In this instructional video, Kedeisha Bryan warns that the technical skills that once secured data analyst positions are now being automated by AI, and argues that aspiring analysts must shift from tool‑centric expertise to business‑centric impact. She outlines three "levers of business value"—risk, revenue, and retention—and provides concrete project ideas for each, explaining how to frame analyses (e.g., fraud detection dashboards, e‑commerce sales analytics, churn prediction) to demonstrate tangible business outcomes. Bryan also highlights common analyst roles tied to each lever, stresses the importance of quantifying impact (e.g., cost of data breaches, churn costs, employee turnover), and advises candidates to build portfolios that solve real problems rather than generic dashboards. Throughout, she shares her personal journey from low‑wage delivery work to leading a community of 80,000 data professionals, positioning herself as a mentor for career changers. The video concludes with a call to adapt quickly to AI‑driven changes, emphasizing that business thinking, not just technical proficiency, is the key to landing a data analyst job today.
The skills that landed you a data analyst job just a few years ago are now being automated by AI. So if you're trying to break into data right now, thinking that technical skills alone will get you hired, it's not gonna cut it anymore. But here's the good news. The real opportunity isn't actually disappearing. It's only shifting.
We should not be afraid of AI. We should actually be embracing AI for all of the places that it can help. What it doesn't replace is really smart, creative people.
I think this idea that AI is going to take jobs is gonna change everyone's job. We're more productive today because of AI. We're hiring more.
The people getting hired right now, they're not the ones who know the most tools. They're the ones who can think and operate like business analysts. In this video, I'm breaking down the 3 key levers of business value that you will need to know to get hired faster in today's job market, and how you can build projects that will make hiring managers bring you in for interviews. And no, you don't need a PhD or get another degree. If this is your first time here, I'm Kedeisha, and 5 years ago I was delivering pizzas and Amazon packages for $8 an hour, and today I am running a community of over 80,000 current and aspiring data professionals. I've helped over thousands of other career changers break into data analytics without going back to school and wasting time and money on courses that just don't work. And if you ever want to work with me to land your first job in data analytics, click the link in the description. Now let's get started. Okay, starting with lever number 1, risk protecting the business. The first lever of value is showing that you understand how to help companies protect what they already have. And this is where most aspiring analysts completely miss the mark. They think data analysis is all about growth, finding new opportunities, increasing revenue, optimizing campaigns, but they don't realize that before a company can grow, it needs to stop the bleeding. Every single business is constantly at risk. I'm talking about operational failures that can cost millions, compliance issues that can turn into lawsuits, or inefficiencies that can quietly drain budgets month after month without anyone noticing. A company could have the best marketing campaign in the world driving new customers to your business, but if you have a fraud problem eating away at your revenue, all that growth is just covering up the leak. You're actually moving forward, you're just treading water. And when it comes to cybercrimes, the average cost of a data breach in the US alone is about $10 million, and that's at an all-time high. So when you build a project that shows that you understand how to identify these risks before they become expensive problems, you're not only showing technical skills, you're showing that you can protect the bottom line, and that makes you valuable. So a project idea would be building a fraud detection dashboard using credit card fraud dataset, but don't just flag transactions and call it done. Think like a business analyst. Dig into the patterns. What time of day do fraudulent transactions spike? What transaction amounts are the most common? Are there geographical patterns? And then quantify the business impact. Common analyst roles that you can find that often deal with risk are risk analysts, fraud analysts, compliance analysts, or loss prevention analysts. Now let's get on to lever number 2, revenue. The second lever of business value is demonstrating that you know how to help businesses grow. AI can tell you that sales went up or down, but your projects need to show that you can interpret why and recommend what to do next. This means identifying which products or customers drive the most profit, identifying opportunities to increase conversions, or using forecasting to guide marketing decisions. Businesses that leverage data for customer experience can increase their bottom line by up to 8% above their competition. Now here's your project idea, one that'll set you apart from the competition. There are tons of e-commerce brands out there run by online creators or small business owners that would love free sales analytics. Reach out to them and offer to analyze their sales or Shopify data for about 30 days. Analyze performance by product, region, and channel, and then present a consulting-style presentation of your analysis and recommendation. You get real-world experience and they get valuable insights, and you walk away with a case study that proves that you can drive revenue and a story you can tell in your interviews. Common analyst roles in this space include sales analysts, marketing analyst, pricing analyst, growth analyst, product analyst, or e-commerce analyst. Okay, now third lever, retention, sustaining the business. The third lever, and one that's most commonly missed, is showing that you understand how to help companies sustain what they've already built. And I'm talking about both customers and employees. Most aspiring analysts think retention is about keeping customers happy, but that's just half the story. And if you can show hiring managers that you understand both sides of retention, you're gonna separate yourself from everyone else. A known fact in business is that it's way more expensive to acquire a new customer than it is to keep an existing one. We're talking 5 to 25 times more expensive depending on the industry, but companies still chase and obsess over new customer acquisition while their current customers are quietly walking out the door. So when you build a project that shows that you understand how to identify why customers are leaving, predict churn Before it happens and recommend specific interventions to keep them around, you're not just showing technical skills, you're showing that you understand how to protect recurring revenue. Okay, now let's talk about employee retention. Companies are bleeding money from employee turnover, and most of them don't even realize how much it's costing them. Employee turnover in the US alone costs businesses about $1.8 trillion a year. And it's not just the cost of recruiting and onboarding, it's loss of productivity, lost institutional knowledge, and decreased morale, and a ripple effect on the whole team. But here's Here's why companies need analysts to get visibility into why people are leaving. Is it bad management? Is it compensation? Is it the workload? Is it lack of growth opportunities? They're just guessing, and guessing is expensive. So when you build a project that analyzes attrition rates, connects turnover to specific factors like manager performance or workload, and identifies what actually drives engagement or burnout, you're showing hiring managers something that they rarely see: someone who understands that data isn't just about customers, it's about people. Now you're showing that you're not just a data analyst. Analyst, you're someone who understands the full picture of business health. You understand that retention isn't just about customers, it's about people serving those customers. Common analyst roles in this space include customer success analyst, retention analyst, customer experience analyst, people analyst, and HR analyst. Okay, so I know you're thinking that, hey, this sounds way more work than just learning SQL and dashboards. And you're right, it is more work. But that's why most people stay stuck for months. They're doing exactly what everyone else is doing, the same courses, same degrees, the same projects, and the same templates. Hiring managers have seen the same Netflix dashboard a thousand times, and it all blends together. But when you build these projects that actually solve actual business problems, you're speaking their language, and you're showing that you know how to add value from day one. Technical skills is just the baseline. Business thinking is what gets you the offer today. Okay, now let's bring it home. The hiring landscape is changing fast, but aspiring analysts who actually land jobs today will always be the ones who can tie their projects to actual business results. AI is going to keep getting Better and better. It's going to automate more basic tasks, and that's exactly what you need to position yourself as someone who can think beyond the code.
There's always this question of adaptation. I'm a little bit more worried about the labor impact simply because it's happening so fast that yes, people will adapt, but they may not adapt fast enough.
Build a portfolio that shows that you understand how to protect what companies have, help them grow, and sustain what they've built. Do that and you will always have a job. While everyone else is panicking about AI taking their jobs, you're going to be the one using AI to amplify your impact, and you're gonna be the one landing interviews and getting the offers. So stop worrying about learning every technical skills and start demonstrating business impact in your projects and position yourself as the business-minded data analyst that every company is desperate to hire. Now, if this information was helpful, drop a comment, a like, and subscribe, and check out this next video.
