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Encoder ANSI/AIM Code 39 in Software Two

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Common stock B163 B162. Copy across to column G. B166 D166 Leave this blank because, for the historical years, retained earnings will be defined by the numbers from the data source, which will be entered in the input cells in row 165. E166 E65. Copy across to column G. This is the reference to the Net to retained earnings row in the income statement. B167 B165. Copy across to column D. E167 IF(E165,E165,D167 E166). For the forecast periods, we are most probably going to rely on retained earnings being calculated as the prior period s number plus the current period s net to retained earnings. So the formula need only be D167 E166 in cell E167. Nevertheless, on the off chance that you would want to use a specific input, we will use the IF formula shown to give you the ability to specify retained earnings by specific hard-coded inputs.
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In the program, the declaration of a generic class is similar to that of a generic function. The actual type of data stored by the queue is generic in the class declaration. It is not until an object of the queue is declared that the actual data type is determined. When a specific instance of queue is declared, the compiler automatically generates all the functions and variables necessary for handling the actual data. In this example, two different types of queues are declared. Two are integer queues. Two are queues of doubles. Pay special attention to these declarations:
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FIGURE 21-16
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Unfortunately, no company has completely clean data. The old saying is that as soon as you make something idiot proof, the universe creates a bigger idiot. While this is likely true, it s also a fact that many applications allow bad data into the system in the first place. Having bad data then makes analysis much more difficult. Here is a real world example: A company had a large presence in the city of Ann Arbor, Michigan. One of the systems asked customers for their address and the input box for the city was a free-form text field. People living in the city of Ann Arbor found (at last count) fourteen different ways to spell Ann Arbor. These included Anne Arbor, AnnArbor, AnneArbor, Ann Arbour, and so forth. The easy solution going forward would be to fix the application so that the city was chosen from a drop-down box. Unfortunately, the owners of that application were busy and didn t see it as a priority. Even if it had been fixed, however, this did nothing to handle the existing data that was incorrect. At this point, the business could have gone in and cleaned up all the source data. Instead, they chose to do the cleanup in their ETL process. The source system could continue to hold misspellings of Ann Arbor, but the data in the warehouse would be consistent. This was important because they wanted to analyze sales by city and when someone chose Ann Arbor, they wanted all sales for that area to come up without having to know to add in many misspellings of the city name. The ETL process was written to handle all known misspellings of Ann Arbor. Periodically, a new one would appear and the ETL would have to be updated. Note that today, this would have been much easier thanks to the Fuzzy Lookup transformation in SSIS, but at the time the customer had to do everything manually. Given that there are such data quality issues inside any organization, it s important for the business to come up with the rules for handling such issues. It s appealing to be able to say that everything will be fixed in the warehouse, but sometimes the effort to do so outweighs the benefits. Imagine a system in which bad records are flagged as unknown. If the estimate to truly fix the data is 2000 man hours, and less than one-tenth of one percent of the data is bad, is it worth the cost to fix On the other hand, if 40 percent of the data is bad, fixing the data probably has a much higher priority. Articles, whitepapers, and books can be written about data quality and the issues around it. The fact is that most organizations have bad data and still allow bad data to flow into the system. There are ways to ameliorate this but eliminating it entirely is often more costly than just living with some level of dirty data. It s important for business users to understand why bad data is in the system and what options exist to fix it, and why it might be necessary to see some percentage of data listed as unknown.
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How do you go about choosing a life that expresses all that you can be The first step is to identify and detail your human competencies.
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In this section we provide a review of the EdgeSight Server Console. The EdgeSight Server Console is the primary interface for accessing both real-time EdgeSight agent data and historical EdgeSight database data. The EdgeSight Server Console is a very power-
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fixed (int* p = &o.num) { // use fixed to put address of o.num into p Console.WriteLine("Initial value of o.num is " + *p); *p = 10; // assign to o.num via p Console.WriteLine("New value of o.num is " + *p); } } }
Table 6-2. Available Object Types for Object Groups
Pass Arguments to Main( )
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