You’ve heard of people who work in data and we’re sure you’ve seen an increasingly high number of AI professionals popping up as AI takes an important role in today’s world. But have you heard of AI Data Analysts? Yes, you read that right: there are professionals taking the best of data analytics and artificial intelligence to transform their careers and take advantage of two of the hottest topics in tech–and all industries–right now.
Although you may not have yet heard of the field, demand for AI data analysts is expected to grow by 23% through 2032 and that’s precisely why there’s never been a better time to focus your efforts on the intersection of data and AI.
In this article, we’ll dive into the nitty gritty of both data analytics and artificial intelligence, highlighting the ways the two fields come together to create the highly demanded and interesting field of AI data analytics.
Ready? Let’s dive right in.
Artificial Intelligence & Data
You know that the best decisions are backed by data and that’s no surprise. When you use data to guide your decision making process, you not only have more guidance to help you make the right decision, but also numbers backing up your process to stakeholders. There is room for problems, of course, but the probability of success is simply higher when you choose data.
Artificial intelligence tools and systems, as you probably know, are heavily backed by data. In fact, they’re trained on data sets to help them learn more and create more accurate outputs, which is why artificial intelligence and data come together seamlessly.
Together, they can bring the following benefits:
Improved accuracy: while there will always be some level of guessing involved in predictions, of course, but with data to support your reasoning, you’re setting yourself up for success.
Faster analysis: when done by humans or simple computer systems, data analysis can be quite time consuming. AI tools, however, are able to analyze, sort, and produce findings in an incredibly quick period of time, helping companies and individuals save time and resources.
Better identification of trends: in large data sets, identifying where patterns or trends emerge can be quite the challenge and can be overlooked by the human eye. Artificial intelligence tools, however, have an incredible ability to identify patterns and trends and flag them so that they’re known to all.
Lower costs: with AI tools that can analyze large amounts of data in a matter of seconds or minutes, you can save lots of time and resources, freeing up employee time for other tasks and receiving results in no time.
Better actionable insights: looking to increase customer loyalty? Or figure out why a certain group of users are leaving your site quickly? With AI tools, you can better understand the data you’re looking at and get results that actually help you move forward.
It seems like AI can do everything right? Will data jobs be wiped out by AI? Well, if you’re worried about this, you’re definitely not alone. But before you begin to panic, remember that the introduction of powerful AI tools is actually a giant advantage for the field and instead of eliminating jobs, the priorities and requirements for data analysts will simply shift to knowing how to use AI tools instead of just analyzing data.
The future of data and AI is incredibly bright.
Becoming an AI Data Analyst
As you can see, there is quite a strong connection between data and AI and that’s why demand is forecasted to be so high in the coming years. And to help you take advantage of this potential, we’ve outlined the basics of AI data analyst roles, what you can do to prepare yourself to enter the field, and the industries that would benefit most from your AI/data skills.
Think about it: as a data analyst, you’ll need to be familiar with the basics of data analytics, where to get data from, and what to do with results once you’re done with the analysis. But the actual process of analyzing data can be quite time-consuming and demand a certain level of competence with the actual analysis process. And here’s where AI comes up: capable of analyzing large amounts of data and delivering clear results to you in a matter of seconds, data analysts who use AI tools to optimize their workload save time and money and have more accurate results.
It’s simple: those who have AI skills and data analytics skills will soon be the most highly demanded candidates out there because they’ll be able to completely transform the company’s data process and produce better results.
AI data analysts are also needed in a wide range of fields, such as:
Marketing: with a better analysis of what users want and need, AI data analysts in marketing can help companies retain customers, attract new ones, and more accurately meet customer desires.
Healthcare: the more patient information that healthcare providers have, the better they’ll be at diagnosing and suggesting treatment options for patients. And in the field of healthcare, AI data analysts play an essential role in providing more visibility and data points for healthcare professionals.
Finance: with quick responses to possible fraud based on previous data points, AI data analysts can help protect client data and information.
Combining data and AI
If you’re looking to take advantage of the potential of AI data analysts, you’re probably wondering how exactly to get into this up-and-coming field. Well, first things first: while coding knowledge isn’t required for many AI data analyst roles, it’s probably a good idea to be familiar with the basics of popular programming languages used in AI systems, such as SQL and Python to better understand how the tools you’re using work.
To become a competitive candidate for AI data analyst roles, you’ll need to polish both your data and AI skills. What does that mean? Take a look.
Improving your data skills means:
Reviewing the basics: even if you’ll be counting on AI tools to handle the bulk of the data analysis, you’ll still need to know how data analysis works so that you can identify any potential issues and flag them.
Practicing: use real-life data sets to put what you’ve learned to the test, practicing analyzing and visualizing results so that you get some real life experience before you get to work.
Being open to feedback: if you are lucky enough to have data professionals around you, ask them for feedback on your work so that you can take their suggestions and feedback and incorporate it into your next practice data set, continuously improving.
Honing your analytical skills: make sure you don’t rely too heavily on AI by keeping your own analytical skills strong, flagging issues with the data and investigating results to ensure you fully understand the output of AI tools once you get to work.
Working on your artificial intelligence capabilities means:
Doing your research: the AI field is relatively new and incredibly fast moving, meaning you’ll need to make sure you’re up-to-date with the latest and trends, in addition to understanding the basics of how AI tools work.
Reviewing your programming skills: deep coding knowledge definitely isn’t required for AI data analysts, but to fully understand how AI tools work, a refresher on programming and machine learning can go a long way.
Thinking about AI ethics: the issue of AI ethics is quite a major one and not one that’s going away anytime soon--before you begin to use AI tools, you should explore the ethics discussions happening behind the scenes and ensure your use of AI tools is as ethical as possible.
The intersection of data and AI is incredibly powerful and if you’re looking for your ‘in’ to the tech world with a well-paid and highly-demanded field, this is definitely something to consider. And depending on where you are in your data or AI careers, an Ironhack bootcamp or short course from AI School by Ironhack may be just what you need to get started.
Take a look today and don’t miss out on what your future career as an AI data analyst could be.
