Arjean Lydia May 1, 2021 Spreadsheet
The former hangs like a transparent curtain four feet above the floor and shrink-wraps itself to anyone bold enough to attempt passing through. The latter represents a fragrant blend of beer, cheap cologne, and unkempt toilets, and assaults an unsuspecting visitor‘s nose like an aggressive index finger. By Saturday, the fragrance would be pungent enough to cause mere mortals to speak in tongues. Lance led the way with Lester in tow, dodging around dark figures that emerged from the nicotine and odoriferous fog. Lester had difficulty keeping up, licking the lenses of his glasses and tie-drying them as they wove their ways toward diffused light they assumed was the bar area where lusty women awaited.
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.
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.
Structured Query Language, often referred to as SQL, is a grammar of instructions that allows us to tell a relational database to add, modify or delete data. The key benefit, pardon the pun, of SQL is that it allows us to craft instructions relating large sets of data together. In this way SQL is the natural complement to the single cell and formula based interface of spreadsheets like Microsoft Excel. Imagine you had five hundred appointments from your business calendar laid out in a table. Each appointment might have a day, time, location and description. Now imagine you also had five hundred appointments from your partners business calendar, also each having a day, time, location and description.
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.
”Happy crapola!” he exclaimed, rising from the rollered chair and scooping accordion folds of printouts into his tattered briefcase. He snatched his worn black suit coat from a hanger on the back of the office door, switched off the fluorescent overheads, and walked to the executive offices in the adjoining building. When his audit week ended, Lester typically teamed with Lance Lott for a tour of the local watering holes. Lance was a marketing guy he‘d met when he first worked the Bourgeois account. Lance also was single, and resembled Keanu Reeves on a bad hair day. Lester considered him a ”chick magnet,” and although he himself never got lucky on their semi-annual expeditions, the other always disappeared with a babe on his arm. Lester decided, tonight would be HIS night.
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