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Investigate the use of different types of database structures in the source database, the use of complex data types, and features that are specific to the source database technology Investigate if database-specific access structures have been defined for speeding queries For example, the Teradata database has the capability to create join indexes for speeding up queries that involve joins Join indexes in Teradata can be translated to Oracle Materialized Views If such straight translations to Oracle-equivalent objects exist, the objects will be the candidates for automated migrations The objects that are proprietary to the source database technology and for which an equivalent object does not exist on Oracle will need to be manually analyzed and migrated Document the use of procedures, functions, triggers, complex types, and methods Also gather the source code LOC metrics and the complexity metrics that categorize the object into low, medium, or high Analyze the use of non-ANSI SQL implementations for DML (Data Manipulation Language, or write operations) and queries This usage makes the SQL hard to translate, so it is important to document such occurrences Analyze the use of server-side scripts, their purpose, the scripting languages used, and all the source code related metrics that are associated with it Capture the performance metrics of the database server the I/Os per second (IOPS) for short I/Os and the MBs per second (MBPS) for long I/Os Calculate the disk space utilization of the current database The space used by data, indexes, summary tables, staging schemas, and projected growth requirements for the next three to five years should be estimated Also incorporate nonlinear growth requirements that arise in order to support ad hoc growth Capture the database authentication requirements mainly the administrator and user authentication and the requirement of LDAPbased authentication mechanisms Capture the security authorization requirements of the database schema mainly the database roles, users, and privileges.

To successfully utilize the iron condor there are a few factors to keep in mind, With the iron condor we are looking for elevated implied volatility and a market with a reasonably de ned trading range Also we like to see probabilities of under 30 percent for hitting the outside strike prices, so make sure your condor is wide enough to account for the trading range Condors have multiple commissions and fees that must be calculated into the breakeven The effect of the commission on the breakeven will be greater in futures trading because each option generates a commission, and in equity trading the commissions will increase in trades that represent over 1,000 shares in most cases Risk for a condor should be considered as the entire spread on one side of the trade plus costs of trading You can certainly set any of the risk strategies we have discussed for the condor, from monetary stops to a percentage of the premium, but be prepared for slippage resulting from liquidating four options at the market on a stop Make sure your risk-to-reward ratio doesn t exceed 3:1 on the iron condor If your risk is higher than three times the premium captured, you are not creating enough premium or selling enough volatility The trade demonstrated is the opposite of this, but it is not common for the reward potential to be substantially higher than the total risk in a short wingspread

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Figure 74: Covariance analysis results for the system of Section 71 with an additional velocity sensor The top graph shows results for the standard deviation of position p The bottom graph shows results for the standard deviation of velocity v in this section

IOPS (input/output operations per second) and MBPS (megabytes per second) are the metrics that measure performance of storage devices IOPS measures the small I/O performance, which is a typical characteristic of OLTP workloads The objective of measuring IOPS is to see how fast the storage is capable of writing (or reading) transactions that span a small number of disk blocks IOPS can be measured for reads, writes, or mixed read/write transactions, with a typical 4K or 8K block size The MBPS metric measures the storage bandwidth utilization, which is the total number of bytes flowing through the storage device or the network per second The MBPS metrics are associated with large I/Os that prevail in data warehousing and reporting environments These environments have workloads that scan large volumes of data from the storage

Figure 817: Single di erence DGPS L1 C/A position estimate scatter plot Example 88 Figure 81 presented GPS position estimation results For the same set of data, a scatter plot of the di erential L1 pseudorange position estimation results is shown in Figure 817 The north, east, and down position estimation error mean vector is [002, 016, 008]m the error standard deviation vector is [03, 02, 07]m A scatter plot of the di erential L1 (integer-resolved) phase position estimation results is shown in Figure 818 The north, east, and down position estimation error mean vector is [0008, 0001, 0014]m the error standard deviation vector is [0004, 0002, 0009] As expected the phase estimation standard deviation is approximately 100 times improved relative to the pseudorange estimation standard deviation

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