Merci Amaya June 5, 2021 Spreadsheet
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.
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.
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.
When presenting your business plan to an angel investor you must understand that they will be very interested in your spreadsheets and proformas, but you must also realize that it is typically an entrepreneurial optimistic approach, which causes problems with proformas. Therefore, you should have dueling spreadsheets; that is to say the spreadsheets, which take your best guess and double the time, double the expenses to compete with your optimistic approach. You should be able to present both of these to your Angel Investor; who chances are is a retired business person with a little bit of financial savvy.
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.
These common complaints with Microsoft Excel filtering are heard time and time again by engineers, accountants, management consultants, bankers and finance professionals who work with data in Excel spreadsheets on a daily basis. Many spreadsheet users including financial modellers (who seem to be leading the charge) are turning towards Excel Add-ins and software tools that plug into Microsoft Excel to help them improve the in-built filtering logic of Microsoft Excel and thus analyse certain data sets quickly and easily.
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