Structured query language (SQL) is one of the most important computer languages and data technologies in use today, but many people will never encounter SQL directly. Unless you work with data, particularly on the web, you probably have no idea that SQL is used all around you.
From searching databases to find products when shopping online to checking your username and password against a database to pull up your account, SQL is used for all sorts of things. If you want to know more, check out the following:
SQL Queries to Identify and Retrieve Data
Data is what makes the Internet work, and therefore, it is what makes things such as computers and smartphones work. Raw data is generated constantly by websites, apps, manual data entry, search engines and so much more. To sift through this data, it must be organized, or else it becomes meaningless.
SQL allows for datasets to be queried to find the right data. This language can also be used to identify dataset outliers when making a comparison or analyzing data to find specific results. To identify dataset outliers, a query is made against a dataset that contains entries that are expected to be there. Outliers are entries that do not match the expected result, and therefore, these can be pulled to showcase where data exists that does not belong or match an expected result.
How Do Queries Work?
When you query a database, you enter a search string. SQL parses the syntax and compares your search string against entries. If matches are found, SQL will return the results. You will usually select a table to search along with a field name. These represent the rows and columns of the database.
Queries also rely on operators and conditions to find exactly what you’re looking for. An example of an operator may be where you insert “NOT” to display entries that match the condition of not being true, meaning the opposite of what you’re searching for.
Conditions can be used to look for specific data as well. For example, using the “WHERE” condition means that your search will look for data from a specific place in the dataset while excluding matching data from other areas of the dataset. This is used to avoid returning irrelevant results.
Author Resource:-
Jeson Clarke writes about technologies, import/export data and customs data tools. You can find his thoughts at data analytics platform blog.
