Chantel Enora June 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.
Microsoft plans to have this program up soon and now Google is beta testing a similar situation, which would allow you to do essentially the same thing. Why is this good? Well, consider the Digital divide in the world and if everyone just had a terminal rather than a big hard drive with lots of expensive stuff on the computer then they can store all their information at one location. By doing this, the computers would actually be terminals and it would be very inexpensive to make them, meaning that everyone in the world could afford to have one and everyone in the world could be online and interconnected in a giant collective of humanity. There would be no one who would be without the Internet and this would bring the world closer together in a common cause.
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.
He grossed $2,000 a week for his bosses, and earned slightly less than $500 for himself. Still, the wages kept him in seeds, bowling shoes, stick pins, and a Platinum Buddy Holly Fan Club Membership. Lester‘s favorite word was ”crapola,” and he applied it to the ball bearing factory‘s antiquated data processing system in coats as thick as the olive drab membrane clinging to the smudgy glass before him. ”You piteous piece of crapola!” he‘d hiss at the computer when error messages flashed across its screen or its ancient system locked under the demand of crunching numbers to the tenth decimal point. ”Some day I‘ll throw your sorry ass into one of those melting pots out there!”
Microsoft Excel is a phenomenally powerful calculator. You can create spreadsheets with 10,000 lines of data and calculate subtotals instantly. Indeed, if you change your data, any totals will get automatically updated. Arguably that‘s not too impressive. If we have quarterly revenues of $1m, and we secure another $20k, we can update our subtotal without summing revenues from scratch. So it‘s more impressive that Excel can do the same thing with statistical functions. If you‘ve ever plotted a chart on Excel, you may be aware that you can add a best fit line. These best fit lines are calculated using a method known as regression. Basically, you have to calculate the distance of every single point from the line, and minimise the sum. The maths is a little more sophisticated but the key point is that, every time you change the data, you need to perform the analysis all over again.
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.
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