A compilation and review of articles about technology, current products, and discussion of how it all sometimes has unintended consequences.
12 IT Disasters
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May 28, 2009 (Baseline) Learning from your mistakes is good. Learning from others’ mistakes is even better. Baseline looks at 12 major IT failures to learn more about how and why they happened.
Today in Operations Management we had our "Billionaire's Challenge." Each semester we do a production case study involving Excel's Solver "add in." Students must first solve the case, earn at least one-million dollars profit, and then may compete to make at least $1,000,000,000. This semester's Billionaires are: Kevin Kolb BreAnna Nuñez Zach Pusti Jordan Tucker Congratulations! For more information on this exercise, refer to my earlier post .
Last week in Operations Management we used Excel to calculate the Economic Order Quantity and graph Carrying Costs, Ordering Costs, and Total Costs. The Economic Order Quantity or "EOQ" is the order size that "minimizes" Total Costs. Any more or less and you are spending too much on ordering or too much on keeping inventory. For example, in the Excel spreadsheet below, if you had an Annual Demand of 12000 units, Ordering Costs of $10 per order, and Holding costs of $4 per unit per year, the EOQ would be 245 units and Total Costs would be $980.00: We used the following formula in Excel to calculate EOQ: =SQRT((2*B2*B3)/B4) And the following formula to calculate Total Costs at this point: =$B$6/2*$B$4+$B$2/B6*$B$3 To create the graph, we used the following formulas and simply copied them over a range of 100 to 500 units. Ordering Costs: =$B$2/D2*$B$3 Holding Costs: =D2/2*$B$4 Total Costs: =F2+G2 Looking at this chart, we can clearly see that our order size of 245 is ...
Power Query is found within both Excel and Power BI, helping users to transform and clean up their data before they analyze it. With Power Query, you can easily connect to data sources like Excel worksheets, external databases, websites, and even Cloud services. Once connected, you can import data and perform a wide range of data transformations. Data Cleaning: Clean up messy or redundant data. Power Query can help clean up by removing duplicates, correcting errors, and standardizing formats. Data Transformation: Power Query lets you pivot, unpivot, merge, and append tables to get your data ready for analysis. Columns: Add calculated columns or split existing columns. Similar to the way we do it in Excel, Power Query makes it easy to perform various operations. Data Merging: Power Query can merge data from separate tables or files into a single large dataset for analysis. Power Query records all the steps you take to transform your data so if your data changes, you can refresh your qu...
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