{"id":10887,"date":"2021-07-30T11:06:46","date_gmt":"2021-07-30T05:36:46","guid":{"rendered":"http:\/\/ivyproschool.com\/blog\/?p=10887"},"modified":"2021-07-30T11:52:52","modified_gmt":"2021-07-30T06:22:52","slug":"is-sql-really-the-backbone-of-the-data-industry","status":"publish","type":"post","link":"https:\/\/ivyproschool.com\/blog\/is-sql-really-the-backbone-of-the-data-industry\/","title":{"rendered":"Is SQL really the backbone of the Data Industry?"},"content":{"rendered":"

SQL<\/strong><\/em> (often pronounced as \u2018sequel\u2019) is the acronym for Structured Query Language<\/a><\/strong>. To pioneer in the field of data analytics, data science or data engineering, SQL becomes one of the most vital building blocks. When people start getting into data science, the biggest problem that they face is coding. <\/p>\n

While it is not mandatory to become a computer engineer to get into data science, coding is essential for data science and its applications. This is because we need to create computer language to make the system understand what we want. In such cases, where coding becomes a roadblock, SQL helps first-timers understand computer language and helps them know about its basics – Extraction, Transformation, Load. To do that, it is advised to start with SQL Queries. <\/p>\n

After that, they either learn Python or R to learn and apply Data Science<\/a>. In this blog, we want to focus on how SQL is helping and transforming the data industry. In addition to that, we will also focus on various SQL concepts that would help in getting started with a job in the data industry.<\/p>\n

Role of SQL in Data Industry<\/strong> : <\/p>\n

SQL is a programming language that is designed to manipulate data. The data that we manipulate is stored in a Relational Database Management Systems or RDBMS. SQL is used to insert, delete, update, modify data, etc. However, it is not possible to write full applications on SQL. Usually, data analysts, data scientists and data visualization analysts, use SQL to fetch the data from databases. After that, they undergo data wrangling and work on analyzing the data as per requirements. Most of the processes include extracting data from SQL servers and using it to create an automatic data extraction when they visualize it for their clients. This is often used in data visualization tools like Tableau and Microsoft Power BI. <\/p>\n

How SQL works : <\/strong><\/p>\n

SELECT * FROM table_name;
\nAlthough very simple, SQL is a very powerful language. It is written in simple English Query Language that is designed to extract information from databases. The syntax (code) for that goes like this: <\/p>\n

Here SELECT * refers to that we have to select all the columns and FROM table_name refers to that table_name.<\/p>\n

A database is an organized collection of structured data. Database Management Systems or DBMS is software for storing and retrieving data in a simple organized way. There are many SQL servers available, so it is important to be familiar with one of them as a data scientist. The server depends on the company you are working for, in addition, the syntax may change a little bit based on the DBMS you are using.<\/p>\n

SQL is a bridge between a data professional and a database. Some popular SQL servers are :<\/p>\n

Microsoft SQL Server
\nMySQL
\nIBM DB2 Oracle
\nApache Open Office Base
\nSybase ASE
\nSQLite
\nPostgreSQL<\/p>\n

Demand for SQL :<\/strong><\/p>\n

If you want to get a job in data, you must focus on the skills required by the job posters. SQL is the most in-demand technical skill for data jobs. (Data: Indeed.com, 1\/29\/2021). It turns out that if you are looking to start fresh in the field of the data industry, then learning SQL is even more critical. SQL is used by Google, Amazon, Apple, Airbnb, Netflix, Uber, Wells Fargo, Shopify, WordPress, and hundreds of thousands of other companies. In short, it is everywhere.<\/p>\n

What jobs can be secured with the help of SQL in the Data Industry?<\/strong><\/p>\n

1. Business Analyst : <\/strong><\/p>\n

Business Analysts usually perform what is known as a gap analysis to identify the necessary steps to get from a current state to a desired future state. SQL helps to find the gaps in data such as dates or number sequences. <\/p>\n

2. Data Scientist :<\/strong><\/p>\n

A Data Scientist is someone who is an analytical expert and utilizes their skills in both business, technology, and social science to find trends and manage data at a massive scale. For this role, there should be a combination of many different languages and concepts along with SQL to have a strong ground in some of the fundamental tools. For example SQL, R or Python, Hadoop, Excel, D3, and Java\/C\/C++, and the theoretical basics like statistics, data warehousing principles, accounting, general numeracy.<\/p>\n

3. Database Administrator : <\/strong><\/p>\n

A Database Administrator (DBA) manages the database software to store, organize, and access data successfully. DBAs usually oversee a team of SQL developers and need to be skilled with computer programming, software engineering, and data architecture. A SQL Server DBA only writes code on specific occasions, however, play an essential role in optimizing SQL queries and oversee backups, audits, and data replication. This is done to ensure that SQL databases remain accessible, secure, and stable.<\/p>\n

4. Data Visualization Analyst : <\/strong><\/p>\n

A Data Visualization Analyst is someone who creates visuals to narrate a story about data and helps to understand the future of business. They use SQL to extract data from databases, clean the data and then visualize them for the stakeholders. <\/p>\n

If you are someone who wants to learn SQL and prepare for SQL interviews, then Ivy Professional School<\/a><\/strong> is the perfect place to learn SQL and then transform your career in the field of data. We have various certifications that will not only enhance your technical knowledge but also expose you to real-world problems that deal with data. <\/p>\n","protected":false},"excerpt":{"rendered":"

SQL (often pronounced as \u2018sequel\u2019) is the acronym for Structured Query Language. To pioneer in the field of data analytics, data science or data engineering, SQL becomes one of the most vital building blocks. When people start getting into data science, the biggest problem that they face is coding. While it is not mandatory to become a computer engineer to get into data science, coding is essential for data science and its applications. This is because we need to create computer language to make the system understand what we want. In such cases, where coding becomes a roadblock, SQL helps first-timers understand computer language and helps them know about its basics – Extraction, Transformation, Load. To do that, it is advised to start with SQL Queries. After that, they either learn Python or R to learn and apply Data Science. In this blog, we want to focus on how SQL is helping and transforming the data industry. In addition to that, we will also focus on various SQL concepts that would help in getting started with a job in the data industry. Role of SQL in Data Industry : SQL is a programming language that is designed to manipulate data. 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