Future of Trusted Data Analytics

📌 The Future of Agentic Analytics in BI There’s a growing misconception right now... That layering AI into your dashboards will magically transform your analytics. There’s a lot of hype around AI agents in analytics: ⤷ Natural language interfaces. ⤷ Auto-generated insights. ⤷ Chat-based dashboards. You might’ve even heard of the term Agentic Analytics The promise is that business users will be able to “ask anything” and get instant answers from data. But here’s the problem no one’s talking about: Most organizations aren’t ready for AI agents yet. Not because the tech isn’t mature. But because their data context is broken. → If your KPIs are misaligned across teams… → If your semantic layer is missing or incomplete… → If no one trusts how metrics are calculated… Then all an AI agent will do is generate faster wrong answers. You’ll get output but not outcomes. Before you invest in Agentic Analytics, ask yourself: 1) Do we have a single source of truth for our KPIs? 2) Is our semantic layer well-structured and governed? 3) Are stakeholders confident in the meaning behind the metrics? 4) Can business users explore data on their own? If not, the priority isn’t AI. It’s trust, structure, and shared understanding. That’s why the recent Salesforce acquisition of Informatica makes perfect sense. While the market chases the next flashy analytics tool, Salesforce is investing in the fundamentals: → Data integration → Metadata → Governance Because they understand this: AI is only as effective as the context it runs on. Here’s what I’ve seen work in the real world: 1️⃣ 𝐒𝐭𝐚𝐫𝐭 𝐰𝐢𝐭𝐡 𝐲𝐨𝐮𝐫 𝐬𝐞𝐦𝐚𝐧𝐭𝐢𝐜 𝐥𝐚𝐲𝐞𝐫 Define your KPIs, dimensions, and filters like you’re building a product. 2️⃣ 𝐃𝐨𝐜𝐮𝐦𝐞𝐧𝐭 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐥𝐨𝐠𝐢𝐜 Explain what each metric means and where it comes from. 3️⃣ 𝐀𝐥𝐢𝐠𝐧 𝐚𝐜𝐫𝐨𝐬𝐬 𝐝𝐞𝐩𝐚𝐫𝐭𝐦𝐞𝐧𝐭𝐬 Marketing, sales, ops should all speak the same data language. 4️⃣ 𝐁𝐮𝐢𝐥𝐝 𝐝𝐚𝐭𝐚 𝐭𝐫𝐮𝐬𝐭 Through consistency, transparency, and usage-based feedback. 5️⃣ 𝐃𝐞𝐩𝐥𝐨𝐲 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭𝐬 Then and only then you can explore AI as a layer on top of a solid foundation. BI without context is just noise. And AI without structure is just risk at scale. If you’re serious about improving decision-making in your business, fix your foundations first. The tools will come and go. Context is what makes them useful. #DataStrategy #BusinessIntelligence #DataGovernance

Talk to Data, "the future of conversations with data" Imagine asking your data a question and getting a clear, contextual answer that cites sources, shows the key numbers and explains itself in plain language. That future is closer than you think. Conversational access to data will change how organisations decide, act and who gets to make informed choices. Key trends to watch • Voice and multimodal interfaces Talking to data will include voice and visual inputs so people can point at charts, refine results naturally and get answers without a steep learning curve. • Domain tuned models and retrieval augmented generation General models will be combined with domain specific retrieval so answers are both fluent and grounded in verified sources. • Real time contextual analytics Conversations will keep context and work with streaming data, surfacing changes and anomalies as they happen. • Knowledge graphs and semantic layers Semantic models will resolve ambiguity, link concepts and deliver richer, explainable responses across datasets. • Agents and workflow integration Conversations will not just inform. They will trigger actions, schedule reports and integrate with business workflows. • Governance, provenance and explainability Provenance, audit trails and clear explanations will be essential to build trust and meet regulatory requirements. Practical tip: Start with a focused pilot, pair it with strong governance and measure time to decision. Small wins build trust and scope for bigger change. How is your organisation preparing to talk to data? #TalkToData #Data #AI #Analytics #KnowledgeGraphs

DataOps: Accelerating Trustworthy Data Delivery As Enterprise Architects, we know: 👉 Moving fast with bad data is worse than moving slow. Data is now the backbone of decision-making. But speed alone won’t cut it—leaders need data that is fast, reliable, and trustworthy. This is where DataOps changes the game. Think DevOps, but for data pipelines—bringing rigor, automation, and governance to every step of delivery. What makes it different? 1️⃣ Continuous integration for data pipelines 2️⃣ Automated testing to catch issues early 3️⃣ Real-time monitoring for failures 4️⃣ Collaboration across engineering, analytics, ML, and business 5️⃣ Versioning for trust and reproducibility For Enterprise Architects, the takeaway is clear: DataOps isn’t just a technical framework—it’s a governance accelerator. It ensures the data flowing into analytics, AI, and dashboards is something your business can trust. 👉 The future of EA isn’t just designing systems. It’s ensuring those systems deliver trusted data at scale.

📢 Debbie Reynolds "The Data Diva" presents The Data Privacy Advantage Newsletter 📢 In my latest essay, “Trust as Currency: How Privacy Will Shape the Next 10 Years of Business Success,” I explore why privacy is not just a compliance requirement but the most decisive factor that will determine which companies thrive and which companies fall behind. Trust has become the new currency of business. Customers, regulators, partners, and employees are all watching how companies handle data, and the choices made today will determine competitive advantage tomorrow. Over the next decade, the organizations that lead will be the ones that: 💡 Treat trust as a measurable asset - building it deliberately, protecting it rigorously, and using it as a foundation for long-term growth 🔒 Integrate privacy into every decision - not as a box to check, but as a lens that drives innovation, customer confidence, and sustainable operations 🌍 Navigate global complexity with agility - understanding how AI adoption, cross-border regulations, and evolving trust frameworks will impact strategy 📊 Turn privacy into performance - leveraging governance, accountability, and transparency to expand into new markets, reduce risk, and unlock revenue The hidden risk is not just data breaches or fines, it is the erosion of trust that quietly eats away at brand value and customer loyalty. Once lost, it is nearly impossible to recover. But companies that place privacy and trust at the center of their strategy will not only avoid costly mistakes, they will win business that their competitors cannot. Executives should be asking themselves: ❓ Are we treating trust as an asset on par with financial capital ❓ Do our customers truly believe we are transparent with their data ❓ Are we ready to prove our privacy practices when regulators, partners, or clients demand it The next 10 years will not be won by companies that move the fastest, but by those that inspire confidence in every transaction, every relationship, and every innovation. Privacy is the foundation of that confidence, and the companies that understand this will set the pace for the future. 📖 Read the full essay here If your organization is ready to retain value, reduce risk, and increase revenue through data privacy and trusted governance, I help executives and leadership teams achieve exactly that. Connect with me directly to discuss how I can support your strategy. #dataprivacy #datadiva #privacy #cybersecurity #trust #businessgrowth #governance #digitaltransformation #AI #futureofbusiness #leadership #strategy

AI is everywhere right now, but not every approach delivers real value.   At Precisely, we’re committed to putting trusted data - and customer control - at the center of how AI is adopted. That’s why our approach spans four dimensions, each designed to deliver measurable impact for both our business and our customers:   1️⃣ Driving operational efficiency – With 30 live deployments and another 30 pilots, AI is already embedded across our company. This isn’t experimentation without purpose - it’s about driving efficiency and productivity across our operations and helping employees focus on what they do best.   2️⃣ Enabling trusted AI with data integrity – No AI initiative can succeed without trusted data at its foundation. Yet only 12% of organizations believe their data is AI-ready. That’s why we’re helping customers govern their AI use and ensure the right data is fueling their initiatives.   3️⃣ Accelerating customer outcomes with AI-powered features – Our focus is on empowering businesses to realize value faster. Through our AI Innovations Lab, we’re delivering solutions grounded in our core principles of being trustworthy, valuable, and fully in the customer’s control - never AI for AI’s sake.   4️⃣ Expanding through strategic M&A – For over a decade, acquisitions have strengthened Precisely’s capabilities. Looking ahead, we see new opportunities in areas like unstructured data - increasingly critical with the rise of generative and agentic AI.   👉 In this video, I take a deeper dive into each of these four dimensions, and what they mean for the future of AI at Precisely and for our customers. Link: https://lnkd.in/eZHHX2d4   #DataIntegrity #AI #TrustedData