As a complex field, data analytics jobs tend to require some measure of higher education as well as an array of skills, as we’ve discussed above. 

A large-scale survey of data analytics job descriptions by Glassdoor turned up three almost universally required qualifications:

• A degree, preferably in mathematics or statistics
• Experience with programming languages like Python, R and SQL
• Solid foundation in technology and data mining techniques

Given the diverse skill set required to qualify for most jobs, any aspiring data analyst should consider supplemental instruction and certification to give themselves a competitive edge in the job market. Fortunately, there are a wealth of opportunities available, from introductory data analytics courses to specialized programs in machine learning and Python all the way up to MBA programs with a data analytics focus.

Data analysts require a unique blend of technical and “soft” skills in order to decipher and communicate meaningful conclusions and solve problems. A data analyst’s toolbox must include:

Math 

Math is a core element of data analytics, particularly probability and statistics. Depending on the complexity of your job, the volume of data and algorithms involved, you may need some fluency in calculus and algebra as well. There’s some debate in the data analytics field over exactly how much math is really required and which skills you need, but the general consensus is that any successful data analyst must be very good with numbers.

Computer science 

Data analytics requires versatile computer skills, including programming, databases and data analysis tools. Some of the most common tools employed in data analytics range from the everyday like Microsoft Excel to more complex programs and languages, such as Python, R, JavaScript, MATLAB, SQL and machine learning. Then there are visualization tools like Tableau and Qlikview, which are a key element in delivering the insights gained from the analyzed data.

Communication

One major challenge for some data analysts is effectively communicating the patterns and insights you’ve found to others who don’t have the same level of technical expertise. Once you’ve found the numbers in your data, it’s vital to know how to communicate the insight. A data analyst must be multilingual – fluent in the highly technical aspects of the work while also able to provide clear explanations to decision-makers. A data analyst must also be adept in different formats, ready to explain findings and conclusions verbally, textually and visually.

Data analytics in action

There are four main types of data analytics:

Descriptive: uses data to examine, understand and describe something that has already happened. For example, data showing a decrease in monthly sales. 

Diagnostic: works to explain why something happened. Why did a company’s sales go down?

Predictive: uses historical and other data to forecast the near future. What is likely to happen to our company’s sales in the next quarter?

Prescriptive: aims to provide a course of action. What steps can our company take to improve sales based on insights about our target customer and past increases or decreases in monthly sales?

Organizations then leverage these analytics to inform and enhance their operations, applying them to key areas like budgeting, risk management, marketing, sales and product development.

Data analytics skills open opportunities in an enormous range of industries and sectors, including life sciences, media, financial services, technology, retail and many more. Those skills can also lead to various data specialties, including these common career tracks:

Data Scientist

Many data scientists start their career as data analysts. Armed with foundational data skills, a data analyst can level up their advanced math and programming abilities and develop new skills like an understanding of machine learning and transition into data science. Many data scientists are employed “in-house” at companies, organizations or governments, for example, to handle ongoing data needs. 

Specialist

A data analyst may choose to focus their skills on a particular industry or sector. Here are just a few of the specialized roles available to those with data analytics skills.

• Business analysts examine data specific to a business and use it to optimize internal operations, such as manufacturing processes or organizational structures. 
• Financial analysts use data to target investment opportunities, identify potential revenue streams and mitigate financial risk.
• Market analysts consider market trends to determine which products and services to sell, the effective price points, and how to best target customers.
• Actuaries analyze accident, disability, sickness, retirement and mortality rates to create probability tables and forecasting strategies for insurers.
• Web analysts monitor website activity to optimize user experiences and improve website conversion metrics.
• Marketing analysts pore over campaign analytics across various channels, including social media, email, and web traffic, to develop and optimize digital advertising campaigns.
• Healthcare analysts work for public health organizations, from government ministries to hospitals, to understand everything from wait times for certain procedures to the value for money being delivered from different healthcare equipment.
• Insurance and credit analysts use massive data sets to evaluate risk and develop financial and insurance products that determine everything from how much credit you qualify for to how much you will pay to insure your home.
• Data journalists analyze data sets like crime, economic or sports statistics, healthcare records or government employee salaries to either create or supplement news content.

Consultant

After developing your skills and experience to a high degree, working as an external consultant can be an attractive option. This can involve freelancing or working for a consulting firm, conducting analysis for a wide range of clients. Freelance consultancy in particular offers greater freedom to pick your own projects and hours, as well remote work opportunities.

Instructor

Along with the increased demand for data analysts is an increased demand for people to train them. Data experts with sufficient experience and excellent communication skills and a passion for teaching may find opportunities at colleges and universities to train the next generation of data analysts.

Data analysts tend to work in a team environment, collaborating with other analysts to interpret data and then with other departments and individuals within an organization, such as marketers, salespeople, developers and executives. 

The work tends to be office-based with the typical accompanying schedule, 9-5, five days a week. Overtime and weekend work is sometimes required to meet aggressive deadlines or complete major projects. 

Most of the work is done at a computer, so will involve long hours at a desk.

Like data science, the data analytics field has a distinct gender gap. A 2020 report from Boston Consulting Group found men make up nearly 80 per cent of the workforce and the bulk of senior-level positions as well, although the STEM fields are slowly growing more diverse.

Overall, data analysts benefit from a safe working environment. The most often reported cons of the job are heavy workloads and the accompanying stress, as well as the health concerns stemming from long hours seated in front of a computer.

There’s no better time to be a data analyst. As it also turns out, there’s almost no better place. According to a 2021 report from SalaryExpert.com, the pay for an entry-level data analyst in Canada is the fifth-best on the planet.

The average salary for data analysts in Canada is $70,676, according to Talent.com. Entry-level positions pay just over $65,322, while the most experienced candidates can earn closer to $140,000 per year. This is, on average, less than the average salary for a data scientist.

Compensation can vary widely, depending on the company, industry and location. For example, data analysts in Quebec have the highest average pay ($135,384), while Manitoba is on the low end of the scale at $82,466, according to Talent.com. Ontario sits near the top, at $129,492 annually, along with Nova Scotia ($125,295) and New Brunswick ($123,698).

Expect salaries to be highest in the financial services field (banks and insurance companies in particular) although professional services, media and technology, and even some larger retailers, offer generous pay.