information carried by a set of data can be obtained. that is
Data is transformed into information, which can be represented by the formula "data + background = information".
1.2 Services
Service is an activity, paid or unpaid, of doing something for others and benefiting them. Not in physical form, but in the form of providing living labor to meet a particular need of others.
The provision of services may involve: activities performed on tangible products provided by the customer (such as a car repaired); activities performed on intangible products provided by the customer (such as income statements required for the preparation of tax returns); Delivery of intangible products (eg information provision for knowledge transfer); creating atmosphere for customers (eg in hotels and restaurants).
1.3 数据即服务
数据做为一种服务是通过传递有用的信息以帮助他人的活动来实现的。
如有关汽车的组成及损坏情况的数据帮助维修师傅维修。我们经常上网查询资料，这些资料中的有用信息给我们的活动产生影响也是一种服务。
了解更多开源相关，去LUPA社区看看吧。
客户需求构建一个DaaS平台，其中所涉及的元素主要包括：
数据采集(Data acquisition)：来自于任何数据源，如数据仓库、电子邮件、门户、第三方数据源等。
数据治理与标准化：手动或者自动整理数据标准。
数据聚合：这个有很强的服务与技术驱动的质量控制机制，不是简单地写100个ETL程序。
数据服务：通过web服务、抽取和报表等，让终端用户能够更容易地消费数据。
http://blog.163.com/samuel_phoenix/blog/static/21515701420156241339709/