Data science has progressed to a point that it is applied to almost every industry that deals with information on a large scale. From predicting search results to innovation in healthcare and various other industries, there’s hardly any discipline where you won’t find the use of data science. And this is only the beginning. So if you’re done with your computer science course and are looking for job prospects, you might want to look into data science.
Data science is an interdisciplinary area that involves data analysis, data mining, visualisation etc. It uses various tools and techniques to find insights in massive data sets. It becomes increasingly important to have robust databases that can store endless amounts of data and classify them. Here’s where SQL finds its application.
SQL stands for Standard Query Language. It’s used to design relational databases (RDBMS). These are databases where all data points are related to each other. SQL is used to add, remove, change and retrieve data from relational databases. Several database platforms are modeled after SQL, Hadoop being one of them.
For an aspiring data scientist, getting into an sql certification course becomes indispensable. You will learn how RDBMS works, basic SQL commands like DDL (data definition commands) DQL (data query commands), DCL (data control commands) etc, Indexing, Null Value and others. Those CS students who need SQL homework help from experts, can rely upon professional programmers from AssignmentCore.
Reasons to learn SQL include its wide use in business intelligence tools, data testing and control are done through SQL, application in data science tools like Impala, Hadoop and high demand in many industries. It’s regularly applied to structured big data.
There are a few advantages of SQL that make it so necessary to learn for data scientists.
Easy to Learn - Virtually no coding knowledge is required to learn SQL. There is no need to learn complex codes as simple commands like SELECT, UPDATE are used to store and retrieve data. SQL comes with one of the simplest syntax and can be learnt by anyone.
Fast Processing - SQL can help store and retrieve massive amounts of data in relational databases. Simple commands like DDL, DQL, DCL, DML and TCL can be used to carry out data retrieval, classification and manipulation within seconds.
Multiple Views of Data - Different levels of users have different views of database systems. SQL can enable this with the CREATE VIEW command. A view is a subclassification of a database. Each view is modified so that every user can access only the points of data that are required for them.
Portable and standardized - SQL can be used with a variety of hardware with multiple operating systems. It’s also easily embedded and clubbed with other applications. Over the years, SQL has become a standardized platform with a large support base.
There are many functions of SQL that make it a favorite among industries and employers. It;s a great skill to arm yourself with to be a data scientist. Features of SQL like its ease of learning, access and wide application can give you a bang for your buck and time.
