image of a mountain peak against a skyline of blue and white fluffy clouds and the Lighthouse Labs Logo and the words Lighthouse Labs

There's a famous saying: If you are not paying for a product, then you are the product. Though this might sound a bit bleak, this phrase perfectly captures the freemium model many companies have adopted in this digital age. In the first quarter of 2023, Meta, the parent company of Facebook, declared total revenues of about $28.6bn without charging the core users of its products a single cent. Companies are forced to find creative ways to monetize their services in a world where we expect entertainment, convenience and functionality from our digital services at little to no cost. They must learn to find that delicate balance between generating revenue for their shareholders and ensuring their services remain accessible to their users. How do they achieve this? Data! Data!! Data!!!

However, the use of data in achieving business goals is not exclusive to companies that operate the freemium model. Data has become the gold of the digital age, and many companies leverage it to achieve their business objectives. Food and grocery delivery apps like Instacart and Skipthedishes use data to match you with vendors and delivery persons, to estimate delivery times and predict future purchases. Ride-hailing apps like Uber do the same. They use it to predict routes and model future pricing estimates, and navigation apps use data to help determine your routes and predict future traffic trends. The list goes on. In this digital age, Data is king.

It isn’t merely enough to just collect and store data. Companies need the services of skilled professionals to collect, sort, analyze and interpret this information before it can be leveraged appropriately to drive business objectives.

Enter Stage : Data Analyst

In simple terms, a Data Analyst is someone who, through self-learning or formal education, has acquired the skills and knowledge to collect, sort, analyze and interpret large datasets, often to uncover insights that organizations can use to drive their business objectives.

How To Become A Data Analyst

  1. Get a Data Analytics Education
  2. Acquire core technical skills
  3. Get an Entry-Level Data Analyst job

Getting A Data Analytics Education

The first step to starting a new career in any field is to acquire the relevant foundational knowledge required for the job. As a data analyst, you will need to master the skills of Data acquisition, cleaning, interpretation and visualization. You will require data management skills and languages such as SQL, Python, R, and Javascript to manipulate and interpret the data in your databases. There are three main paths to acquiring this education:

  • Self-Study: The internet is a treasure trove of information. Suppose you have the time, discipline and commitment to dedicate yourself to a strict learning schedule. In that case, many online resources could help you acquire the foundational technical skills required to launch a career as a Data Analyst. While this is the least costly option, it involves focus and commitment. Unfortunately, it is easy to get overwhelmed by the number of available resources. Except you are using this option to advance along a similar Data-centric career path, you may have to consider getting additional industry-relevant certification. While employers no longer have a strict college degree rule, you do have to show some formal accreditation. You also miss out on developing many soft skills employers are looking for, which come from a structured and collaborative learning environment. Pros: Cheapest option. Cons: Can be overwhelming. No accredited education diploma or certificate. Have to pass certifications on your own. No soft skills training.

  • College Degree: As the Data Analysis field gains popularity, it is now possible to find college degrees structured specifically around Data Analysis/Science. However, even if you don't take a specialized degree program, many employers will take a bachelor's degree in a related field, like statistics and computer science. Manipulating data is the core function of the Data Analyst. A computer science degree that teaches you Python and Databases such as SQL and Advanced Excel will provide a solid foundation for launching a career as a Data Analyst. However, this route requires significant time and financial commitment. This is a good option for young people who plan to go to college anyway but less so for mid-career professionals looking to make a quick shift to Data Analysis. Pros: Broad curriculum will provide a strong foundation for any tech career. Cons: Expensive. Too time consuming. Depending on your degree you might need to acquire certifications or attend a short-duration course like a bootcamp to get that specialization.

  • Bootcamp: This is the quickest path to getting into the field as a young person just starting their working life and for mid-career professionals looking to make a switch. A Data Bootcamp at Lighthouse Labs will take you from novice to job and career ready in as little as eight weeks. The comprehensive curriculum and quick pace of learning might be challenging for some. Still, this option is the most time-efficient, with a specialized curriculum and a diploma/certificate at the end of your study. Pros: Quickest option, specialized diploma, industry-aligned curriculum, network and community building, soft-skills enhancement. Cons: Intense pace, more expensive than self-study.

Acquire Core Technical Skills and Build a Portfolio

Once you've acquired the foundational skills to begin your career, it is time to boost your chops as a Data Analyst. This will require knowledge and mastery of industry-relevant tools and software. You will need to become familiar with the tools of the industry, such as Microsoft Excel, Matlab, and IBM SPSS, which are used to analyze and gain insights from large data sets.

You should also be competent in using data visualization tools such as Tableau, QlikView, and Power BI. This will help you translate those patterns and trends into user-friendly presentations.

It would help if you also began building a portfolio of work, taking on personal projects and problems that highlight the essential skills you've acquired.

Finally, you will need to develop or enhance the soft skills that are key to success within the field. Presentation, communication, collaboration, teamwork and problem-solving are all crucial to a Data Analyst's work.

Read our feature: Data Analyst Interview: Top Questions.

Data Analyst Career Path

You’ve done it; you acquired the education, beefed up the technical skills required for success on the job, and searched for and landed your first Data Analyst job. Congratulations. Enjoy your first few years of learning as much as possible because soon, it will be time to start thinking about advancing your career beyond the entry-level stage.

So what does the career path of a data analyst look like?

The demand for data professionals is high because their skills are used across all industries. This means that the career progression for a Data Analyst is not precisely linear. It depends on where your interests lie. As a Data Analyst, you could take a job in Finance, Healthcare, Insurance, Digital Marketing and many more. This will set the stage for possible specialization down the line if you’re not interested in advancing to a management position.

You can also decide to break out of the Data Analyst function to become a Data Scientist. We will touch on each of these paths below.

Entry Level

As an entry-level data professional, you will be hired as a junior analyst, junior data analyst or other similar-sounding roles. As a newbie in the field, your first couple of years will be dedicated to hands-on intensive learning to gain practical experience.

Some of your duties will include:

  • Data Collection: You will collect, clean, analyze and interpret trends and insights from large data sets. You might also design the channels used to collect that data.
  • Database Design and Maintenance: depending on the size of the organization and your previous experience, you might help design and build the databases, such as CRMs, ERP systems, and others, which will store all the data collected.
  • Producing reports and making presentations: You will produce reports and make presentations of the insights and trends gleaned from the data using tools like MS Excel or Power BI. This is often for the benefit of non-technical stakeholders within the company. So you need to be able to communicate complex ideas, patterns and insights clearly.

Salary: Because data analysts work across all sectors and under different job titles, you should take the average salaries stated by the top job boards more as a guide. Payscale puts the figure at C$59,972, Glassdoor has the figure at C$61,721, while Indeed averages out their data at C$66,495.

Mid - Senior Analyst Roles

As you gain experience as a data analyst, delivering projects and mastering your technical and soft skills, there are two main paths to progress your career in paid employment. These are the management and specialization routes.

  • Management: As a manager, you will identify and delegate projects to junior members of the team. You will also be in charge of allocating and accounting for your team's financial and staffing resources. You will have to set priorities and target dates. You might find yourself moving away from technical tasks to more of a supervisory role.
  • Specialization: The second option brings us back to the field where you got your first position as a junior analyst. You might decide that being a manager is not for you. Maybe you prefer to be in the weeds, using your technical abilities to gain insights to help solve complex problems. In that case, your best option is to specialize in that sector. Depending on that, you can expect job titles such as Finance Analyst, Systems Analyst, Digital Marketing Analyst and so on. This will involve advanced study and taking data certifications relevant to your chosen area of specialty.

Salary: As a senior data analyst, you can earn upwards of CAD85,000 as your average base salary. Indeed puts the figure at C$87,309, while Glassdoor pegs it at C$96,354.

Alternative Paths

The two other options for a data analyst looking to advance their career, either independently or along a different path, are Consulting and becoming a Data Scientist.

  • Consulting: Your years of experience, alongside your knowledge of the field in which you’ve specialized, puts you in a position to work independently, either as an independent contractor or by setting up your Data outfit. There are upsides and downsides to both options. As an independent contractor, you can choose the projects you would like to work on, prioritizing based on preferences of interest, challenge or fees. However, you will have to be in charge of your finance and tax obligations. Setting up your outfit provides even more flexibility if you have strong entrepreneurial skills. However, running a business is not a prospect many find appealing.
  • Become A Data Scientist: A data scientist plays a slightly more advanced and complex role than an analyst. A data analyst might be charged with collecting, sorting, cleaning, analyzing and presenting data. At the same time, a scientist will be responsible for devising new methods for collecting, cleaning and visualizing that data. A scientist will often require a Master's or Ph.D. in a related field.

Click to read our piece on Data Science career. We discuss the salaries and skills required for success.

The pandemic accelerated the march toward the digital economy. With the increased demand for digitized services, the need for professionals with the skills to collect, analyze and interpret this data is only set to increase.

According to the Canadian Job Bank, new job openings for Data analysts and administrators are expected to total 29,300 over the next 10 years. The future is bright for anyone interested in going down this exciting path.

Frequently Asked Questions

  • What other jobs can a Data Analyst do? The use of data in driving business objectives spans many industries and sectors, which means many companies require the services of a trained data analyst. You can utilize your skills to move into Business Intelligence Engineer, Marketing Analyst, Product Analyst, Business Analyst and Research Analyst roles.
  • Does a Data Analyst have a good career path? The short answer is yes. With the demand for data on the rise, there is also a corresponding increase in the market for people with the technical skills to collect, clean, sort and analyze that data.
  • Do Data Analysts need to code? It is possible to begin a career without necessarily learning to code. The rise of advanced data management tools means you can carry out some of the core functions of an entry-level data analyst without writing a single line of code. However, learning a scripting language will be crucial to help you advance your career. Knowing how to use languages to manipulate data and databases is a core part of the skills you will need to grow beyond the entry-level stage.
  • Do Data Analysts get paid well? As we have seen above, the pay for an entry-level data analyst is on par with that of other tech roles. Because it is a field that is slowly gaining momentum, there is still an acute shortage of senior data professionals. Your earnings rise significantly as you gain experience and progress in your career.

Ready to jump in? Join the Data Analytics Program to launch your career.