Hello everyone. This is Ma Car Busa. I am a BN data specialist with 18 years of experience. Today I want to talk about something every company struggles with. How do we let people use data easily while still keeping everyone, everything, everything's secure. We are living in a world where data is everywhere. And everyone want answers fast. So let's walk through how self-serve BI and DevSecOps can work together in a simple practical way. So here's our plan for today. The huge growth of data, why self-serve BI is becoming essential, why security must be built into everything, how AI is changing analytics with some real time examples and. Simple roadmap you can follow. Let's get into it. We are surrounded by more data than ever before. The world is hitting 1 75 terabytes of data. That's a number. So huge. It's almost silly, but here's the problem. Even though we have all this data, companies still struggles to answer simple questions. Why? Too much data? Too many systems. Reports take too long, and everything is struck in silos. So the business waits and waits. This is where self-serve BI comes in. Self-serve BI is simple, lets people get their own answers without waiting for it. Imagine if marketing, hr, finance, operations. Everyone could open a dashboard and get insights instantly. It saves time. It speeds up decisions. It removes body lengths, and instead of waiting a week for a port, people get answers in minutes. That's the power of self serve. But here's the catch. When you give more people access to data, you must also be careful. That's where DevSecOps comes in. It basically means build security into every step from development to deployment to daily operations. Don't think about security at the end. Think about it from the beginning, just like you put on a seatbelt before driving, not after. This slide is important because studies show 70% of BI projects fail. Not because the technology is bad, but because there is no governance, people aren't trained, access is too open and too restricted, or the system is too complicated, so only 30% succeed, and they do so because they balance two things. Security and easy access. Not too tight, not too loose, just right. Ai, AI has changed the game completely. Now, you don't need to write code our sql. You can simply ask the system, show me this month revenue. What are the top reasons for customer churn? And the system answers. AI can find patterns, predict outcomes, and guide users. It's like having a mini data analytic. Analyst sitting on your shoulder. But again, the more powerful the tool, the more important the security. This is the perfect mix. Faster insights, more accurate predictions, strong security, working quietly in the background. Users shouldn't have to fight the system. The security shouldn't show slow down and business. When done right, you get speed and safety together. Here's a simple example. A marketing team used AI powered BI to check how their campaign campaigns were performing before reports took hours. After insights came in minutes, they cut costs improved ROI and still stayed compliant with privacy loss. That's the goal. Fast answers with zero risk. One more example this time from hr, A company used predictive analytics to understand which employees might leave. Not to punish everyone, but to offer help early. This only worked because sensitive data has protected. Only HR could see the details. Every access was audited. This is responsible analytics. Good security starts with simple things, give people access only what they need, hide sensitive data for people who shouldn't see it, and use multiple multifactor authentication. Make sure sessions automatically time out. These control prevent, prevents accidental mistakes and protect the organization. Lineage is basically the story of your data, where it come from, what transforms happened, who touched it, how it be being used. This builds trust. When leaders ask, where did this number came from? You have the answer, right? It also keeps auditors happy. Tools don't create success. People do to make BI and security work. Leaders must support it. Users must be trained. Policies must be clear and continuous improvements must happen when people understand the why they follow them, and how out here is an easy roadmap, access your current state. What data do you have and what gaps exist? So design your architecture, build the security and automation in mind, and how do we enable users, train them, support them, make tools simple. And finally, monitor and option optimize. So improve based on usage and feedback and security needs. This roadmap works for small teams and large enterprises as well. And finally the key takeaways, let's, let me summarize the whole talk in four points. Security and accessibility should work together, not against each other. AI is speeding up analytics tremendously. Culture matters more than tools and DevSecOps ensures BI is scalable and safe. If we get this right, we build a truly. Data driven organization. Thanks for thanks everyone for listening. I'm happy to answer any questions and talk through any of the challenges that you're facing right now with the within BI and data space. You guys can reach out to me in LinkedIn. Thank you.