Data analytics, a sub-field of data science, is a critical business function in industries ranging from healthcare to finance to gaming and travel. With Canada’s leading data analytics courses and training programs, you will learn to extract meaningful insights from an organization’s data and use it to inform strategic decision-making at the highest levels.
Success in the data analytics field requires a versatile skill set combining technical and soft skills, along with meticulous attention to detail and critical thinking abilities. Proficiency in data visualization in order to communicate findings with both technical and non-technical audiences is also a key skill. Professionals in this dynamic field should be passionate about continuous learning and take into consideration the ethical implications of handling sensitive data.
According to the U.S. Bureau of Labor Statistics, the data analytics field is projected to experience growth between 2022 and 2032, particularly in market research analyst roles. They’re expected to increase by 13 per cent during that period, with a forecasted 94,600 new job openings every year. Meanwhile, financial analyst roles are projected to grow by 8 per cent with 27,400 new positions added annually.
Programs preparing people for a career in data analytics typically include courses in data visualization, data ethics and privacy, business intelligence, how to design and maintain decision support systems, data mining, and data governance. Data analytics programs may also include specialized training in statistical methods for data analytics, grounding in advanced Excel, and programming for data analysts that commonly focuses on Python, SQL and R.
Employers hiring for data analytics roles usually require a bachelor’s degree in computer science, data science, IT, statistics, or mathematics — although graduates in related fields such as information management, finance, economics, and business will also have transferable skills. For those interested in deeper learning and specialization in the field, a master’s degree in the above disciplines or an MBA with a business analytics specialization could provide a competitive edge.
Increasingly, learners are turning to colleges and bootcamps offering certificates, diplomas, and short courses in accelerated formats to kickstart their career with hands-on training and career support.
Talent.com reports the average salary for a data analyst in Canada is $91,948. While entry-level roles start at $65,663, more experienced candidates can earn closer to $140,000.
What is the difference between data analytics and data science?
Data analytics is a specialty within data science, which is a general term that encompasses many different types of data roles.
Data analytics uses processed, historical data to identify trends, generate actionable insights and answer questions to drive better business results. Data science takes raw data from various unconnected sources and creates algorithms, predictive modeling processes, and other custom analyses to shape raw data into insights.
In other words, data analytics makes sense of existing information. Data science finds innovative ways to capture and analyze the data used by analysts.
Data science is a more technical field, and typically requires more advanced education and programming expertise. Data analytics, on the other hand, may require more business training and context in order to translate insights — about consumer behaviour, seasonal demand trends, supply chain issues or product defects, for example — into strategies that help businesses and organizations achieve their objectives.
Do I need a degree to get a job in data analytics?
While the typical level of education needed for an entry-level data analytics role is a bachelor’s degree in computer science, IT, statistics, data science, or mathematics, it is still possible to land a job without a degree.
According to Shaohua Zhang, CEO of data science and AI training academy, WeCloudData, today’s technologies are evolving so fast that most university programs may not be able to keep up. A degree by itself may not, therefore, be the best job performance indicator. Having real-world project experience, and a portfolio of work that demonstrates a history of trial and error, especially in combination with the right training, can increase a candidate’s chances of securing a good job in the field.
There are a number of coding bootcamps and college certificate and diploma programs that offer intensive, accelerated training that can help build necessary foundational and practical experience in the field while providing job support.
What are common career paths within the data analytics field?
Armed with data analytics skills, there are a number of career paths available to you across virtually every industry, from technology, media, life sciences and retail to financial services, government and academia.
For example, business analysts extract business-specific data and use it to streamline processes or optimize organizational structures, how budgets are allocated and marketing dollars spent. Financial analysts leverage data to reduce financial risk for banks, or uncover potential revenue streams for startups.
Healthcare data analysts interpret historical data in order to facilitate medical research and improve outcomes for patients, while data journalists use tools like Python and Tableau to communicate through charts, graphs and infographics that reveal important and perhaps counterintuitive insights within news stories.
Marketing analysts, meanwhile, might use sales data to determine which products to prioritize across email, social media and featured positions on an eCommerce website.
Finally, data analysts can transition into data science roles by adding advanced math and programming skills to their toolkit while gaining a deeper understanding of machine learning. In fact, many data scientists begin their career as data analysts. Data scientists, conversely, might grow into more senior managerial roles, at which point managing people and business strategy requires them to focus more on interpreting data than collecting it.
What is the average salary for a data analyst?
Data analytics can be a high-paying career, but average salaries depend on your level of experience, the size and location of the company you’re working for, and the role you’re in.
According to Talent.com, data analysts in Canada earn an average salary of $91,948. Entry-level salaries start at $65,663 and can reach up to $140,000 for more senior level positions. Related roles fetch similar salaries: data managers earn an average of $137,844, business analysts make on average $130,617, and business systems analysts pull in average salaries of $113,462.
Those interested in transitioning into data science and becoming well-versed in machine learning engineering can expect even higher salaries, earning on average $150,186.
How do I become a data analyst with no experience?
While it may be challenging to land a full-time job without any prior experience, volunteering, interning, or working on freelance projects is a great way to gain that practical, hands-on experience.
The first step to building a profile ahead of applying for junior data analytics roles is to develop the right skills. Online courses and coding bootcamps focused on programming languages such as Python or R, can be an excellent start for newcomers to the data analytics field.
The next step is to create a portfolio that showcases your data analytics projects, while also demonstrating problem solving and data analysis capabilities.
Finally, earning certifications that show proficiency in data analytics tools and methodologies, as well as relevant programming languages, are a way to get the experience you need to land a job.
Joining a community and networking is another way to get your foot in the door. You’ll be able to connect with other data analytics professionals in the field, and get advice from those with more experience.