How to Achieve 98% Data Reliability with Governance

I post about data governance a lot. I talk about it with customers. I bring it up in meetings. And the other day I thought: maybe not everyone actually knows what “data governance” means. Here’s how I think about it. Data governance isn’t some abstract IT thing. It’s the rules of the road for your data. Making sure it’s 𝗮𝗰𝗰𝘂𝗿𝗮𝘁𝗲, 𝗰𝗼𝗻𝘀𝗶𝘀𝘁𝗲𝗻𝘁, 𝘀𝗲𝗰𝘂𝗿𝗲, 𝗮𝗻𝗱 𝘂𝘀𝗮𝗯𝗹𝗲. That translates into a few simple but powerful practices: - 𝗔𝗰𝗰𝗲𝘀𝘀 𝗰𝗼𝗻𝘁𝗿𝗼𝗹 → who should really see what data? - 𝗦𝗵𝗮𝗿𝗲𝗱 𝗱𝗲𝗳𝗶𝗻𝗶𝘁𝗶𝗼𝗻𝘀 → “revenue” means the same thing in finance, marketing, and sales. - 𝗟𝗶𝗻𝗲𝗮𝗴𝗲 → knowing where the data came from and how it’s been changed. - 𝗔𝘂𝗱𝗶𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆 → being able to trace back who used what and when. Without governance, you get chaos: dashboards that don’t match, models that don’t perform, risks that slip through the cracks. With governance, you get trust: one version of the truth, faster decisions, and AI that’s reliable instead of risky. It’s not glamorous, but it’s the foundation everything else rests on.

🚀 New Blog Alert on Medium 🚀 “Data Governance Simplified: A Beginner’s Guide for 2025” In today’s data-driven world, organizations struggle with data silos, poor quality, and compliance challenges. Without a strong data governance framework, scaling AI and analytics becomes nearly impossible. At Segmetriq Analytics LLP, we break down the essentials of Data Governance in simple terms: ✅ Metadata Management ✅ Data Quality Rules ✅ Data Lineage ✅ Business Glossary ✅ AI & Agentic AI Integration 👉 Read the full beginner-friendly guide here: 🔗 - https://lnkd.in/dRYq4quB 📊 Because in 2025, businesses that govern data well will lead the digital race. #DataGovernance #DataStrategy #AIinBusiness #AgenticAI #DigitalTransformation #DataQuality #MetadataManagement #SegmetriqAnalytics

💡 Data Governance is no longer optional — it’s the backbone of data-driven decisions. I recently wrote a blog on “Data Governance Simplified”, where I break down: ✔ Metadata Management ✔ Data Quality Rules ✔ Lineage & Glossary ✔ AI-driven Governance 👉 Here’s the link: https://lnkd.in/dARSY4ic Curious to know — in your organizations, which area do you find most challenging right now? #DataGovernance #DataQuality #CDO

Data Governance isn’t a bureaucracy. It’s the decision factory of your entire supply chain. If planning and execution feel slow, noisy or political, it’s usually a data problem disguised as a process problem. What it really is; * A system of ownership + rules that produces reliable inputs (master & transactional data) for faster, auditable decisions. * The backbone of Digital Transformation and AI—no single source of truth, no scalable analytics or advanced algorithms. * The first step to visibility & performance management - for dashboards to give you insight and direction, and OKRs to actually work. Where companies stumble; ✔️ IT alone is responsible (--need to elaborate here --)) ✔️ Ownerless data fields (lead time, MOQ, service targets) → fingerpointing, firefighting. ✔️ Excel creep—shadow copies beat the golden record. ✔️ Metric theater— “more is better” syndrome with awful mistakes on measuring the wrong thing, e.g., accuracy focus instead of bias and error to drive OTIF and inventory investment. ✔️ No change discipline for new SKUs, promos, supplier shifts. The NexusLogIQ angle; * Playbook: Field-by-field rules, ownership, validations, and workflows—lean, practical, auditable. * RACI-first design so decisions don’t stall; responsibility is explicit, not implied. * Analytics-ready data for planning models & AI (traceable features, less drift, better service/cash outcomes). * Quality gates at ingestion: Completeness, Validity, Consistency (then Uniqueness, Timeliness). * Visibility that matters: dashboards tied to WAPE, bias, σ(FE), OTIF, Turns/DoS, write-offs. 🎯 Result: fewer stockouts/expedites, cleaner S&OP decisions, lower working capital—without heroics. If you want a 2-week Data Governance Health Check including an action plan, let’s talk. 📩 info@nexuslogiq.com | 🌐 www.nexuslogiq.com #SupplyChain #DataGovernance #SOP #IBP #Planning #Analytics #AI #MasterData #NexusLogIQ ÖMER BAKKALBAŞI #CPG #Retail #Manufacturing

🚀 From Data to Decisions: The Power of Data Warehousing In today’s fast-paced business environment, decision-making depends on more than just access to data — it depends on how well we structure, store, and analyze it. That’s where Data Warehousing comes in. As Bill Inmon, the “father of data warehousing,” defined back in 1990 — a data warehouse is subject-oriented, integrated, time-variant, and non-volatile. Simply put, it provides a single source of truth that empowers executives, analysts, and managers to: 🔹 Access consolidated historical data for long-term insights 🔹 Perform advanced OLAP analysis (slice, dice, drill-down, pivot) 🔹 Drive customer, financial, and operational analysis with confidence 🔹 Support AI and machine learning models with clean, structured data For banks, financial services, and corporates, this isn’t just a technical function — it’s a strategic enabler. By separating operational systems (OLTP) from analytical systems (OLAP), organizations can run the business while also analyzing it — without compromise. 💡 The future? Data Warehousing is evolving into AI-powered ecosystems, where metadata, automation, and governance ensure accuracy, scalability, and trust in every insight. 👉 How is your organization leveraging its Data Warehouse? Is it just a storage solution, or is it truly shaping strategic decisions? #DataWarehousing #AI #Analytics #BankingTransformation #Strategy #DigitalTransformation

📊 Data Governance: The Secret Weapon for Smarter Business In today’s world, data has become the most valuable asset of every business. Managing data in a structured and standardized way is no longer optional, it’s essential. This is what we call Data Governance. 📌 What is Data Governance? Data Governance is the set of processes, rules, and practices that an organization uses to store, control, protect, and manage data, ensuring that data is: 🔹Accurate 🔹Complete 🔹Secure 🔹Accessible It is about creating a “single standard” that guides how data is used across the entire organization. ✨ Why is Data Governance Important? ✅ More Accurate Decision-Making  Reliable data ensures better quality and more effective strategic decisions. ✅ Reduced Legal & Compliance Risks Data usage must comply with regulations such as PDPA or GDPR. Without proper Data Governance, organizations risk facing serious penalties. ✅ Improved Operational Efficiency  Eliminates duplicate or hard-to-find data, enabling teams to access the right information faster. ✅ Builds Trust with Customers & Partners  Organizations that manage data transparently and securely gain greater trust. ✅ Foundation for AI & Data Analytics  High-quality data is the cornerstone of Machine Learning, AI, and advanced Data Analytics. 💡 Data Governance is not just an “IT matter.” It involves people, processes, and technology working together to ensure data is properly managed and turned into real business value. 🚀 Inteltion can help ! Our Data & AI experts can design and implement a tailored Data Governance framework that fits your business needs, transforming data into a true driver of growth. 📩 Contact us: admin@inteltion.com | 🌐 www.inteltion.com | 📞 (+66) 2 – 619 – 0209 #Inteltion #DataGovernance #DataDriven #DigitalTransformation #DataAnalytics #FutureOfData

⚡ Handling Data at Scale: Pipelines That Perform #GTS-CND:117 As data grows exponentially, the challenge isn’t just collecting it — it’s making it work at scale. 🚀 High-performing data pipelines are the backbone of modern organizations. They ensure that massive volumes of information move efficiently, reliably, and securely from source to insight. What makes a pipeline truly perform? ✅ Scalability to handle growing data streams ✅ Automation to reduce manual bottlenecks ✅ Real-time processing for faster decisions ✅ Resilience to keep operations running smoothly ✅ Cost-efficiency without sacrificing speed In 2025, businesses that master data pipelines at scale will unlock smarter analytics, AI-driven innovation, and a sharper competitive edge. 📌 The question is no longer “Do you have data?” but “Can your pipelines keep up with it?” 👉 How is your organization ensuring its data pipelines are built for the future? 📩 Contact us for more details:  ✉ Email: contactus@galaxytechnologyservices.net  🧑💻 https://lnkd.in/gaEDVW_j 👾 https://lnkd.in/gw3D4JDm? #BigData #DataEngineering #Analytics #AI #DataPipelines #Scalability

💡 Data Governance Delivers: $12M Saved, 315% ROI, and AI That Finally Works In 2025, the benefits of strong data governance are undeniable 👇 📈 ROI Gains Enterprises see an average ROI of 315% over 3 years. Many recover their initial investment in just 6–12 months. 💸 The Cost of Poor Data $12.9M lost annually due to bad data. $14.8M in compliance fines vs. $5.5M prevention cost. ⚠️ The Governance Gap Nearly 40% of companies lack governance frameworks. 44% of financial firms wrestle with fragmented silos. 💻 AI + IT Pressure With AI everywhere, up to 50% of IT budgets go to fixing disconnected data sources. 🚀 How Flex83 Helps ✅ Edge-to-Cloud Architecture → Unified data across silos ✅ Real-Time Monitoring & Alerts → Issues caught before impact ✅ Metadata Validation → Clean, trusted data at scale ✅ AI/ML Pipelines → Dynamic, automated governance Flex83 transforms governance from a roadblock into a strategic growth engine — cutting costs, accelerating ROI, and enabling innovation with confidence and control. 🔎 Question for Leaders: 👉 Are you still paying the price of inaccurate data, or are you ready to make governance your growth advantage? 📩 Let’s talk: ankit.sharma@iot83.com 👉 #DataGovernance #DataQuality #AIandData #DigitalTransformation #DataPrivacy #IIoT #Innovation #BusinessGrowth

🔐 Day 19 – Why Data Governance Matters More Than Ever Everyone wants advanced analytics, AI models, and real-time dashboards. But without data governance, those initiatives often collapse under their own weight. I’ve seen teams spend 60% of their time reconciling conflicting data definitions, or dashboards that don’t even align with financial reports. That’s what poor governance looks like — data becomes a blocker, not an enabler. Common pitfalls without governance: ❌ Conflicting definitions ❌ Data errors slipping into reports and dashboards ❌ Lack of accountability for data quality ❌ Slow decision-making due to mistrust in data Data governance is not about bureaucracy — it’s about balance. Benefits of strong governance: ✅ Clarity & Ownership → Every dataset has an accountable owner. ✅ Consistency → Standard definitions prevent multiple “versions of the truth.” ✅ Compliance & Security → Protects sensitive data and avoids regulatory risk. ✅ Quality & Accessibility → Ensures data is accurate, timely, and available. ✅ Enablement → Speeds up delivery by reducing rework and confusion. An iterative approach to solving data governance: Start small, iterate, and grow trust over time. #DataGovernance #DataStrategy #DataManagement #Analytics #DataQuality #30DayChallenge #AI

𝗠𝗮𝘀𝘁𝗲𝗿 𝗗𝗮𝘁𝗮 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝗳𝗼𝗿 𝘂𝗻𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝗱 𝗱𝗮𝘁𝗮? For those who have worked in Data space, we have gone through cycles of Master Data Management in organizations and it has been structured data for most part. Most Data Leaders are solving for it as we speak. As GenAI is being used to build knowledge systems (chat on data) & workflow automations, unstructured data is being generated and consumed at an unprecedented pace. At some point, volume of unstructured data will be much higher than structured data. Now with unstructured data becoming the main source for GenAI Solutions, 𝗗𝗼𝗲𝘀 𝘁𝗵𝗲 𝗠𝗮𝘀𝘁𝗲𝗿 𝗗𝗮𝘁𝗮 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 𝘀𝘁𝗶𝗹𝗹 𝗺𝗮𝗸𝗲 𝘀𝗲𝗻𝘀𝗲 𝗳𝗼𝗿 𝘂𝗻𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝗱 𝗱𝗮𝘁𝗮? 𝗢𝘂𝗿 𝗣𝗢𝗩- 𝗡𝗼𝘁 𝗶𝗻 𝘁𝗵𝗲 𝘁𝗿𝗮𝗱𝗶𝘁𝗶𝗼𝗻𝗮𝗹 𝘀𝗲𝗻𝘀𝗲 𝗯𝘂𝘁 𝗶𝗻 𝘁𝗵𝗲 𝘀𝗽𝗶𝗿𝗶𝘁 𝗼𝗳 𝗶𝘁. You cannot enforce the “golden record” principle but you do need governance around it. It could be around identity, provenance, enrichment, and relationships. Having clarity on these will help accelerate your GenAI solution build and drives trust and adoption. This could be the new & evolving concept and maybe its MDM2.0 loading………. At BridgePath Innovations, as we work with our clients, we’re asking the real & practical questions on Data, Data Quality & Governance. 𝗖𝘂𝗿𝗶𝗼𝘂𝘀 𝘁𝗼 𝗵𝗲𝗮𝗿 𝘆𝗼𝘂𝗿 𝘁𝗵𝗼𝘂𝗴𝗵𝘁𝘀! Ramaswamy Narayanan Premil Dennison Jayen Desai Prabhakar Vijayaprakash #Data #DataQuality #DataGovernance #GenAI #MDM #MasterDataManagement #AI