Charlotte Lison June 4, 2021 Spreadsheet
He was an ex-divorce attorney who had seen firsthand what a messy thing divorce was when lawyers were involved. He developed a program where a couple would meet together, with him present, and work through the divorce piece by piece. Property, finances, kids, pensions. It was a great system. And he was cheap! Relatively speaking. It took about 10 months including some stops and starts (”what do you mean you want some of my inheritance? if you want my inheritance then you STAY married to me”) but in the end we were able to come to terms with each other in a reasonable and fair way.
In a well-designed spreadsheet, any output can be calculated from the raw data. However, that‘s not always enough. Sometimes the output is fixed and the raw data is variable. Let‘s say you run an investment company and want to offer your clients a fixed return. An Excel expert could create a very complex model to calculate the likely return on investments over a fixed period. You could then calculate the internal rate of return being offered to clients. The problem is that you‘re not interested in the return offered to clients; that is, after all, fixed. Instead you‘re concerned with how much money you expect to draw from the investment fund, whilst still offering your investors a satisfactory return. If you have $1 and owe investors a quarter, you can calculate your profits using a simple formula.
So why does data that inevitably finds its way into a Microsoft Excel spreadsheet often suffer from the problems outlined above. The reasons are many. If the data is imported, it may have been sourced from a combination of other spreadsheets, databases, systems, reports, word documents, emails or web pages. If the data has been entered manually it may have been poorly done so by an inexperienced computer users such as administrative or junior staff with a lack of understanding for data structures. Excel is easy to use and widely accessible, so an inexperienced colleague can quite easily update your spreadsheet with a false sense of confidence and inadvertently enter new data incorrectly. And finally, unlike a fully functional software system, data entry in Excel generally has no automatic validating rules, unless carefully setup by the spreadsheet‘s creator.
Given this data set imagine trying to find out which Fridays you were busy at an appointment at noon while your partner was also busy at an appointment at noon and the descriptions of both of your appointments contained the phrase down town. If you are not familiar with relational databases and SQL it might surprise you to know that the question can be answered by a single simple SQL query. The database and SQL don‘t have it all their own way however. Spreadsheets come in to their own for tasks that benefit from a visual representation. Traditionally databases do not provide a visual way to browse the data in tables without explicitly requesting data.
You can go over your budget as often as you like. Some find it easier to enter amounts every day after they‘ve settled in for the day. Others will choose to go over it monthly. Going over it weekly is likely where most will settle though. Occasionally, we‘ll have a surplus or deficit at the end of the month. Perhaps you‘ve spent too much, or not spent all that you thought you would. Spending too much can be troublesome, but not spending as much as you thought can be a lot of fun. You may want to consider adding a budget field carryover in the income sheet and one called shortfall in the expenses sheet. If you spent too much, the amount that you overspent by becomes your budgeted amount for shortfall in your expenses sheet the next month. Didn‘t spend enough, and you put that amount in the carryover field in the income sheet. This will help you keep track of all your money as well as account for any shortfalls.
As a set of general rules data is most useful when things like text fields hold only names as well as meaningful and validated codes, categories and classifications. Text notes and other free form text should be isolated to a dedicated notes field and thus separated from other numeric data. Numeric fields should hold only numeric values (numbers, dates, %‘s and in the correct quantum or magnitude with no text prefixes, suffixes, spaces, text elements or text notes present. You must also be careful that numeric data is not stored as text and it should be internally consistent in terms of the correct format so that it can be used in calculations or for comparison and queries. Finally, addresses should be separated out into multiple fields such as street address, town /suburb, state / province, postal code and country to allow for geographic analysis and mail outs if required. Fixing up a data set to meet these criteria is called data scrubbing, cleansing or massaging. This data cleansing process can be very time consuming even for an experienced Microsoft Excel user, database engineer, business analyst or computer programmer.
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