Business Analysts spend a lot of time pouring over spreadsheets and putting together slide presentations. But these roles are evolving as more complex data streams and advanced analysis, like data analytics, become more common.

That’s why it’s helpful to have some background programming knowledge. As a Business Analyst, strong programming skills can help you leverage powerful tools that streamline day-to-day tasks and set yourself apart in a competitive job market.

Ahead, we’ll explore five programming languages that you might want to consider learning if you want to be a Business Analyst.

1. SQL

Structured Query Language (SQL) is a programming language used to manage relational databases. And since Business Analysts spend so much time searching through databases, SQL should be the first addition to your toolkit.

With SQL, you can easily query and extract data from databases to analyze in a spreadsheet program or with one of the other programming languages noted below. Plus, its simplicity and easy-to-understand syntax make it relatively easy to learn.

2. Python

You also might want to consider learning Python. Business analytics involves working with increasingly larger datasets that are beyond the capabilities of traditional spreadsheet programs, and Python makes it easier to process and analyze big data.

It also has statistical modeling capabilities that allow Business Analysts to make much more sophisticated demand and price forecasts. Python even makes data collection faster by easily integrating with SQL databases and automating tasks like web scraping — and its powerful machine learning libraries, like scikit-learn and TensorFlow, help detect trends and patterns from big data. And libraries like seaborn help communicate data insights and results with data visualization tools.

3. R

Like Python, R is an excellent tool for working with big data, and it can also be used for machine learning and complex statistical analysis. It also offers thousands of libraries that give Business Analysts access to tools for time-series analysis, forecasting, and advanced data visualization.

In fact, one of R’s biggest advantages is its sophisticated data visualization tools, which allow you to easily create interactive graphs for websites, report-ready panels of multiple graphs with comments, or customized PDFs.

4. VBA

Not every Business Analyst needs to learn VBA (Visual Basic for Applications), but it can be helpful. Imagine how many monthly, weekly, or daily reports you might need to prepare as a Business Analyst. Sure, they all have different information, but you can save yourself a lot of time with VBA when they’re formatted in the same way.

Business Analysts use VBA to generate custom summary tables in Excel, periodic reports in Word, or slide decks in PowerPoint. And since everything in Microsoft Office is integrated, it’s easy to combine everything — for example, creating a monthly report based on data in Excel, then using the contents of that report to automatically generate slides with bullet points in PowerPoint. Business Analysts who know VBA can save themselves a lot of time in their daily tasks.

5. The language of your team

While Business Analysts aren’t expected to get into software development, it does help to learn a bit about the language your company or team uses every day.

Are you working for a start-up game developer? Learn the basics of C++. Applying to an Android app developer? Pick up some Go or Kotlin. If you already know one or more of the programming languages above, it’ll be easier for you to pick up on some of the other languages used in software development.

When you can grasp the fundamentals of the code your team uses, it’s easier to understand the impact of business decisions on the technical side of things. It also helps build a better relationship with your colleagues and teammates when you’re willing to “speak” their language — literally.

Order matters

When it comes to learning programming languages for Business Analysts, some languages are more in-demand than others.

SQL is at the top of the list. In fact, most hiring managers will rank your SQL knowledge higher than any other language.

After mastering SQL, we recommend learning Python or R. These languages will round out your Business Analyst technical skills by allowing you to do more in-depth statistical analysis and generate sophisticated data visualizations.

Finally, learning VBA can potentially be a great way to work more efficiently with creating spreadsheet summaries, reports, and other administrative tasks if your team uses the Microsoft suite.

Learn the programming skills you need to become a Business Analyst

Ready to learn the skills you’ll need to become a Business Analyst? Pick any of the courses below to get started:

Then, once you’ve mastered the basics, check out our Analyze Business Data With SQL and Analyze Financial Data With Python skill paths to learn how to analyze large datasets and communicate your findings. You also may want to consider taking a course on data visualization.

Sign up now to get started. And if you need a little help while you’re going through your courses, reach out to our community in the Codecademy Forums or on Discord.

For Business Courses & Tutorials | Codecademy

Programming languages serve many different areas of a business that include maintaining operational excellence, improving customer-facing experiences, and evaluating business performance. Keep up with the latest technical knowledge and skills to transform your business.

If you’re looking to break into software development, you might have come across the scrum framework.

Never heard of it? It’s essentially a method for teams to work together to update and improve upon software. It’s a process that’s closely related to Agile software development, an iterative approach to completing projects that’s very popular in the tech world. In a scrum project, team members must communicate to prioritize tasks, keep track of progress, and sum up what was done and what was learned at the end of an effort.

Teams that use the scrum framework have a Scrum Master who is responsible for assembling a team of developers and making sure that the software they’re working on actually works. A Scrum Master’s role is a combination of a coach, technical expert, and manager. They ensure clear communication within a team of developers or programmers, organize their focus on development tasks, contribute to tech development where needed, and take responsibility to deliver the team’s work on deadlines.

While it’s common for salaries to vary in any industry, a Scrum Master’s pay is particularly mixed. That’s because there’s a broad range of people (with varying experience levels) who can take on the role of Scrum Master on any given team. For example, Developers, Business Analysts, and Senior Project Managers can all be Scrum Masters according to Indeed; and average annual salaries for these jobs range from $46,582 to $106,121.

With all that in mind, let’s break down the salary range you might expect from a Scrum Master role, and what factors can affect it.

Range of roles and compensation

Because of the varied nature of Scrum Master positions, determining what their compensation is will also require breakdowns of the various titles that can be considered Scrum Masters. Here are just a few that will help give you a better idea.

Software Engineers

Software Engineers are a key part of a scrum team, and can also be Scrum Masters. These engineers, or developers, should know key languages such as HTML, PHP, SQL, and Python. Even if the Scrum Master comes from a discipline other than software engineering, they need that programming knowledge to communicate effectively with the working team. Software Engineer compensation can range from $38,000 for the most junior professional to about $172,000 for the most senior and experienced software engineer.

Project Managers

Indeed gives a few different figures for Project Managers:

However, a Project Manager’s title can be very general and doesn’t always connote the same thing as Scrum Master. A Scrum Master is different from a Project Manager because the Scrum Master’s sole focus is on the success of the team working on the project or product in question, while the Project Manager is also responsible for budgeting time and resources, among other issues.

Agile Coaches or Managers

Agile Coaches, also referred to as Agile Managers, focus on that type of software development approach. Glassdoor estimates the average salary of an Agile Manager at $115,277. An Agile Manager must have more specialized knowledge than a Project or Program Manager, and can even take an exam to be certified as an Agile Manager.

Similar Scrum Master roles that include Agile specialties have a much higher ceiling for pay. According to ZipRecruiter, a Safe Agile Coach can earn $152,236, while Glassdoor estimates that an Agile Scrum Coach can earn $111,874.

Qualifications

Naturally, your education and experience will affect your earning power in a Scrum Master role. For some people, that begins with a bachelor’s degree in a relevant subject, such as information technology (IT), computer science, or business administration. That said, more and more tech companies are moving away from requiring specialized college degrees. There are many paths to tech careers that involve flexible education, and you can seek out online courses and certifications that will get you up to speed. If you want to learn to code, check out our course catalog for a range of options.

Of course, to become a Scrum Master, your education should be supplemented with work experience, particularly in using Agile or as an Agile Developer. You should also earn a certification as a Scrum Master. A preparation course for this certification lasts just a few days.

While certification is not an absolute must-have to work as a Scrum Master, it could help increase your salary prospects. A 2019 survey by Age of Product, an Agile software development company, found that 44% of Scrum Masters with certification earn over $100,000, while only 18% of those without a certification earn over $100,000.

Since the role of the Scrum Master is flexible and the definition varies, succeeding as a Scrum Master requires certain soft skills. To be a Scrum Master, you should be an adept communicator and comfortable interacting one-on-one and in groups. A Scrum Master should also be a motivator and administrator for the scrum team.

A wide Scrum Master salary range

Due to variation in experience, role, and levels of qualifications in Scrum Master roles, different sources and surveys show Scrum Master salary ranges and averages that are less consistent than those of other programming, computing, and technology jobs.

So while it may be difficult to say exactly what you’ll make in this industry, here are different sources’ ranges for what the salary you might expect to see:

• Glassdoor: $108,907
• PayScale.com: $90,312
• Salary.com: Entry-level Scrum Master averages $82,215, with a range of $63,627 to $107,825
• Salary.com: Scrum Master II averages $98,490, with a range of $76,485 to $125,879
• Salary.com: Scrum Master III averages $118,896, with a range of $90,409 to $143,747
• Salary.com: Scrum Master with Agile project manager experience averages $141,561, with a range of $127,544 to $156,906
• ZipRecruiter: average of $114,991, with a range of $52,500 to $157,000

Geographic differences

As you might expect, salaries can vary depending on where you live. Four of the top 10 cities in terms of average salary for Scrum Masters, according to ZipRecruiter, are in California: San Jose, Oakland, Hayward, and Vallejo. The top 10 is rounded out by a few other cities:

• Santa Barbara, California
• Hoboken, New Jersey
• Jackson, Wyoming
• Barnstable Town, Massachusetts
• Seattle, Washington.

These average annual salaries range from $132,454 to $138,361.

A role with great potential

What makes a Scrum Master career path so unique is that the required experience — and thus salary — is flexible according to what you bring to the role and what you hope to get out of it.

Whether you’re interested in being an Agile Coach or Software Engineer, our programming courses can help you get started. Familiarize yourself with PHP, SQL, and Python to establish your foundation to become a Scrum Master, and take a look at our career paths to help figure out what other skills you need to succeed.

You might not immediately associate business analysis with the tech world, but Business Analysts actually play key roles in the Information Technology (IT) industry. Because they use data to help guide businesses in improving their processes, products, and services, Business Analysts can be crucial to companies and their growth.

Unlike Data Analysts, who work more closely with the data itself, Business Analysts use data to help address business needs and make strategic decisions. If you’re good at problem-solving, analytical thinking, and communication, this job might be a great fit for you.

Ahead, we’ll take a closer look at what a Business Analyst does, and how you can get started in this career path.

What is the role of a Business Analyst?

A Business Analyst helps companies define their needs and make better decisions based on past and current business data. Let’s break down what that actually means in practice.

How Business Analysts help define business needs

When we say “business needs,” we’re referring to how the company can meet its financial, strategic, and product goals, both short-term and long-term. Typically, it’s the company’s senior leadership, board of directors, investors, and shareholders who have the final say in the company’s direction and strategy. Examples might include goals such as:

• Having a commercially viable product that does x, y, and z by a certain date
• Achieving a certain amount of market share by a certain date
• Improving sales volume, revenue, or profit within a certain timeframe
• Ensuring that products and business practices stick with a certain mission or set of values such as sustainability or fair trade

Business Analysts take the company’s strategy and goals into account and use data to help the company figure out what it needs to do to meet those goals.

How Business Analysts work with business data

The term “business data” refers to data generated by the business itself (internal data), as well as relevant data from customers and competitors (external data).

Examples of internal data include:

• Customer relationship management (CRM) records
• Direct feedback from customer surveys
• Point-of-sale (POS) and other transactional data
• Internal documents
• Device sensors

Examples of external data include:

• Indirect feedback from people who refer to the company in blogs or on social media
• Competitor data
• Stock indices and other economic indicators
• Third-party data from business intelligence companies

Companies have more access to internal and external data than ever before. But while it may seem like a good idea to work with as much data as possible, remember that it takes time to filter and prepare data before it’s usable. And a lot of external data isn’t free. It’s up to Business Analysts to consider which data sources are the most relevant and cost-effective.

How Business Analysts help make better decisions

By “better decisions,” we mean that business analysts bring value by working with complex datasets to reach conclusions that wouldn’t be obvious just by skimming through the data. At the same time, good Business Analysts know how to interpret the data into a clear action plan. Essentially, they act as a liaison between advanced tech and an organization’s stakeholders. A couple of examples of a Business Analyst’s conclusions might be:

• By implementing the new back-end database structure, your website’s page load times will be 50% faster than your biggest competitor’s, which will help you reach website traffic goals.
• If your next software release includes these new features and is priced 10% lower, we predict that the company will meet its market share goals while still staying above its profit goals.

Business Analysts are skilled communicators

Business Analysts, similar to Data Scientists, occupy a bit of a bridge role. On the one hand, the bulk of a Business Analyst’s role is technical — they need to understand how to process and analyze large datasets and the costs and benefits of different technologies and solutions. Business Analysts also work closely with technical and IT teams to understand the resource and technology limitations of the company.

But on the other hand, Business Analysts must also understand how their recommendations will impact the business as a whole, especially the bottom line. They need to effectively communicate with the company’s stakeholders and senior management by presenting how changes will impact the company’s goals.

In other words, Business Analysts help close the gap between business management and the company’s technical systems.

In addition to typical data analysis tools like Microsoft Excel and Google Analytics, Business Analysts also use a variety of programming languages to make their lives easier. Here are the three most important ones:

SQL

Business Analysts work extensively with databases, which means that Structured Query Language (SQL) is a must-know programming language. While some datasets can still be stored and analyzed within spreadsheet programs, the rise of big data and data protection have made relational databases a far better solution. While most Business Analysts don’t need to be experts in SQL to design and create new database systems, it certainly helps to understand the basics of searching for and extracting data.

VBA

The most successful Business Analysts know how to program in Visual Basics for Applications (VBA). Unlike Visual Basic, which programmers use to create stand-alone applications, VBA is used exclusively within Microsoft Office applications like Excel and PowerPoint. Business Analysts use VBA to quickly generate customized summary tables, stunning graphs and visualizations, and detailed slide presentations in seconds. In other words, VBA saves Business Analysts a lot of time, so they can focus less on creating and formatting documents and more on working with the data.

Python

There’s a lot of debate on whether Business Analysts should learn Python, but it makes sense to have at least a basic understanding of Python. Why? Because business analytics involves a lot of repetitive, complex tasks with large datasets. And when datasets are too big for a spreadsheet program to handle, Python can save a lot of time and frustration. Not only can Python work with large datasets, but Business Analysts can also use Python to perform and even automate key tasks such as web scraping and data merging.

Secondly, more and more companies expect Business Analysts to cover multiple roles, including data analysis. By learning Python, you’ll open up more doors to Business Analyst job positions.

Start your career as a Business Analyst

Now that you know what a Business Analyst does, you might be wondering how to get started. We recommend beginning with an online course in programming, especially in SQL or Python, which are both skills a Business Analyst should have. Once you know the fundamentals, consider learning more advanced skills, such as analyzing business data with SQL or financial data with Python. And if you’re not sure where to go next, our developer career paths will help you decide which skills to learn as you start your next chapter.

Data is changing the game for the professional sports industry, giving athletes new ways to track biometrics and optimize their performance. Competitive esports is no different: There’s high demand for Data Scientists who can interpret all of the data coming out of video games and help coaching staff make informed decisions.

Evil Geniuses is one of the oldest competitive esports gaming organizations, with rosters of pros in games like League of Legends, Dota 2, and Counter-Strike. Even if you’re familiar with esports, you might not know that the organization employs as many Data Scientists and Engineers as it does Coaches — a fun detail that CEO Nicole LaPointe Jameson recently shared with The Washington Post.

Ivan Sheng is one of the Data Scientists at Evil Geniuses, where he focuses on the games League of Legends and Counter-Strike. “I take data from video games and I create predictions and business use cases in order to have an edge over our competition,” Ivan explains. (Ivan is also a Codecademy contributor and worked on our recent course Introduction to Big Data with PySpark.)

Here’s how Ivan uses Python and SQL to help esports pros strategize and succeed, plus the programming languages you need to know to become a Data Scientist in competitive esports.

What got me interested in the job

“I’ve actually known about Evil Geniuses since I was in middle school. I had a friend who was really into this one game called StarCraft: Brood War. We started watching clips on YouTube and this concept out of South Korea called ‘esports’ popped up. I got addicted to it, and one of my favorite players was signed with Evil Geniuses.

My introduction to data was kind of interesting. As a junior in college, you’re kind of desperate for internships, so I just shot my resume everywhere. One day I got a call from an unknown number, and it was apparently an interview for a data analyst internship at a marketing agency that I forgot that I applied to. Going from a mechanical engineering major into a marketing agency where everyone’s super young and sociable was a culture shock for me. I kind of fell in love with it.

I had two really great mentors that I still keep in touch with today — one who is also a Data Scientist, and taught me pretty much everything I know about data. Once I entered the job market, I had a manager who gave me my foundations in Python and natural language processing, and then that’s pretty much where everything kind of just skyrocketed.”

How I got in the door

“I did some contract work for Evil Geniuses prior to actually going full-time with them. I would do some data science work, write about it, and submit it to one of our ESPN-like websites called Factor.

That eventually evolved into me doing some software development work; Monte Carlo simulations and things like that. And then that blossomed into a conversation of, ‘I’m graduating and I’m going to start interviewing.’ Our Chief Innovation Officer basically said, ‘Hey, do you want to come over here?’ I was like, ‘Yeah, I’ll entertain it. Of course!’

It’s super cool to work with products or companies that you’re familiar with, because you have some personal stake in it. I came to Evil Geniuses from Disney Streaming, where I got to see the birth of Disney+ and all that fun stuff. I had the same good feelings coming over to Evil Geniuses, because I’ve known about this since I was a kid as well.”

What I actually do every day

“I am basically sitting down in Python, just coding up lots of different things. As for what I’m coding, it depends on the day and the task. We’re a bit of a small company, so I’ve done work all the way from creating automated data pipelines to creating models in the deterministic and non deterministic side of things. On our team, we’re kind of split between gaming and marketing: I’m working with gaming data like 60% of the time, and then 40% on the business side of things.

I’ve also done some software development work in terms of flagging interesting in-game events to kind of let our coaches know like, This thing happened at this specific time point in the game. Maybe you guys could check it out? Maybe this was a big turning point in the game? I don’t directly talk to our pros. I usually talk to the coaches or an analyst who works directly with the team — those people are the main stakeholders.

Now I’m following more esports, because I have to learn about all these different games. Like, I never really got that into Counter-Strike before, but that’s my biggest responsibility now. So I’ve been watching that endlessly.”

Here’s what you need to get started

If you’re interested in becoming a Data Scientist, it’s a good idea to learn Python. Ivan strongly recommends that you learn SQL too, because it’s frequently used in Data Science careers. “I think it’s criminal to underrate SQL as a language,” Ivan says.

Inspired to start your journey to becoming a Data Scientist? Here are the courses and paths that will help you pick up the skills you need for the field:

• Data Scientist: Analytics Specialist: In this Career Path, you’ll learn how to use SQL and Python to answer big questions with data. There’s even a portfolio project where you’ll be analyzing streaming data from players on Twitch.
• Analyze data with SQL: This beginner-friendly SQL path will have you querying data right away, plus includes prep for technical interviews.
• Analyze data with Python: With Python, you can present data in compelling visuals like graphs and charts. In this course, you’ll also learn how to use common Python libraries like NumPy, Matplotlib, and Pandas.
• Fundamental Math for Data Science: “Having a strong statistics foundation is just as important as your programming capabilities,” Ivan says. Need to brush up on your math? This skill path will review key statistics, algebra, and calculus concepts and help you build a foundation for more technical work.

There’s more to being a successful Data Scientist than just programming and software engineering: Communication skills are a must, because you’ll often have to translate data and findings for people who aren’t data-oriented, Ivan says.  

Once you reach a stage where you’re applying to jobs and landing technical interviews, don’t skimp on practice, Ivan says. “With a lot of these tests, especially the SQL ones, there’s a pattern that you can figure out — because they always test very similar concepts,” he says. Our skill path Data Analyst Interview Prep is a great way to get familiar with common interview questions and practice formulating answers.

Ivan’s other tip for slaying a technical interview or live programming test? “Be very open and communicative with your recruiter,” he says. “They’re there for you and want to see you succeed, so it’s important to have a back-and-forth with them if you’re ever confused.”

Data Science Courses & Tutorials | Codecademy

Data Scientists try to make sense of the data that’s all around us. Learning Data Science can help you make informed decisions, create beautiful visualizations, and even try to predict future events through Machine Learning. If you’re curious about what you can learn about the world using the data p…