With information being generated every time you shop online, use a device, visit a medical centre and more, the need for data analytics continues to rapidly increase. From 2010 to 2020 alone, the amount of data created, captured, copied, and consumed in the world increased from 1.2 trillion gigabytes to 59 trillion gigabytes, an almost 5,000% growth.1
Data and analytics are now a core business function and outweighs strategy as the key requirement in business planning, making data analysts among the most in-demand professionals.2 Have skills in data is a priority for employers searching for new talent, even in non-technical roles. So, if you’re seeking a lucrative new career or advancement, it’s time to consider data analytics.
What do data analysts do?
Data analysts are responsible for utilizing data in a number of ways:
Find, collect, organize and analyze several styles of data, then present their data in an easy-to-understand way.
Create, develop and administer solutions for a variety of industries and organizations.
Visualize past, present and future patterns by linking and presenting information in meaningful ways.
Offer deeper insight and meaning by telling the story behind the data through narrative and visual representations. Data storytelling can include charts, graphs, diagrams, pictures, and even videos to help turn insights into action.
By amassing and examining data and employing storytelling techniques, data analysts can leverage their data to make an impact and initiate change through informed decision-making.
Types of data analytics
- Descriptive – is the backbone of reporting
Utilizes data to answer the questions like how many, when, where and what
- Diagnostic – explains why an occurrence happened
Examines data to help answer why something occurs and understand its cause and effect. This includes techniques such as drill-down (selecting and querying data), data discovery (detecting patterns by visually navigating data or applying guided advanced analytics), data mining, and correlations are often employed.
- Predictive – highlights what is likely to happen in response to changes?
For example, a business can model the changes in pricing or product offerings to determine the effects on consumer demand.
- Prescriptive – indicates what is the data guiding us to do?
Merges descriptive, diagnostic and predictive analytics to guide strategic and operational decisions.
Benefits of data analytics for industries
- Personalizing customer experience
- Informing business decision making
- Streamlining operations
- Strengthening security
Do you have what it takes?
Skills needed to become a data analyst:
- Critical thinking
- Structured Query Language (SQL)
- Microsoft Excel
- R or Python-Statistical Programming
- Data Visualization
- Presentation Skills
- Machine Learning
Is data analytics right for you?
If you’re interested in entering the field or advancing in the field of data analytics, here are some great programs to consider:
Look for Data Analytics program options that study the foundations of statistics, data analytics, big data analytics, machine learning, and software applications. Learn technical concepts from leading industry experts and benefit from virtual classroom courses and computer lab training with the latest industry tools to be job-ready.
Data Science programs find analytical solutions to business problems, using common industry software tools. This program examines new and emerging technologies, tools and strategies applicable to data science and related fields that can be applied immediately to your work.
Big Data Programming and Architecture
Big Data Programming and Architecture programs address more advanced topics, including data science, machine learning, and software applications. Programs typically provide computer lab training that can help build a professional portfolio.
Health Analytics programs focus on how to collect, analyze, and report using health data in statistical, programming, software tools and provides hands-on training that will help you stay ahead of this rapidly growing field.
Open Source Intelligence
While Open Source Intelligence (OSINT) has been around for decades, originally used by the U.S. military, organizations today are using OSINT across many departments to effectively access intelligence that will advance their business. Open Source Intelligence programs teach current, real-world skills, techniques, and tools to effectively gather and investigate OSINT data.
How much do business analyst get paid?
Data analyst shortages will create challenges – and opportunities. Now could be a good time to pursue data analytics.
The average data analyst salary in Canada is $67,632 per year. While entry-level positions start at $50,229 per year, and experienced workers can make up to $91,288 per year.3 As this field grows, those with a career in analytics can look forward to healthy compensation and a variety of career options.
Thinking of expanding your career opportunities with data analytics, but not sure where to start? Check out this short quiz to learn what data programs are right for you?
2 Canada Job Bank