How to prioritize data trust over quantity

Why most data should be ignored The general consensus seems to be that all data is valuable. It’s not. In fact, I’d argue acting on the wrong data at the wrong time is worse than having no data at all. Wisdom doesn’t come from having more data. It often comes from knowing which data to ignore. I see a lot of companies trying to act on immature, incomplete, or decaying data - and then wondering why their AI models underperform or their dashboards mislead. The problem isn’t the tool. It’s the ‘fruit’ they’re feeding it. < I'm going to pause here and apologise for torturing this banana metaphor... > Some reminders: [1] 𝗗𝗮𝘁𝗮 𝗶𝘀 𝗮 𝗽𝗿𝗼𝘅𝘆, 𝗻𝗼𝘁 𝗮 𝘁𝗿𝘂𝘁𝗵. Just like a green banana isn’t ready to eat, raw data lacks the context and refinement needed to make intelligent decisions. [2] 𝗦𝘁𝗮𝗹𝗲 𝗱𝗮𝘁𝗮 𝗱𝗲𝗰𝗮𝘆𝘀. Insights have a shelf life. What was accurate a month ago might now be irrelevant - or worse, dangerously misleading. [3] 𝗥𝗶𝗽𝗲𝗻𝗲𝘀𝘀 𝗶𝘀 𝗮𝗯𝗼𝘂𝘁 𝗿𝗲𝗮𝗱𝗶𝗻𝗲𝘀𝘀. Good decisions come from timely, well-understood, and appropriately aggregated data. Not every data point needs to be acted on. [4] 𝗤𝘂𝗮𝗹𝗶𝘁𝘆 𝗯𝗲𝗮𝘁𝘀 𝗾𝘂𝗮𝗻𝘁𝗶𝘁𝘆. Most companies are drowning in data lakes and mistaking the splash for insight. If your team is making decisions based on every piece of data they can collect, you’re not data-informed. You’re 'data-bloated'. Here’s what to do instead: [1] 𝗗𝗲𝗳𝗶𝗻𝗲 𝘆𝗼𝘂𝗿 𝗿𝗶𝗽𝗲𝗻𝗲𝘀𝘀 𝗰𝗿𝗶𝘁𝗲𝗿𝗶𝗮. What makes a dataset ready for decision-making? Timeliness? Completeness? Source credibility? Verification via a 3rd party source? [2] 𝗕𝘂𝗶𝗹𝗱 𝗮 𝗱𝗶𝘀𝗰𝗮𝗿𝗱 𝗰𝘂𝗹𝘁𝘂𝗿𝗲. Empower your teams to ignore data that isn’t ready. Just because it’s there doesn’t mean it’s helpful. [3] 𝗖𝗿𝗲𝗮𝘁𝗲 ‘𝗱𝗮𝘁𝗮 𝗿𝗶𝗽𝗲𝗻𝗶𝗻𝗴’ 𝗽𝗿𝗼𝗰𝗲𝘀𝘀𝗲𝘀. Governance, context enrichment, QA, feedback loops - these aren’t overhead. They’re what make data edible. The goal isn’t to consume all the data. It’s to consume the right data at the right time. Just like a banana, most data is either too green or already rotten. Choose your banana wisely.

More data is not the answer. More good data is. A model underperforms? "We need more data!" Analytics seem off? "Let’s ingest more sources!" Executives demand better predictions? "Just get more data!" No. Instead ask for : ➤ Data Contracts to define clear expectations for schema, freshness, and accuracy before data even enters your pipelines. ➤ Observability & Monitoring so we can track data drift, schema changes, and anomalies in real-time to prevent silent failures. Invest in processes that prioritise quality over volume. How is your organization ensuring data quality before data quantity?

1,000,000 broken data pipelines and 15 years later, I still have nightmares. My worst decision as a first-time data leader: "Let's ingest ALL the data!" I was Head of Business Analytics at Rocket Internet - the world’s largest venture builder. Our ambitious plan: Launch every new venture with a complete data warehouse. All use cases covered: - customer churn prediction - financial reporting - merchandise planning - performance marketing budget allocation - and so on What data do we need for that? ALL OF IT! The painful reality: → Daily pipeline failures → Unreliable data → Lost stakeholder trust → Countless sleepless nights The lesson that changed everything: Start small. Pull only what you need for prioritized use cases. Today, my approach: → Focus on critical business needs → Ingest minimal necessary data → Build trust through reliability → Scale gradually with demand Result? Happy stakeholders, better sleep, and data that actually drives decisions. Want to build impactful data infrastructure without the nightmares? P.S.: Follow me Sebastian Hewing 🚀 for strategies on creating business impact with data & AI. ♻️ Reshare to anyone who needs to hear this.

More data doesn’t always mean better decisions. We’re living in an age where data is everywhere. Every click, scroll, and interaction is tracked. But collecting more data doesn’t automatically translate to better insights. In fact, too much data can cause analysis paralysis. When you’re buried under metrics, it’s easy to lose sight of what really matters. In 2025, over 68% of businesses reported that they struggled to make data-driven decisions despite having advanced analytics tools. Why? Because they were overwhelmed by irrelevant data points and lacked a clear strategy to interpret them. Instead of gathering endless data, focus on the quality and relevance. → Start with a clear hypothesis. → Identify metrics that directly align with your goals. → Avoid tracking vanity metrics that don’t impact your bottom line. → Regularly review and clean your data to remove noise. For example, instead of tracking every micro-interaction, prioritize metrics that show user intent or reveal conversion barriers. This way, you’re not just collecting numbers; you’re gathering insights that lead to action. Remember, more data isn’t the answer. Better data is.

"𝗕𝗶𝗴 𝗗𝗮𝘁𝗮" 𝗰𝗮𝗻 𝗯𝗲 𝘁𝗼𝗼 𝗺𝘂𝗰𝗵! So, focus on "𝗥𝗶𝗴𝗵𝘁 𝗗𝗮𝘁𝗮" for success. Instead of chasing vast amounts of data, prioritize precision. 𝙎𝙚𝙚𝙠 𝙞𝙣𝙛𝙤𝙧𝙢𝙖𝙩𝙞𝙤𝙣 𝙙𝙞𝙧𝙚𝙘𝙩𝙡𝙮 𝙜𝙪𝙞𝙙𝙞𝙣𝙜 𝙨𝙩𝙧𝙖𝙩𝙚𝙜𝙞𝙘 𝙘𝙝𝙤𝙞𝙘𝙚𝙨 𝙖𝙣𝙙 𝙙𝙧𝙞𝙫𝙞𝙣𝙜 𝙗𝙪𝙨𝙞𝙣𝙚𝙨𝙨 𝙤𝙪𝙩𝙘𝙤𝙢𝙚𝙨. This leaner approach offers several advantages: 🟢 𝗖𝗼𝘀𝘁-𝗘𝗳𝗳𝗲𝗰𝘁𝗶𝘃𝗲 𝗔𝗴𝗶𝗹𝗶𝘁𝘆: By focusing on the right data, you significantly reduce storage, processing, and analysis costs. This agility allows for 𝘲𝘶𝘪𝘤𝘬𝘦𝘳, 𝘮𝘰𝘳𝘦 𝘳𝘦𝘴𝘱𝘰𝘯𝘴𝘪𝘷𝘦 𝘥𝘦𝘤𝘪𝘴𝘪𝘰𝘯-𝘮𝘢𝘬𝘪𝘯𝘨, giving you a competitive edge. 🟢 𝗙𝗮𝘀𝘁𝗲𝗿 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀, 𝗕𝗲𝘁𝘁𝗲𝗿 𝗗𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀: Streamlined data processes lead to swifter analysis. This enhanced speed lets you stay ahead of trends, react to market shifts in real-time, and capitalize on emerging opportunities. 🟢 𝗔𝗰𝗰𝘂𝗿𝗮𝗰𝘆 𝗕𝗿𝗲𝗲𝗱𝘀 𝗦𝘂𝗰𝗰𝗲𝘀𝘀: Prioritizing the right data enhances the accuracy of your insights. This ensures 𝘴𝘵𝘳𝘢𝘵𝘦𝘨𝘪𝘦𝘴 𝘢𝘳𝘦 𝘣𝘶𝘪𝘭𝘵 𝘰𝘯 𝘴𝘰𝘭𝘪𝘥 𝘪𝘯𝘧𝘰𝘳𝘮𝘢𝘵𝘪𝘰𝘯, minimizing the risk of bad decisions and maximizing success. 🟢 𝗜𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻 𝘄𝗶𝘁𝗵 𝗖𝗼𝗻𝗳𝗶𝗱𝗲𝗻𝗰𝗲: With precise, actionable data, your business can identify unmet needs and emerging trends with greater clarity, fueling innovation. This targeted approach leads to the development of 𝘱𝘳𝘰𝘥𝘶𝘤𝘵𝘴 𝘢𝘯𝘥 𝘴𝘦𝘳𝘷𝘪𝘤𝘦𝘴 𝘵𝘩𝘢𝘵 𝘳𝘦𝘴𝘰𝘯𝘢𝘵𝘦 𝘥𝘦𝘦𝘱𝘭𝘺 𝘸𝘪𝘵𝘩 𝘺𝘰𝘶𝘳 𝘤𝘶𝘴𝘵𝘰𝘮𝘦𝘳𝘴, fostering loyalty and market differentiation. 🟢 𝗧𝗮𝗶𝗹𝗼𝗿𝗲𝗱 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝘀, 𝗦𝘂𝗽𝗲𝗿𝗶𝗼𝗿 𝗥𝗲𝘀𝘂𝗹𝘁𝘀: By aligning data strategies with specific business goals, you create 𝘩𝘪𝘨𝘩𝘭𝘺 𝘳𝘦𝘭𝘦𝘷𝘢𝘯𝘵 𝘢𝘯𝘥 𝘦𝘧𝘧𝘦𝘤𝘵𝘪𝘷𝘦 𝘴𝘰𝘭𝘶𝘵𝘪𝘰𝘯𝘴. This personalized approach ensures your strategies are data-driven and uniquely suited to your competitive landscape and objectives. This focused and efficient approach 𝙨𝙚𝙩𝙨 𝙮𝙤𝙪 𝙖𝙥𝙖𝙧𝙩 from competitors struggling with massive data volumes. It 𝗲𝗺𝗽𝗼𝘄𝗲𝗿𝘀 𝘆𝗼𝘂 𝘁𝗼 𝗱𝗿𝗶𝘃𝗲 𝗴𝗿𝗼𝘄𝘁𝗵, 𝗶𝗻𝗻𝗼𝘃𝗮𝘁𝗶𝗼𝗻, 𝗮𝗻𝗱 𝗰𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝘀𝗮𝘁𝗶𝘀𝗳𝗮𝗰𝘁𝗶𝗼𝗻 in a more targeted and cost-effective way. 𝗘𝗺𝗯𝗿𝗮𝗰𝗲 "𝗿𝗶𝗴𝗵𝘁 𝗱𝗮𝘁𝗮, 𝗿𝗶𝗴𝗵𝘁 𝗮𝗰𝘁𝗶𝗼𝗻" 𝗳𝗼𝗿 𝘀𝘂𝗽𝗲𝗿𝗶𝗼𝗿 𝗿𝗲𝘀𝘂𝗹𝘁𝘀 𝗮𝗻𝗱 𝘀𝘂𝘀𝘁𝗮𝗶𝗻𝗮𝗯𝗹𝗲 𝘀𝘂𝗰𝗰𝗲𝘀𝘀. 💬 Tara Kenyon, PhD 📧 DIVA@tarakenyon.com 📞 +1 828 590 4021 🌐 _www.tarakenyon.com #innovation #businessgrowth #results #qualityoverquantity #TaraKenyonPhD