Is SQL Important For Learning Data Science?

If you are one of those who is unsure in answering is SQL important for learning data science, this article is just for you, illustrating what is SQL, the importance of learning SQL and much more than that.

• Introduction  
• What is SQL? 
• Importance of SQL in Data Science
• Skills Required for Data Science
• Why Global Tech Council for Data Science?
•  Conclusion

 

Introduction 

Is SQL needed in the field of data science domain? The short answer to this question is, of course, yes! In fact, Data Science (DS) is strongly interlinked with SQL, and if you want to pursue a career in this domain, learning SQL is mandatory.

There are various data science certification courses where individuals can grasp this excellent opportunity to get certified in data sciences. Certified Data Science Developer certification aims to provide individuals with a competitive edge for superior employment opportunities.

As alphabets are the foundation of English, in the same way, we can say that SQL is the foundation of DS.

What is SQL? 

 

Before answering this, let’s revise the definition of data science.

Data Science is the field of computer science that deals with data, including the collection of data, storing, and analyzing data to generate insights that are helpful for businesses and organizations.

SQL is the Structured Query Language for all relational databases. For storing, retrieving, and updating data from databases, this language is used. Data Scientists use SQL to extract information that is stored in databases with the help of SQL commands, making this language essential for Data Science.

SQL is the language that is used everywhere; therefore, it is high in demand as many top companies like Facebook, Google, Amazon uses SQL to query data and perform analysis. Though there are many other languages, the scope of SQL is never going to end.

 

Importance of SQL in Data Science

SQL is the choice of almost all Data Science developers making it universal and high-demand language. In fact, many interview question of Data science starts with the basic concepts of SQL.

To handle structured data, stored in relational databases, Data Scientists/ Engineers need an in-depth knowledge of SQL. So, if one wants to play with data stored in the database, there is no other way than learning structured query language.

• If data stored in the database need to be altered or manipulated in some way, SQL is the key solution. For table creation and test environment, this language is used as a standard tool.

 

• Is it thinkable to experiment on data without knowing SQL? What if a data team need to perform data analysis to generate insights? The answer to all is to have a profound knowledge of this language to perform on relational databases.

 

• As the field of data science is very vast, learning big data, big data analytics, and data analysis need the sound knowledge of SQL.

 

• For analyzing data stored in Relational databases like Oracle, MySQL, Microsoft SQL, hands-on SQL is a must-have skill. Big data tools and Cloud tools also require the streamed knowledge of this language.

 

• Before modeling data, the Data Science team has the responsibility of cleaning, modifying (if needed), and validating data, which is impossible without SQL.

 

 

SQL Skills Required for Data Science

 

To become proficient in the data science domain, one needs to develop programming skills along with profound knowledge of statistics, data visualization, big data, set of toolboxes, exploratory data analysis, and much more than that. But understanding SQL is the core fundamental to become a good data scientist.

• Understanding and writing simple and complex SQL-based queries.

 

• Ability to perform SQL implementations like MS SQL Server and more.

 

• Sound knowledge of Relational Database Management System(RDBMS) for accessing, retrieving, and manipulating data from SQL.

 

• Knowledge of advanced SQL to perform aggregation, nested queries, table expressions, and more.

 

• Knowing how to perform query optimization to determine the most effective ways to access data.

 

Writing SQL commands and subqueries, creating tables, performing Joins, knowing SQL indexing, are the part of SQL skills required to become a data engineer or a data scientist.

 

Why Global Tech Council?

 

Global Tech Council is one of the best platforms that offer data science certification to make you become a data science developer like a pro. The data science training focuses on analyzing the fundamentals of data science for beginners and intermediates, covering all the advanced topics like neural networks, R programming, and machine learning to make you stand out from the rest of the crowd.

 

Conclusion

 

Data Science is an emerging field that has infinite job opportunities. Building a career in this domain opens various career openings like data science engineers, data scientists, BI analysts, data architects, and data analysts. Data Science is a high-ranking profession but professionals, short in demand. Scoring data science certification will give your career a head new start.

‘SQL can be termed as an interpreter between the data science team and database,’ and this statement makes clear how crucial it is to learn SQL.  Learning SQL paired with critical thinking ability will help you gain the fat packages that you are wondering for.

 

Are you looking for the best data science programs online to become a Data Science Developer? For more updates and best data science certification, check out the Global Tech Council.