Taking the time to learn SQL is an excellent choice for anyone who wants to quickly pull data or information from large databases. That’s because Structured Query Language (SQL) is used to manage and retrieve data from relational database management systems. After this information is pulled from a database, users can analyze it or use the data as part of a larger program.
If you’ve already gained a firm understanding of SQL, you may be ready to level up your skills. Below are some subject areas and tools that complement SQL, including programming languages like Python and fields of study like data science.
Python
Python is an object-oriented and open-source programming language that is incredibly versatile. This language can be used for a variety of purposes, from software development and data analysis to machine learning and automation.
Taking the time to learn Python would be particularly helpful for anyone who currently manages or analyzes large amounts of data, or plans to do so in the future. Python can also be used in tandem with SQL to access relational databases and put that information to use for analysis.
How to Learn Python
Because of its large community and open-sourced nature, many people teach themselves Python through self-study. A large number of online forums and resources, including Git, make this an incredibly viable option for learning this programming language.
Alternatively, you may prefer to learn Python by enrolling in a more structured course. Noble Desktop offers a variety of Python classes, each catered to a unique purpose. The school’s Python for Data Science Bootcamp prepares students with a basic understanding of coding with Python, then moves on to more challenging topics, such as structuring programs and analyzing/visualizing data. Noble’s Python Developer Certificate teaches students the skills needed to become a Python Developer, including using Django, Django REST, Git, and SQL.
Excel
If you’re learning SQL, you may already be an Excel wizard - but if not, it’s time to become one.
Excel is a fairly easy and intuitive program to learn, given that this spreadsheet software is largely structured in rows and columns (or cells). Individuals can simply type into each cell directly (no programming experience required!). Excel is a great language to learn if you plan on doing a lot of data analysis or want to take your analysis to the next level through visualization.
How to Learn Excel
Many people may have the opportunity to learn Excel when working in an office environment. This might occur when managing data on behalf of an organization, such as client phone numbers, or conducting basic analysis, such as finding the average of a group of numbers.
Individuals who prefer a more structured approach to learning may consider enrolling in a virtual or in-person course through Noble Desktop. Noble offers Excel courses at a variety of experience levels. Those just starting out learning Excel can enroll in the school’s Excel Level I class, which teaches the basics of doing calculations in the spreadsheet program. Individuals who want to build upon existing Excel knowledge can enroll in Excel Level II, Excel Level III, or Excel Bootcamp.
Tableau
Tableau is a useful tool for data visualization. As such, it’s an excellent skill to learn alongside SQL, as it enables users to create attractive displays of data. Tableau is available in several formats, including a free version, making it great for both beginners and professionals who would like to learn how to use this tool for work.
How to Learn Tableau
Noble Desktop offers a Tableau Bootcamp that teaches individuals how to turn data into attractive visualizations, including interactive maps, charts, and graphs. In this course, students also learn how to analyze, filter, and structure data for visualization, as well as use geographic data to make maps.
Data Science
Unlike Excel or Python, data science isn’t a tool in and of itself. Rather, data science is a field of study that uses data to identify patterns and gain insights. Within the field of data science, there are numerous different topics that individuals who want to get acquainted with the industry can learn. Generally speaking, however, those who would like to pursue roles as Data Analysts or Data Scientists will need to take the time to learn about statistical methods, data analysis, and visualization, among other things.
How to Learn Data Science
Individuals may choose to learn data science at a college or university. This may include taking courses on things like statistics, math, and programming (for example, Python). You may also choose to learn about some of these topics through self-directed learning, including reading books about data science or watching online educational videos on websites like YouTube.
Alternatively, individuals can learn about data science tools by enrolling in an online or in-person data science class. Noble Desktop offers a Data Science Certificate course that prepares individuals for job positions like Data Scientist and Data Analyst. In this class, students learn how to program with Python, create machine learning models, and use tools like Pandas and Sci-kit learn. This course also offers portfolio development and 1-on-1 mentorship opportunities, making it a great option for individuals looking to pursue a new career.
Wrap-Up
SQL is an incredibly helpful tool when it comes to working with data. Those who would like to take their data management and analysis skills to the next level can benefit from learning more about some of the other tools and fields of study listed above, including Python and Excel.
You may also be interested in attending Noble’s Data Analytics Certificate course, which includes many of the classes mentioned above all rolled into one course. This is a great option for those who want to learn about excel for data analytics, Tableau for data visualization, and Python for data science, automation, and machine learning (among other topics). This class also provides an SQL Bootcamp, making it a perfect refresher for those who may be a bit rusty on using the tool.