Laverna Philippine May 7, 2021 Spreadsheet
Whilst Excel cannot clean or structure all of your data for you it does come with some useful functionality for manipulating and analysing clean and structured data sets. This in-built functionality includes pivot tables, sorting and filtering. Filtering alone is a powerful tool and can help to quickly isolate data based on specified criteria. But what happens if your data is clean but not very structured (a common problem). For instance what if you, a client or your team is using colours, fonts or some kind of formatting to classify data in an Excel spreadsheet. In short, you wont be able to filter the data, because Excel‘s in-built filtering logic requires rules based on numbers, dates and text only. It will not perform filtering based on formats. In addition Excel filtering only applies down rows. It will not perform filtering across columns.
Lester‘s temporary office at the Factory was glassed on all sides, and surrounded by the sights, sounds, searing temperatures, and smells of the smelting and pouring areas. Originally, the cubbyhole had been used for storing coal and coke until the plant converted to gas-fired furnaces in the mid-‘50s. Over the next three decades a succession of plant superintendents used the room to boink their secretaries, which necessitated its windows being painted a squalid olive drab. During 10 years of performing this chore every six months, Lester had scraped two panes clear, so now he could gaze into the murky, smoky, smelly pit outside as he waited for the grinding computer and clackety printer to spit out a stream of spreadsheets.
Spreadsheets such as Microsoft Excel are well suited to tasks involving the manipulation of small amounts of related data. Working out a budget, producing visual reports, organizing lists and calculations that involve many variables are all tasks well suited to a spreadsheet. There are some data related tasks however that spreadsheets such as Microsoft Excel are not suited for. Tasks involving the processing and combination of large sets of data for example are generally not well suited to spreadsheets. There is another technology with a long history and theoretical background that specializes in these sorts of tasks. That technology is relational databases. The most common way people insert data into and extract data from relational databases is via the language of Structured Query Language.
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.
Here‘s where the expense sheet gets complex. All of your categories of spending go in column A. Get as detailed as you like, or keep it really simple and just put the basic categories. Generally, the more detail the better. it‘s also helpful to have categories for your categories. A Utilities category for your power, gas, water, etc, categories. Again, detail is good, but be wary of going into too much detail. Column B is where you‘ll put the amount that you‘re budgeting for that category. Column C, how much you‘ve spent on that category to date. If you like (or are a statistics junkie) you can add columns for % of budgeted amount, and % of total budget as well. For our simple budget, we‘ll just leave that out for now.
His entomological collection occupied any open areas large enough to accept skewered insects. And his Buddy Holly collection consisted of three scritchy albums the talented tunester recorded before dying at 22 when his plane crashed in Iowa. Lester wore black horn-rimmed classes identical to those of the late singer, and considered these a statement to the world that a ”cool” persona existed within his ”bean counter‘s” body. Too, Lester was a college graduate: Penn State, class of ‘78. He maintained a solid ”C” average over four years, and finally earned ”Certified Public Accountant” status on his fifth try. ”Reversing entries are hemorrhoids in the ass of accounting,” he remarked flatly during a first interview with his present employer, who dwelled briefly on his gradepoint average and numerous shots at CPA accreditation. ”They tricked me every time!” In spite of his lackluster academic record, the firm hired Lester and beginning Day One sacrificed him to Bourgeois and 20 other mediocre accounts.
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