How can data analysts utilize and benefit from AI?

As a data analyst in the era of generative AI, there are myriad opportunities to expand your skill set and make your daily work easier with emerging technologies. AI can automate data cleaning and preprocessing, increasing efficiency so analysts can focus on higher-level, more dynamic tasks. AI-powered predictive analytics also improves delivery and decision-making by providing more accurate forecasts based on historical data.

As a data analyst in today's digital-first environment, it's your job to learn how to use AI tools to improve productivity. If you do it right, AI can be a vital tool in your toolbox, creating a meaningful advantage and setting yourself apart as an adaptable, expert analyst.

How AI is revolutionizing the data space

Today, data is king, and AI is at the forefront of revolutionizing how data is processed and analyzed. Overall, AI is making it easier for organizations to take action. Rather than having mountains of data left under-utilized, businesses can now use it to make analytics-driven decisions.

Advanced analytics also plays a major role in data analyst up-skilling. With generative AI, analysts can conduct more sophisticated queries, including predictive modeling and simulation. This enhances the depth and breadth of insights derived from the data while empowering analysts to uncover actionable patterns and trends that were previously challenging to spot.

Analysts can also benefit from ChatGPT's endless use cases, including generating descriptions of charts or graphs and summarizing complex datasets. Programs like ChatGPT can also conduct advanced data analysis to read, clean, and manipulate data.

AI's impact on workflows

AI, when used correctly, is more of an analyst superpower than your kryptonite.

Here are a few ways AI can improve your workflows:

• Increase efficiency and productivity — AI tools can automate repetitive everyday tasks, accelerating workflows, enabling analysts to manage larger datasets, and making data processing more efficient. Alteryx, for example, is a data analytics platform that helps with data prep and basic data processing tasks.
• DataRobot — An automated machine learning platform, has more advanced capabilities such as feature engineering and model selection for higher-level analysts or those looking to up-level their skills.
• Generate collaborative insights — AI fosters cooperative data exploration and enhances interdisciplinary teamwork by making it easier to get actionable information from large datasets. Tools like Google's Looker Studio turn your data into easy-to-understand visualizations and charts that you can share throughout your organization.
• Find the right tools for your work — AI makes it easier to work smarter and faster. Generative AI tools like ChatGPT, Google Gemini, or Microsoft Copilot can provide recommendations for software and solutions that align with specific client requirements and ensure you're using the best tool for your client's needs.

New skills and tools

To master these new tools, data analysts must understand the basics of AI and machine learning (ML). Going forward, consider "AI literacy" a necessary skill for your resume.

Here are some ways to gain proficiency in AI:

• Take a course — Need help with ChatGPT, including relevant use cases for data analysts? Udemy's Generative AI for data analytics course and IBM's Generative AI for Data Analysts are two great options to get started.
• Stay up-to-date with industry trends — Participate in AI-related workshops, seminars, or webinars to stay in the loop about best practices. Fiverr's AI Hub has resources for learning fundamental AI topics as well as on-demand webinars with AI experts.
• Play around with new tools — Whether you're eager to improve your data visualization skills or leverage no-code data science, there's no better way to elevate your skillset than with hands-on learning. Other than the platforms previously mentioned, we recommend Google Colab for experimenting with new machine learning models or GitHub for learning from others' data analysis projects or showcasing your own.
• Become an industry insider — Reading articles from Data Science Central, Kaggle, and Towards Data Science and engaging with their professional networks on LinkedIn and Medium can help you network with experts and learn from their wealth of knowledge.

No matter your starting point or learning approach, as an analyst, committing to continuously refining your skills is crucial to mastering AI and enhancing efficiency in your daily tasks.

If you're seeking a hyper-personalized learning experience, Fiverr offers a variety of tutorials and data-related services.

Have a senior data scientist teach you about optimizing AI solutions, learn how to build AI-generated visualizations in Tableau, or work with an AI coach — the choice is yours!