A firm understanding of SQL terminology is key for anyone breaking into the tech industry. SQL is one of the most used programming languages amongst software developers. Our list of SQL terms will give you the groundwork you need to communicate and collaborate efficiently with your colleagues.
Our glossary of SQL terminology is the perfect place to start. This list of five common SQL terms will help anyone who is getting started in tech. If you are a budding data analyst, our SQL terminology cheat sheet is for you. These advanced terms will give you the edge you need for a highly successful career.
What Is SQL?
Structured Query Language (SQL) is a programming language used to communicate with a single database. A database is a collection of rows and table columns that are structured in the relational model. With SQL, you can extract and organize data in relational databases. SQL is basic and easy to read, with a syntax similar to the English language.
Furthermore, SQL facilitates a hierarchical database repository that helps identify, diagnose, and resolve problems. This aids active transactions, improving the database performance. Relational databases like Microsoft Office leverage SQL for data extraction. Big tech companies like Facebook, Microsoft, and the Oracle Corporation use SQL for backend data storage and analysis services.
Who Uses SQL Terminology?
SQL terminology is most commonly used by data professionals. However, basic SQL terms are used across all sectors of the IT industry. This is due to the popularity of SQL and its use in data extraction across numerous platforms.
Professionals who utilize SQL terminology include database managers, data analysts, web designers, SQL developers, operations research analysts, relational operators, server management specialists, and computer research scientists.
List of SQL Terms: Things Every Data Analyst Should Know
- Aggregation Function
- Data Block
- Data Manipulation Language
- Database Administration
- Database Buffer Cache
- Database Client
- Database Commands
- Database Engine
- Database Files
- Database Instance
- Database Management Systems
- Database Manager
- Database Object
- Database Server
- Database Tables
- Database Transaction
- DTU-Based Purchasing Model
- Input Values
- Memory Databases
- Oracle Databases
Glossary of SQL Terminology: 5 Common SQL Terms
This glossary of common SQL terms is ideal for any novice data professional. Whether you are starting a new job or looking to advance your career, these common SQL terms will get you started.
An aggregate function is when the values of multiple rows are summed together to create one value. This function is performed within a relational database that uses the relational model. The different aggregate functions you can use include Sum, Count, Avg, Min, and Max.
Why Data Analysts Need to Know About Aggregate Functions
An aggregate function is essential for data analysts. Aggregative functions are often used to attain descriptive statistics which is ideal when you want to show your results. This database feature will also ensure you obtain the correct values in your relational table.
A data block is the basic unit of data storage in a relational database. If you work within the Microsoft Oracle database, these data blocks are more commonly called Oracle blocks, logical blocks, or pages.
Why Data Analysts Need to Know About Data Blocks
Data analysts use data blocks to identify what to read or write once a trigger block event executes. It also helps them transfer data between the relational database and their iFIX process database.
Database files contain data that is stored within a database, such as tables, indexes, and views. There are three types of database files, including primary, secondary, and transaction logs. These database files can be stored on separate drives.
Why Data Analysts Need to Know About Database Files
Understanding database files allows data analysts to leverage its components, such as data files and log files. They can use database tables, stored procedures, or views. These database files also provide access to all transactions in the database through log files.
A database server uses a database application to share database services with other computers within the network. Authorized users can access the required data. This keeps the data in a central location so it can be backed up regularly.
Why Data Analysts Need to Know About Database Servers
A data analyst will need to be familiar with database servers to access data across a network. This will allow analyst teams to have simultaneous access to data securely and easily. Setting up and maintaining a database server is a critical role for data professionals.
A database object is used to store or reference data. These database objects can be used to hold and manipulate data. The most common object that people use is the database table. Other objects include indexes, sequences, and stored procedures.
Why Data Analysts Need to Know About Database Objects
Understanding database objects is crucial for any data analyst’s performance. For example, an Azure SQL database contains Schema objects that have table objects. Data analysts can attain essential data from the derived tables.
SQL Terminology Cheat Sheet: 5 Advanced SQL Terms
As you learn SQL, you will encounter complex terminology. This SQL terminology cheat sheet will help you master these advanced terms and boost your SQL and database knowledge.
Database Buffer Cache
The buffer manager copies data to the database buffer cache when it is written to or read from a SQL server. Data is written to the hard disk when the data is no longer used or the buffer cache is full. This allows you to quickly access frequently used data and improve workload activity.
Why Data Analysts Should Know About Database Buffer Cache
Database buffer cache impacts performance significantly. Therefore, a data analyst must know how to use the database buffer cache efficiently. If queries slow down, it is usually because of a buffer cache issue.
At its core, a database instance is the entire structure of a database system and its collection of processes. This environment includes the relational database management system (RDBMS), client applications, the relational model, and stored procedures.
Why Data Analysts Should Know About Data Instances
A data analyst can use a database instance to manage specific data and assist users of the associated database. Since it involves background processes, it can be run in different configurations including single-instance configuration, one-to-many relationship, and Oracle Real Application Cluster (RAC) configuration.
Database Management Systems (DBMS)
DBMS refers to software that manages data storage, order, and retrieval. This allows users to interact with underlying data. Some examples of DBMS include Oracle, Postgre SQL, Microsoft SQL Server, and MySQL.
Why Data Analysts Should Know About DBMS
Database management systems act as intermediaries between the database and the database user. As a result, they help data analysts access files stored in the database. Data analysts can also get an integrated view of the data and translate the different applications into functions that fulfill all incoming client connection requests.
Data Manipulation Language
Data manipulation language (DML) refers to the process of editing the data in spreadsheets. It is a programming language that can be used to add, delete, or modify data. When using SQL, data manipulation language is used as a sublanguage.
Why Data Analysts Should Know About Data Manipulation Language
Data analysts can use DMLs to gain in-depth insights into data. It gives data analysts the flexibility to easily modify the data they want to retrieve and access. This speeds up production time and helps inform better business decisions.
A database transaction refers to a collection of operations that function as a unit. This transaction must be logical and contain one or more SQL statements. The four properties of database transactions are atomicity, consistency, isolation, and durability.
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Why Data Analysts Should Know About Database Transactions
As an aspiring data analyst, a database transaction can help you easily identify a change in a database. When working within a company, this can help you optimize operations and identify critical user information.
How Can I Learn SQL Terminology in 2022?
You can learn SQL terminology through various online resources, such as coding bootcamps. These SQL bootcamps will provide you with in-demand skills and knowledge of SQL terminology. Moreover, these bootcamps train you over a short period of time. SQL tutorials are another excellent resource for learning SQL terminology in 2022.
Also known as a database transaction unit, DTU is a blend of CPU, memory, reads, and writes. The DTU-based purchasing model provides preconfigured computing resources and storage bundles to propel performance in different client applications.
User-defined function refers to functions that accept parameters, return a value, and perform complex calculations. They are designed to use logical storage whenever necessary.
Also known as ADDM, Automatic Database Diagnostic Monitor refers to the automatic detection and reporting of performance issues in databases. It helps you identify problems and provides recommendations on solving them, boosting the application-specific database operations.
If you want to learn SQL via a coding bootcamp, we would recommend Thinkful, Nucamp, or Simplilearn. These courses will help you master database configuration, database backup, and other database activities.
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