SQL or structured query language has an important role in the database management process of any given organization. When considering a data analyst’s job or DBA role for an organization, it is important to have people with hands-on experience and skills in SQL. SQL is a very simple yet powerful language that is widely used for data manipulation in relational DBs. Here in this article, we are discussing some important concepts one should know about SQL for data science. It will give you a fundamental overview, and for more advanced knowledge, you can access the advanced database management topics.
Relational databases and SQL
A database is a collection of structured data, which is made accessible for the users and applications. A relational database is a set of data, which contains some predefined relationships between two columns or two rows in a table. Some of the key terms related to database structure are records, tables, primary keys, attributes, etc., which contain one or more categories of data.
Relational database management systems for RDBMS are there in practice for more than four decades now, and this is the first-generation of database models, which had undergone various changes over time. From the basic data stores to advanced data warehouses and cloud, database databases have various forms and purposes now. When it comes to enterprise database management, database administrators need to have a fair understanding of the databases’ requirements and the applications and uses, which are connected to the DB to structure and run it well.
There are various tools and packages available now for database administration, which you need to choose very carefully in order to ensure optimum performance and upkeep of the databases. There is external support also available for enterprise database administration through remote DBAs. However, all the providers offering remote database administration services are not equal. You need to ensure that you are partnering with reliable and professional service providers when you are availing database platforms or database management as a service. If you are planning for remote administration, you can rely on the services offered by expert providers like RemoteDBA.com.
Further in this article, we will look deeper into to structured query language as the key database administration language. SQL is the most fundamental data covering language, which consists of various commands and structures to ensure proper storage, retrieval, and manipulation of data.
Understanding basic SQL commands
Data Definition Language or DDL- DDL commands are CREATE, DROP, ALTER, and TRUNCATE, which are used for creation, dropping, forming, altering, and modifying the database objects.
DML or Data Manipulation Language – Commands under DML are INSERT, DELETE, UPDATE. As the names suggest, these are used to insert, deleting, and update the database object structures.
DCL for Data Control Language – DCL commands like REVOKE and GRANT are used to provide add-on security to the database objects.
DQL or data query language- DQL command of SELECT is used to retrieve data from the given database.
TCL or Transaction Control Language- TCL commands are COMMIT, SAVEPOINT, ROLLBACK, etc., which are used to manage various database transactions.
This is just an overview of the SQL commands, each of which serves a unique purpose in standard database administration. A DBA must be thorough with the usage of all these types of commands in order to ensure proper data management and database administration.
Understanding joins in the database
SQL features various joins as Inner join, Right join, Left join, Full join, etc. SQL joins are primarily used to combine database records from two or more database tables. Let explore different types of joins in detail below.
Inner join– This join is meant to select all the records with matching values in both of the given tables.
Full join- This join selects all records either from the left or the right table.
Right join- This join is meant to select records only from the right-most table along with matching records from the left table.
Left join- This join can be used to select the record at the leftmost table along with matching records from the right table.
SQL interface with R or Python
Suppose the programmers know the statistical analysis languages like R or Python. In that case, they can easily run the packages of both these languages to build machine learning capabilities on SQL server data sets. Knowledge of these types of statistical programming languages and a good understanding of SQL will help programmers move up their career ladder. Using R or Python in combination with SQL Server, you can perform the tasks for data analysis, manage different datasets, create an interactive visualization of data, and so on.
Gaining knowledge of Advanced SQL
Once you have a basic understanding and insight of SQL, you can try to learn much deeper into the concepts of Advanced SQL. In this advanced part of SQL, you may learn about various concepts and keywords as UNIOR, INTERSECT, LIMIT, TOP, AUTOINCREMENT, IDENTITY, and more. These are used to create advanced reports in SQL and also to perform some complex pattern matching tasks.
To start with common database management systems and practices, to have a fair understanding of SQL. As the database management requirements and the database’s size increases, where you have to manage complex database tasks and analysis, etc., you need to know Advanced SQL too to manage these tasks. A beginner can know SQL as this is a very simple and flexible programming language to learn. Usually, enterprises deploy expert database and SQL programmers in order to manage the DBMS scenario. As discussed above, you can also avail of the support of third-party remote database administration service providers, who can make your job of database management much easier and comfortable. While availing of the database as a service or DBaaS, you have to just pay for what you subscribe to and also need not have to bear any licensing cost of hardware components in terms of database infrastructure.