SQL Courses in NYC or Live Online

What is SQL?

SQL (Structured Query Language) is the most common programming language used in database management systems worldwide. Noble Desktop offers a course and an expert instructor to meet your needs, whether your goals are to understand the essentials of SQL and querying data or to create and maintain your own highly efficient database. SQL students learn how to turn complex datasets into actionable insights using techniques including writing queries to sort and filter data, using math functions and logic statements to target specific data, using data conversion functions to maximize report readability, and incorporating advanced functions to establish and maintain efficient database management procedures.

SQL is the most common programming language for interacting with databases, and as more companies move to the cloud, SQL skills are becoming more critical. SQL skills benefit both developers and business analysts: developers are often tasked with building or connecting databases, and analysts are often tasked with analyzing data from databases. From the business analyst side, SQL can increase your marketability and prepare you for various jobs, and it is relatively easy to learn. SQL, compared to Python, is easy to learn, and with a couple of short lessons, you'll be able to do most data analysis projects required of you.

When starting with SQL, you'll want to build a foundational understanding of relational databases and how they work. This knowledge underscores the importance of SQL in interacting with relational databases. Then you'll move into actually interacting with databases by writing SQL queries. For example, in just one line of SQL code, you can extract all rows in a table that meet certain criteria.

Once you have the basics down, you'll learn to work with grouping and mathematical functions, as well as joins, which allow you to connect multiple tables on a join key. After a couple of days of training, you'll be an SQL pro, and you'll see just how powerful a few lines of SQL code can be to perform common data analysis tasks.

Why Learn SQL?

Learn a high-demand career skill

As companies grow and technology becomes more central to their mission statements and day-to-day operations, their need for specialized employees who work with databases and servers expands. One of the advantages of learning SQL is that it is an in-demand career skill across virtually all industries, since more and more companies and organizations are realizing the importance of data management and storage projects. Large institutions are attempting to streamline their workflow and bureaucracies, which often relies on the work of SQL database administrators and architects, and once these systems are up and running, IT specialists will be needed to maintain, troubleshoot, and protect these databases. Plus, as remote work practices become more common, SQL training will be even more important for ensuring that workflow isn't interrupted as employees attempt to safely and effectively connect to servers and databases.

Lay the groundwork for future skills training

While some specialists work primarily with SQL, most professional computer scientists who work with the programming language complement it with other skills. Whether you are learning Python and Tableau to complement your data science training or you are learning ethical hacking to work on cybersecurity systems, learning SQL will help you lay the foundation for future skills training. SQL is also an ideal first programming language for new computer science students since it is versatile and accessible. After learning SQL, students will be prepared to easily pick up Python, which will allow them to work on everything from data science projects and database administration to back-end web development projects.

Learning SQL is also a versatile language because there are so many different flavors of SQL that you can pick up for specific programming functions. These different versions include PostgreSQL, MySQL, Microsoft SQL Server, and Oracle. While they all have different functionalities, learning one of the flavors will make additional SQL training significantly easier. Noble Desktop’s SQL Bootcamp emphasizes general-purpose programming with PostgreSQL, and their SQL Server Bootcamp emphasizes using Microsoft SQL Server.

What can you do with SQL?

Data science

SQL is one of the most important programming languages for data scientists and other data professionals. As more businesses and organizations begin to understand the advantages offered by having a robust team of data analysts, it is increasingly important that they can collect, organize, and store all the data they and their customers produce. SQL is an important part of this equation since it is the programming language that will most likely be used to handle the data storage process involved in elaborate database projects. Without a firm grip on SQL, database construction will be next to impossible for sufficiently large firms and organizations.

Data science and analytics won’t work if the databases drawn from are poorly managed, difficult to query, or otherwise full of bad data. SQL is an important programming language for ensuring that the data from which insights are drawn is clean, unbiased, and accurate. Without SQL training, it would be much harder for data science professionals to build the foundational databases upon which the rest of their work relies. Learning SQL is an important part of a robust data science curriculum since SQL is the language that most programmers use to insert and extract specific datasets into and out of their databases.

Server and database management

Despite how interconnected our daily lives are with our computers, a lot of obfuscation still separates the end-user experience from the systems that allow our devices to function. Much of this behind-the-scenes work is automated by databases and server infrastructure powered by various flavors of SQL, and it is the responsibility of trained professionals to ensure that systems run smoothly and remain invisible to end users. These complex databases need to be monitored and taken care of to ensure that they are functioning safely and efficiently.

SQL is also vital for connecting databases to one another, which is an essential part of building the server and data infrastructure that large companies rely upon to function smoothly. Even things as simple as password storage databases may rely on complex systems in organizations with a large enough number of employees. This means that the ability of employees to perform basic tasks and job functions is contingent on database systems working, which incentivizes companies to hire IT management professionals who can ensure that these systems remain functional under daily use.

This aspect of management also encompasses cybersecurity concerns. Managing a database means ensuring it is protected against unauthorized access, which is essential for any business or firm storing private information on its databases. This includes internal information such as bank records of employees used for direct deposit payments, and external information such as saved credit card information that customers use to expedite online shopping purchases.

What skills complement SQL training?

Python

The programming language most commonly used alongside SQL is Python. While SQL is used to build and query databases, Python is used to add functionalities to the databases and assist in querying, analyzing, and organizing data. Data science professionals will need to learn both programming languages since they are the two most commonly used tools for data analytics. Combining Python and SQL training will allow data experts to organize, analyze, query, and interpret data to make informed decisions about everything from network security optimization to potential future investment strategies. SQL, in particular, is useful for grouping and separating large datasets to make those databases cleaner, easier to use, and more responsive to specific queries and Python functions.

Students interested in Python training courses can consult Noble Desktop’s offerings or enroll in Noble’s Data Science Certificate program to learn more about the relationship between SQL and Python.

Tableau

Data is only useful if it can be effectively communicated to stakeholders who can make use of that data. While SQL and Python can be used for limited data visualization purposes, many professionals find that they need tools specifically designed with data visualization in mind. One of the most commonly used tools for this purpose is Tableau. Using Tableau, analysts can take raw data and the queries that they have drawn from that data to create charts, maps, and graphs to help them present this information to interested parties like project managers or investors. Tableau is a relatively accessible tool for new users to pick up and learn, and it has built-in functionality for working with SQL databases. Tableau is a great tool to learn if you are going to regularly need to present your data findings to other members of your team or firm, and the tool offers a robust collection of dashboard tools to help users create multiple different kinds of persuasive visualizations.

Students wanting to learn more about their options for Tableau classes should explore the offerings available through Noble Desktop.

Excel

An oft-overlooked part of working with databases is Microsoft Excel. While the program is usually considered an office program (understandable given how common it is in that setting), it is also one of the most foundational tools SQL developers have for manually or automatically constructing databases. Excel training will help lay the foundation for learning how to manipulate and query databases, and the program is often used as the backbone infrastructure for database design and development. While SQL professionals will need to learn tools beyond Excel to succeed in their careers, learning Excel is an important early development tool. Not only will learning Excel help SQL students better understand how databases work, but it will also help them streamline their workflow as they can more easily compile and organize their datasets. They can also utilize their SQL training to develop programs, applications, and queries that specifically use the tools offered with Excel.

To learn more about Noble Desktop’s Excel course offerings, please consider visiting their Excel topics page.

Who uses SQL?

Data scientists and analysts

SQL is commonly used in data science and data analytics contexts since it is one of the most important programming languages for building and querying databases. Data scientists use SQL to write programs that more efficiently query datasets, better scrape data from web traffic, and more effectively organize that data in databases where it becomes more accessible. Data analysts will use SQL querying programs to perform complicated, targeted searches of the massive databases produced by data scientists. They will then organize and interpret the data they have collected and queried, often using SQL, to make inferences and predictions based on the data they have accessed.

Data scientists and analysts are employed in virtually every industry as more and more firms are realizing the competitive advantage they gain by paying attention to the data consumers produce. This means that by learning SQL and Python, you will open the door to work in various industries. Data scientists and analysts can also find work outside of the commercial industry since government agencies, non-profit advocacy organizations, and even entertainment companies and sports franchises are beginning to utilize data analysis projects to improve their services. Regardless of where you are interested in working, there is a good chance that learning data science is a good way to find work in the field.

IT technicians and database administrators

SQL is also a vital part of the modern server and database infrastructure that allows modern information technology systems to function. You might not even think about it, but every time you enter a password into a computer system, you are accessing databases, connecting to servers, and requiring that multiple different interconnected computer systems verify your ability to access that system. Many employees of large companies do this dozens or hundreds of times a day, and at a large firm hiring hundreds or even thousands of employees, these systems could be working nonstop, and this is just for something as simple as recording passwords and verifying user credentials. Many computer systems are far more complex than this, requiring far more computing power and attention. Information systems analysts and other IT professionals are responsible for building, maintaining, and troubleshooting this infrastructure.

As with data science professionals, virtually every major industry employs IT technicians, particularly once firms and organizations reach a certain size. Oftentimes, they need to collect and manage data, not for interpretative purposes but just because they generate so much data that they need dedicated systems to store it all. For example, the healthcare industry generates so much vital data daily that a huge portion of the energy expended in the industry focuses on collecting, categorizing, and organizing that data so that it can be easily re-accessed by people who have the legal authority to access it. This requires elaborate and complicated computer systems designed to streamline a process that borders on the impossible without dedicated IT professionals.

Cybersecurity experts

Another important aspect of maintaining servers and databases is ensuring that they are protected from outside threats that seek to steal or corrupt data. In today’s digital economy, consumers constantly provide vital, identifying information (ranging from medical records to credit card information to social security numbers) to companies and organizations that store this information in various databases. Since there is so much vital, identifying information floating around in these spaces, companies are very concerned about ensuring that this data is protected (in part because many countries legally oblige them to protect consumer data). To keep this data safe from leaks and hackers, most large firms employ cybersecurity engineers and technicians who specialize in designing the systems and procedures that protect this infrastructure from attacks.

Cybersecurity experts will use programming languages like SQL to build the infrastructure in which sensitive data is stored and the programs and procedures that prevent unauthorized access to those databases. They will also work on the systems that compartmentalize different kinds of data so that certain information is stored in one database and is harder to access than database information that needs to be more publicly available. Many cybersecurity experts will also receive training on how to gain unauthorized access to protected systems to understand the kinds of threats that their servers and databases face (this is called ethical hacking). Like all careers that work with databases, cybersecurity professionals can find work in a wide variety of industries, particularly working for firms, organizations, and agencies that regularly deal with massive amounts of sensitive financial or personal information.

SQL careers

Since SQL is such an essential part of building information technology systems and infrastructure, there are a lot of different positions for students who have a deep understanding of the programming language. Whether you are looking for a career in data science, information technology, or cybersecurity, you should be able to find a position that leverages your SQL training into a high-paying career.

Students looking to work in data science can find work as data scientists or data analysts (and there are several specialized job titles for data analysts, like business analysts or investment analysts). While scientists and analysts both work with Python and SQL databases, they differ in what they do with the data. Data scientists are responsible for building the programs and applications that help collect, organize, and store consumer data. For example, if you are using a web traffic analysis program to monitor traffic on your website, that program was likely built by a data scientist. By contrast, data analysts use those applications to view, interpret, and visualize this data. So, in this example, when you are using a web traffic analysis program to monitor your website, you are doing data analysis.

Both of these roles are essential to the success of a modern business and are among the nation’s most in-demand career paths. The Bureau of Labor Statistics estimates that job openings for data scientists and analysts will grow by over 36% year over year for the next decade, significantly faster than the predicted 5% national average. In the US, data scientists earn an average annual salary of $125,000, and data analysts earn an average salary of $71,000 (though specialists are likely to earn more).

Information technology specialist jobs, including dedicated SQL developers, are expected to grow by approximately 9% over the next decade, nearly double the national average, according to the BLS. These professionals are responsible for building and maintaining server and database infrastructure for businesses and organizations. They must know how to utilize SQL code to build multi-layered relational databases and interconnected server networks that allow modern computer server farms to function. In addition, they may work as database administrators who oversee the maintenance, upkeep, and troubleshooting procedures that server networks regularly require. They may also need to work as de facto IT support specialists to fix small problems as they arise in complicated systems. In the US, the average annual salaries for SQL developers are around $81,000. Database administrators working at large companies earn an average annual salary of about $101,000.

Alongside data science careers, information security professions such as security engineers are among the fastest-growing career fields in the country. According to the BLS, jobs in cybersecurity are expected to grow about 35% year over year during the next decade, which is more than 700% faster than the national average. These professionals are responsible for building and maintaining the security systems that protect sensitive user information stored in a company’s servers or the cloud. This is a vital role because so much sensitive, identifying data is exchanged across servers and databases every day and there is so much money to be made by unscrupulous parties attempting to extract this data. Security engineers will need to know how to identify cyber-attacks and quickly build plans to respond to hostile outside action taken by hackers. They may also be expected to know how to breach security systems in an effort to identify weaknesses in a server system that need to be addressed. Information security engineers often need to be professionally certified to ensure that companies conform to legal requirements, but they are well compensated, earning an average salary of $100,000.