ta for the missing values? intended purposes? Auditability-Is the data checked regularly against these aspects? 8.2.3 DATA MANAGEMENT: LAMBDA ARCHITECTURE AND POLICIES As partially described in the previous sections, there are a variety of data management and policy issues that must be decided for a big data system, such as what type of data is collected, how long data is retained, whether data is summarized or anonymized, and whether data is processed and accessed in batch versus real time. Many big data systems utilize batch and real-time processing of data as summarized in the lambda architecture shown in Figure 8.2. Master Batch Layers Query 1 Query 2 Real- Layers 1...M FIGURE 8.2 Lambda architecture. (From Lambda Architecture, http://lambda-architecture.net/.) Network Data and Optimization In many circumstances, other factors beyond the value of the data, such as policy and ethics, gov- ern whether certain data are collected, utilized, retained, or shared. For example, the Federal Trade Commission (FTC), sets data collection and use policy for Internet companies, such as Google and Facebook, with respect to consumer's privacy. The Federal Communications Commission (FCC) estab- lished rules governing data collection and use by ISPs in November 2016, but those rules were based on the premise that the Internet Service Providers (ISPs) are uniquely "able to develop highly detailed and comprehensive profiles of their customers" [NPRM16], which is practically not the case. For example, the following "Future of Privacy Forum" blog [FPOF16], illustrates that a single visit to WebMD.com connects to 24 third-party sites, after which visiting another four websites, a total of 119 third-party sites were connected to. Since many of these third-party sites are advertising related, the data are naturally shared in data exchanges and a comprehensive view of the customer is formed. Further descriptions of various privacy policies and issues are described in this wiki [WikiPrivacy]. Because the asymmetry embodied in the FCC r