Lucille Rose May 28, 2021 Spreadsheet
At times, Lester became so furious his face radiated heat and fogged his glasses. When this happened, he yanked them from his puffy eyes and wiped the lenses with his tie. On this late Friday afternoon, however, Lester felt exhilarated. The printer regurgitated its last run of printouts and as he scanned the rows of figures he penciled in tick marks to indicate matches with numbers found in the corporate ledgers. The task complete for another 180 days, he removed his glasses, rubbed his aching eyeballs, and inhaled deeply to savor the fluttery feeling of excitement flooding his upper chest. Then, Lester logged off the computer, tapped the surge protector power switch with his toe, and shut down the wheezing system.
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.
Lester loved his numeric universe, but this was not how he had envisioned his life unfolding; flying hither and thither from his hometown of Hershey to wherever his firm wished to send him. Just because he was 38, single, and still living with his folks didn‘t mean his employer should take advantage of him which, in fact, his company did on a regular basis. After all, Lester had other important interests, too. The ”Four Bs” he called them: Botany, bowling, bugs and Buddy Holly. Myriad plants crowded his tiny room in his parent‘s house, forcibly sucking carbon dioxide out of anyone who entered. Bowling trophies – ranging in size from tiny silver cups to massive bronze edifices shaped like the Empire State Building – claimed space not dominated by flower pots, planter boxes, and hanging baskets.
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.
First – History/Budget – what kind of a history do you have from your last convention? Did you fill out forms that showed all the results of your meeting? You started with a contract that specified sleeping rooms and scheduled functions, but did you update those numbers at the conclusion of your convention? This is important! You really do need to know what happened last year including your exact sleeping room pick-up, registration numbers with total income generated, specific meeting expenses and the number of attendees that attended each function. Without these numbers you are just guessing.
When Microsoft Excel is used to manipulate, store and analyse data it can become extremely difficult to manage, let alone efficiently work to produce any meaningful insights. This is because with data sets large and small, the data must be meaningful, logical, structured, internally consistent and clean. This holds true regardless of whether the data has been imported into excel from another system or manually entered. In this computing age, most people know that for any data set to be useable it must first be relatively structured and clean. A spreadsheet and its table layout naturally encourages data to be somewhat structured, however ensuring data is clean is also difficult.
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