Flexibility and a variety of options also characterize analytics in the cloud. There are many new possibilities with analytical analysis, but the most exciting possibility is predictive analytics; that is, the ability to predict future performance from historical data. The possibilities are almost limitless, but consider the use of Big Data for predictive analysis

Every major change in the way you conduct business entails some amount of risk; few aspects of the cloud have generated more discussion and controversy than those regarding its security and risk. In this time of breaches, nation-state hacking, and growing and profound concern with individual privacy on the Internet, cybersecurity has become a board-level concern, and rightly so.

The next step is to think about the data your applications can store in the cloud and how they might influence security and risk. Many companies classify their data according to its sensitivity: a marketing document has a very different security requirement than, say, a draft of a 10-K filing prior to earnings release.

During your migration to the cloud, some—perhaps the majority—of your applications will be moved more or less intact as virtual machines (VMs). This Infrastructure as a Service (IaaS) style of migration has a number of advantages, as discussed in previous chapters. After they are in the cloud, applications can take advantage of the numerous services available to them, quickly giving those applications far more function and return on investment. This chapter first looks at how you can redesign your applications to better take advantage of the underlying cloud framework, and then how you connect them to services in the cloud to rapidly expand their features and functions

There are many options for relational database functionality in the cloud, and they serve different purposes

The NoSQL arena has many options, ranging from simple object storage to complex document and graph-based data stores. 

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