There is very high demand for data scientists right now in the market. The hottest job of the twenty-first century offers a six-figure salary in dollars and a job satisfaction score of 4.4 out of five. That is the reason why data science is on the top spot of jobs on websites like Glassdoor. Data analysis of these sites shows that SQL is one of the top three skills required for a data scientist. If you have just started learning data science fundamentals it is important for you to start learning SQL.
SQL is the powerful domain-specific language that is used for communication with a database whether it is big data spanning over a lot of servers, a small table for a government initiative or a data of a startup. Learning SQL has a lot of professional advantages and some of them are;
- It will boost your professional career as a data science as it is the top sought skill in this job.
- It will give you a lot of understanding of the relational database.
- Even if it is not your work to query data, it would be a pleasure to write simple statements and query data out of the database when your teammate is on leave.
In this blog series, you will learn the basics of SQL and relational databases and you will even be able to do a coursera course on data science without watching its videos.
This blog aims to develop a practical knowledge of SQL so that you could work with a database directly. You will need Python and Jupyter notebooks to connect to the relational databases to access and analyze data to connect to the database and run SQL queries like a data scientist.
What is SQL?
SQL is a language used query (or get) data out of a database. SQL stands for “Structured English Query Language. It can be pronounced as S.Q.L or Sequel.
What is Data and a Database?
Data is a collection of facts in the form of words, numbers and even figures. It is a valuable asset of every business so every business tries to store it. Data is everywhere. Your banks, schools, hospitals, etc. store data about you, your name, address, cell phone number, etc. The storage of the data is as important as the data is. Data is stored in a database. A database is a repository of the data. Databases allow for viewing, modifying and querying (getting) data.
Data can be stored in many ways. The database is called a relational database when the data is stored in tabular form. Data is organized in rows and columns like in a spreadsheet in a relational database. As a database is a repository of the data, a set of software tools for managing data in a database is called a database management system or DBMS for short. The terms database, database server, and database system can be used interchangeably. If the database is a relational database then these tools are called relational database management systems or RDBMS. RDBMS is a set of software tools that control data like data access, data organization, and data storage. RDBMS is the backbone of many industries including banking, transportation, and health. Examples of RDBMS are, mySQL, Oracle Database and DB2 Warehouse on Cloud.
Five most commonly used Sql commands
There are five simple commands that are used by most of the data scientists while creating a table.
- create a table
- insert the data to populate the table,
- select the data from the table,
- update the data in the table,
- delete the data from the table.
In this first blog of the series “SQL for data science” you have learned what is SQL and why is it important for data science. Stay connected with us to learn daily through new blog about data science.