![]() ![]() You’ll need to convert this into a CSV file, which is extremely easy. Excel file ConversionĮxcel file extensions are usually xls or xlsx, open your file in Excel. csv (Comma Delimited) but can often be in a format that has a delimiter that isn’t so common. When you receive a file in Excel format, you must convert this data into a readable format. I will show you how to import data from an excel file using the DBA tool DBeaver. You might use pivot tables as well.There are many ways to import data into a database, some are pretty straightforward, and others are more complex depending on the type of data you receive and which format it is in. Notice that SQL uses specific column names instead of abstract cell references, and words like WHEN and THEN instead of parentheses and commas. The second statement returns two columns: the name of each Pokémon and a size label ("small" if under 5, "medium" if under 15, etc.). The first statement returns the sum of all weights in the pokemon table. SUM is used to add multiple values, and CASE is used to handle conditional logic. ![]() SQL offers the same functionality, with greater readability, thanks to its structured and English-like syntax. If you’re an Excel power-user, you might be hesitant to give up familiar formulas like this: ![]() Rather than taking a series of steps that are prone to error, slow to execute, hard to replicate, and cumbersome to share, SQL queries can be faster, easier, and safer. WHERE filters our data on specified conditionsĬompare this to the equivalent work in Excel.FROM is the keyword that tells the query to look at the pokemon table.name and type are columns in the pokemon table. ![]() SELECT is the keyword that tells SQL to start a query.They don’t have to manage file versions or risk corrupting the data, and they can re-run it on any other data.Īll of this contributes to the serious demand from employers for SQL skills. Teammates each have access to the same data, so they can run your analysis on their own. Instead of emailing a massive Excel file, you can send tiny plain text files containing the instructions for your analysis. When using SQL, your data is stored separately from your analysis. Excel can technically handle one million rows, but that’s before the pivot tables, multiple tabs, and functions you’re probably using. It can take minutes in SQL to do what it takes nearly an hour to do in Excel. You can run these queries with a SQL interpreter, which does the necessary retrieval and analysis steps for you. Instead of describing how to get the data-like in Excel or Sheets-your queries describe what data you want.You can save them the same way you save a text file. You retrieve data and perform analysis with queries, which are a sets of instructions written in SQL.Those tables usually look like one sheet in Excel, with rows and columns. Your data is stored in a relational database, which is made of tables.When we say "use SQL," this is what we mean: SQL is just a language used in programming. If you’ve ever been stuck staring at a "Pinwheel of Death" or an "Excel quit unexpectedly" message, you know the pain. If the number of rows is in the thousands, it could really hurt our workflow. In Excel, we have to use step-by-step instructions to get the data:īy this point we’ve edited the data (potential errors), we don’t have a copy of the steps saved anywhere (hard to replicate), and we’ll need to email the whole file to our fellow Pokémon trainers (painful version control).Īs the Pokémon table grows, Excel-or Google Sheets-slows down. Suppose that we want to use Excel to filter out everything but the name and type of every Grass type Pokémon in the table. ![]()
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