Ever looked at a database and been overcome by the need to explore its contents? Imagine it pulsating with an array of data, ready to be unearthed. This task could seem daunting, particularly for starters, but thanks to SQL, it's quite attainable. A simple SQL command, SELECT, permits you to peek into this treasure trove and extract data from databases. Accompany me as I unravel what SELECT can do using an absorbing Matches database.

Okay, let’s write a SQL Select query. The Matches database that I've allocated comprises of a solitary table dubbed MATCHES. This table is crammed with 50 years' worth of competitive sports game data, from 1969 to 2018. Ten columns preserve this data: Match ID, Match Date, Team 1, Team 2, Result, Goals Team 1, Goals Team 2, Venue, Tournament, and Referee. Captivating, isn't it?

Let's draw all the data from our matches table. In order to execute this, we deploy two essential constructs of SQL - SELECT and FROM. Your query would henceforth become, SELECT * FROM MATCHES. You can evidently observe all ten columns, with the first column indicating the record number.

A quick review exposes that there is a record of 23,119 matches - more than a single match per day for the past 50 years. The actual charisma expresses itself when you begin deploying functions such as COUNT to rapidly ascertain row numbers and accelerate query speed – because when dealing with databases, every millisecond counts.

Let's exercise the choice—instead of drawing all columns, we can morph the query to select specific columns like Venue, Result, and Match Date. So the subsequent query would be, SELECT result, venue, match_date FROM MATCHES. SQL's charm is displayed with the capability to select columns in any order of your choice.

Next, we employ the WHERE clause to select rows. While the SELECT keyword is deployed for column selection, the delineation of rows is done using the 'WHERE' clause. For instance, one could select all matches that transpired after January 1, 2000, with the query: SELECT * FROM MATCHES WHERE match_date >= '2000-01-01.

Employing WHERE, COUNT, and SELECT commands, it's rather straightforward to answer a particular inquiry: "What was the result of the highest scoring match in 2010?" The ORDER BY clause can sort returned matches by result, and the sort order can be confirmed using the keyword DESC after the column name. Still, scrolling to the end of the produced results could be arduous. This is where LIMIT serves its purpose in limiting the number of returned rows.

In summary, if you wish to excavate data from a table, you initiate your query with SELECT, specify the requisite columns, and use the FROM keyword to select the table. You can limit rows using the WHERE clause. Further refinement of the query occurs with the sorting – ORDER BY clause – in ascending or descending mode. Lastly, the LIMIT keyword restricts the number of returned rows.

If you are seeking a quicker and simpler solution, AI2SQL is the right choice for you. It is a SQL query builder that allows you to construct queries by writing text. Additionally, it corrects SQL errors in your existing queries.