Key questions for data analysts seeking future-proof careers

AI is only as good as the data it relies on. And right now? That data isn’t always reliable.

From messy, unstructured datasets to security concerns, organizations are struggling to get their data strategies right—and it’s holding their AI initiatives back. As Drew Firment, AWS Community Hero and Enterprise Strategist at Pluralsight, explains:

"Generative AI models require massive amounts of data, which is mostly unstructured and ungoverned. Many enterprise architectures lack a modern data strategy and are not ready for the complexity and operational demands of AI workloads."

In 2025, this data gap will become impossible to ignore. More companies will invest in cleaning up their data, navigating new compliance regulations, and leveraging data for competitive advantage. That means data professionals who can bridge these gaps—whether in data engineering, analytics, or AI—will be in high demand.

To stay competitive in 2025, data professionals need to be strategic about their skills. Here are the biggest career questions you should be asking—and how to answer them.

Is SQL still worth learning in 2025?

Yes—SQL remains a must-have skill for data professionals according to the 2025 Pluralsight Tech Skills Forecast. It continues to be one of the most in-demand skills in tech, ranking as the fourth most-taken Skill IQ test on Pluralsight in 2024. Whether you work in analytics, data engineering, or cloud computing, SQL is essential for working with structured data.

SQL is the backbone of data querying and management, making it indispensable across industries. Employers expect data professionals to not only write efficient queries but also optimize database performance, work with relational database management systems, and integrate SQL with cloud-based data platforms. If you’re already proficient in SQL, consider expanding your expertise by working with cloud-based databases like Amazon Redshift, Google BigQuery, or Azure SQL Database. Advanced SQL skills such as window functions, indexing strategies, and performance tuning can also help you stand out.

What this means for you: If you’re new to SQL, start by mastering SELECT statements, joins, and subqueries. If you’re experienced, focus on performance tuning, query optimization, and cloud-based SQL solutions like Snowflake and BigQuery.

How will new data regulations impact your career?

Stricter data governance and compliance requirements are coming. In 2025, governments and organizations will increase scrutiny on data collection, storage, and usage. The Tech Skills report highlights that businesses are prioritizing data security and governance like never before. Companies will need Data Compliance as a Service solutions to keep up, and professionals with expertise in privacy laws and ethical AI will have a significant advantage.

For data professionals, this means a shift in responsibilities. Simply knowing how to store and retrieve data is no longer enough—organizations need professionals who can ensure data integrity, manage risk, and implement governance frameworks. This includes understanding privacy laws such as GDPR and CCPA, knowing how to implement role-based access controls, and being able to audit and document data flows within an organization.

If you want to future-proof your career, invest in learning data security best practices such as encryption, anonymization, and access control policies. Additionally, AI governance is becoming a crucial skill—companies need professionals who can identify bias in data, ensure model transparency, and build AI solutions that comply with emerging ethical guidelines. With companies facing increasing regulatory pressure, the ability to navigate compliance frameworks will make you an invaluable asset.

What this means for you: Get familiar with data privacy laws and governance frameworks (like GDPR, CCPA, and AI-related policies). Take the next step by learning data security principles—knowing how to apply encryption, access control, and compliance tools will set you apart.

Do you need machine learning and data visualization skills to stay competitive?

Yes—AI and machine learning literacy are becoming essential. The 2025 Tech Skills Forecast highlights that professionals with even a foundational understanding of ML are better positioned to work with AI-driven analytics and automation. Companies are rapidly integrating AI into analytics, automation, and decision-making, which means professionals who can interpret and work alongside machine learning models will have a competitive edge.

Understanding how machine learning models are trained, evaluated, and deployed allows data professionals to collaborate more effectively with data scientists and engineers. If you work in analytics, learning about regression models, clustering techniques, and feature engineering can enhance your ability to derive insights from data. Even fundamental skills, such as understanding how training data affects AI performance, can make you a more strategic contributor.

Data visualization is also becoming increasingly critical. AI-generated insights are only useful if they can be communicated effectively. Tools like Power BI, Tableau, and Databricks SQL allow professionals to create dashboards and reports that make complex data understandable for stakeholders. Beyond just using visualization tools, it’s important to develop a deep understanding of data storytelling techniques—knowing how to present insights in a way that influences business decisions.

What this means for you: Improve your machine learning literacy with foundational ML concepts like regression, clustering, and model evaluation. At the same time, refine your data visualization skills by learning best practices for data storytelling and getting hands-on with Power BI or Tableau.

How can you future-proof your data career in 2025?

To stay ahead in 2025, data professionals need to build a well-rounded skill set that blends technical expertise, analytical thinking, and business acumen. Here’s our top 5 next steps to get ahead as a data professional:

1. Master SQL—It remains foundational across all data careers, from analytics to engineering.

2. Build expertise in data governance and compliance—Regulations are tightening, and companies need professionals who can navigate them.

3. Develop AI and machine learning literacy—Even basic ML knowledge will make you more competitive.

4. Improve your data storytelling skills—Data is only useful if people understand it. Master visualization and communication.

5. Promote the value of data hygiene and strategy in AI projects—Your work is critical to making AI initiatives succeed.

Data professionals are at the center of the AI revolution—but only if they have the right skills. With a mix of technical expertise, analytical thinking, and communication skills, you can future-proof your career and stay in high demand.

The best time to invest in your data skills is now. Pluralsight’s expert-led courses and hands-on labs can help you build the expertise companies need—from SQL and data visualization to machine learning and security. Start learning today and position yourself for success in 2025. Learn more deep insights - read through Pluralsight’s 2025 Tech Skills Forecast.