Key Takeaways
- Data analytics powers every modern industry and is among the fastest-growing career paths.
- A structured learning path can prepare you for long-term success in a data analytics career.
- Data governance and ethics are essential to ensure secure and trustworthy data analysis.
Every Industry Today Runs on Data Analytics
Approximately 402.74 million terabytes are generated every day around the world, across every industry imaginable. With that goldmine of data comes great potential – but only if you understand analytics, and how to work with the data. According to the World Economic Forum, the data analyst job role is currently the 11th fastest growing career world-wide. This is driven, in part, by the growing need for data-driven decision-making in businesses, something 72% of businesses report as the main driver of data analytics and management in their organization, according to our research.
Data analysis allows businesses to collect, organize, and evaluate massive amounts of data, improving everything from business processes to customer service. While a data scientist works primarily with raw data to extract actionable insights, a data analyst focuses more on providing solutions to business problems. You can check out our full breakdown of data science vs. data analytics for more details.
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Six-Month Learning Roadmap
Rather than overwhelm yourself by trying to learn everything at once, we recommend taking a focused approach to improve data analysis skills. This way, you give yourself time to really dive into the particulars in a way that builds as you progress.
| Core Areas of Focus | Learning Opportunity | Your Milestones |
| Month 1: Statistics and Spreadsheets | Essential Mathematics for Business Analytics | Build foundational knowledge of different types of statistical analysis using Microsoft Excel. |
| Month 2: Dashboard Tools | Data Visualization Tools | Understand the fundamentals of popular tools like Power BI and Tableau Software. |
| Month 3: SQL and Python | What Is SQL? | Learn the programming languages you’ll likely use as a data analyst. |
| Month 4: Business Intelligence | Data Storytelling | Master the art of telling stories using charts, graphs, and other data visualization techniques. |
| Month 5: Machine Learning Fundamentals | Predictive Analytics and Machine Learning | Discover how machine learning is used in data analysis. |
| Month 6: Portfolio Building and Continued Education | Professional Subscription | Create a portfolio that shows off your skills to potential employers and invest in continued training. |
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Choose Your Track: Role-Based Learning Paths
No matter where you are on your data management career path, there are data analytics learning opportunities available to help you – and your organization – stay ahead of the curve. Here are a few options to consider depending on your job role.
| Your Role | Areas of Focus | Recommended Training |
| Data Analyst | Augmented analytics adoption | Predictive Analytics for Business Results Learning Plan |
| Business Intelligence Analyst | Data visualization and storytelling | Data Visualization Fundamentals Learning Plan |
| Data Manager | Data science and analytics concepts | Data Science for Business Professionals Learning Plan |
| Data Engineer | Data integration, data wrangling, and data enrichment | Data Engineering for Machine Learning and Data Science Learning Plan |
Building Your Data Governance, Quality, and Ethics Skills
With the rise of AI and data privacy regulations, anyone working with data analytics needs data governance and AI governance skills to ensure secure, reliable, and ethically sourced data. Learning the latest data governance best practices and AI governance best practices not only helps maintain data quality and regulatory compliance, but it also leads to more meaningful insights and trusted decisions.
Choose from a range of data governance courses and consider becoming a certified data governance professional to gain a competitive edge in the job market. DATAVERSITY’s Applied Data Governance Practitioner Certification and CDMP preparation training programs are globally recognized and taught by experienced industry professionals.
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Building an Analytics Learning Path for Your Industry
Every industry – from retail to government – uses data analysis to achieve specific outcomes, including providing better customer service. With the right data analytics strategy tailored to specific industries, organizations can gain a competitive edge.
Banking and Finance
The banking and finance sectors monitor and analyze data sets from customer transactions and trading on the stock market to assist with fraud detection (identifying unusual purchases), marketing trends and predictions, and managing risk and compliance.
Healthcare
Healthcare produces somewhere in the neighborhood of 50 petabytes of data per year. This data can be used for predicting patient outcomes, detecting insurance fraud, diagnostics, and even mapping the spread of infectious diseases.
Energy and Utilities
Utility companies are in a unique position to work with predictive analytics on a massive scale. This can include everything from predicting when a piece of equipment may break down using IoT data to forecasting energy needs based on past usage data.
Government
Governments rely on big data to provide better outcomes for millions of residents. Data is used to guide policy, measure the impact (both positive and negative) of decisions, improve disaster response, and create government efficiency.
| Industry | Must-Have Skills | Recommended Training |
| Banking and Finance | Fraud detection, market analysis, risk and compliance, predictive trading, and financial modeling | Data Security for Business Professionals Learning Plan |
| Healthcare | Ethics and compliance, measuring outcomes, visualization techniques, and fraud detection | Data and AI Ethics Learning Plan |
| Energy and Utilities | Predictive analytics, IoT data skills, and pattern recognition | Predictive Analytics for Business Results Learning Plan |
| Government | Understanding of working with big data using big data analytics, process improvement, measuring outcomes, identifying patterns, and data-backed decision making | Data Warehousing and Business Intelligence Management (Including Big Data) |
Start Your Analytics Journey with DATAVERSITY
As businesses continue to increase data collection and expand AI and automation, the demand for capable data professionals has never been greater. Developing your analytics and governance skills not only helps you turn raw data into meaningful insights, but it also helps you stand out from your peers.
Now is the perfect time to get started. By following our six-month data analytics learning path, earning certification, and building your portfolio, you’ll gain the expertise and confidence necessary to excel in this rapidly evolving field.
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