Daniel Egli

Is a Data Modeller Really Necessary? Absolutely! Here’s Why: In the age of big data and digital transformation, the role of a Data Modeller has become more critical than ever. But why exactly do we need Data Modellers? Key Reasons Why Data Modellers Are Essential: 🔍 Organizing Complexity: As organizations collect vast amounts of data from various sources, Data Modellers create structured frameworks that simplify this complexity. They turn chaotic data into a well-organized asset. 📊 Informed Decision-Making: A well-designed data model allows businesses to extract actionable insights quickly and accurately. This drives better decision-making across all levels of the organization. ⚙️ Optimizing Performance: Efficient data models enhance database performance, ensuring that data retrieval is fast and reliable, which is crucial for real-time analytics. 🔒 Maintaining Data Integrity: Data Modellers set standards and rules that ensure data consistency and integrity, preventing errors and maintaining high-quality data across the organization. 🌐 Future-Proofing: As businesses grow and technology evolves, scalable and adaptable data models are essential. Data Modellers design systems that can handle future data needs without major overhauls. 🤝 Bridging Gaps: Data Modellers act as a bridge between technical and business teams. They translate business requirements into technical specifications, ensuring that data systems meet business goals. In essence, Data Modellers are indispensable in harnessing the full potential of data. They lay the groundwork that allows data scientists, analysts, and business leaders to do their best work. Without their expertise, the path from raw data to strategic insight would be far less efficient and far more error-prone. Let’s Appreciate Our Data Modellers: If you work with data or rely on data-driven decisions, take a moment to appreciate the Data Modellers who make it all possible. Their work might be behind the scenes, but its impact is front and centre. Question for You: How has effective data modelling made a difference in your organization or project? Share your experiences and let's discuss the impact of this crucial role! 📊🔍 #DataModelling #DataScience #DataIntegrity #DataDriven #TechHeroes #DigitalTransformation

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Check the following if you want to deploy your first platform to operationalize Agents and GenAI applications within 20 minutes. This is an amazing artifact and GenAI booster from Elia Secchi! #genai #agents #gcp #aiengineer #cloud

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"𝘚𝘰 𝘵𝘩𝘦 𝘵𝘩𝘪𝘯𝘨 𝘵𝘩𝘢𝘵 𝘐 𝘸𝘰𝘳𝘳𝘺 𝘢𝘣𝘰𝘶𝘵 𝘢 𝘭𝘪𝘵𝘵𝘭𝘦 𝘣𝘪𝘵 𝘪𝘴 𝘵𝘩𝘢𝘵 𝘸𝘦, 𝘦𝘴𝘱𝘦𝘤𝘪𝘢𝘭𝘭𝘺 𝘐 𝘵𝘩𝘪𝘯𝘬 𝘪𝘯 𝘌𝘶𝘳𝘰𝘱𝘦, [...] 𝘵𝘩𝘢𝘵 𝘸𝘦 𝘸𝘰𝘳𝘳𝘺 𝘵𝘰𝘰 𝘮𝘶𝘤𝘩 𝘢𝘣𝘰𝘶𝘵 𝘵𝘩𝘦 𝘱𝘰𝘵𝘦𝘯𝘵𝘪𝘢𝘭 𝘥𝘰𝘸𝘯𝘴𝘪𝘥𝘦𝘴, 𝘢𝘣𝘰𝘶𝘵 𝘵𝘩𝘦 𝘱𝘰𝘵𝘦𝘯𝘵𝘪𝘢𝘭 𝘤𝘩𝘢𝘯𝘨𝘦, 𝘢𝘣𝘰𝘶𝘵 𝘪𝘯𝘷𝘦𝘴𝘵𝘮𝘦𝘯𝘵𝘴 𝘸𝘦 𝘯𝘦𝘦𝘥 𝘵𝘰 𝘮𝘢𝘬𝘦, 𝘢𝘯𝘥 𝘸𝘦 𝘨𝘦𝘵 𝘴𝘵𝘶𝘤𝘬." 🎙 Today I recorded another episode of The Only Constant with Peter Gostev - and what a gem this episode turned out to be! If you've followed Peter, you know he is on the frontier in GenAI adoption and stress testing, and while I perhaps expected a more technical perspective I believe we also managed quite a deep conversation on what adoption means, how transformation looks and what innovation means for societies and organisations at large. We spoke for more 1h 15 mins or so, and while this might seem a lot, it is in great company and I cannot wait to share the episode in a few weeks! 👏 👉 While you wait, why not check out the previous episodes? You can find The Only Constant on Apple, Spotify, or host Spreaker, with a link in my profile 🎧. Do let me know in the comments what you think of the series—and who you think I should attempt to get on the show in the future. #AI #innovation #technology #generativeai #foundationalmodels #usecases 🤝 #Connect or #Follow on LinkedIn for a blend of serious insights and lighthearted humor about everything IT and business. 🎧 #Listen to The Only Constant podcast

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𝐂𝐨-𝐏𝐢𝐥𝐨𝐭 𝐚𝐧𝐝 𝐏𝐨𝐰𝐞𝐫 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦 𝐒𝐞𝐫𝐢𝐞𝐬 #𝟑 𝗪𝗼𝗿𝗸𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗰𝗼𝗺𝗽𝗹𝗲𝘅 𝗱𝗮𝘁𝗮 𝗺𝗼𝗱𝗲𝗹𝘀 𝘂𝘀𝗶𝗻𝗴 𝗘𝗥𝗗 𝘃𝗶𝗲𝘄 𝗮𝘀𝘀𝗶𝘀𝘁𝗲𝗱 𝗯𝘆 𝗖𝗼-𝗣𝗶𝗹𝗼𝘁 𝗶𝗻 𝗣𝗼𝘄𝗲𝗿 𝗔𝗽𝗽𝘀. 𝐋𝐢𝐦𝐢𝐭𝐚𝐭𝐢𝐨𝐧𝐬 𝐨𝐟 𝐄𝐚𝐫𝐥𝐢𝐞𝐫 𝐕𝐞𝐫𝐬𝐢𝐨𝐧𝐬 • Only single table applications could be created. • Real-world applications often require complex models with multiple tables and relationships. 𝐍𝐞𝐰 𝐅𝐞𝐚𝐭𝐮𝐫𝐞 𝐀𝐧𝐧𝐨𝐮𝐧𝐜𝐞𝐦𝐞𝐧𝐭 • Ability to handle complex data models using ERD view with Co-Pilot. • Steps to enable the feature in the Power Apps portal. 𝐒𝐭𝐞𝐩𝐬 𝐭𝐨 𝐄𝐧𝐚𝐛𝐥𝐞 𝐂𝐨-𝐏𝐢𝐥𝐨𝐭 1. Open Power Platform Admin Center. 2. Go to settings and enable Co-Pilot in Power Apps. 3. Ensure the environment is ready with the early release cycle. 4. Enable "Try the new data experience" from the Power Apps homepage. 𝐂𝐫𝐞𝐚𝐭𝐢𝐧𝐠 𝐚 𝐂𝐨𝐦𝐩𝐥𝐞𝐱 𝐃𝐚𝐭𝐚 𝐌𝐨𝐝𝐞𝐥 1. Prompt Example: Create an employee management system with employee information and their multiple educational and experience details. 2. Co-Pilot sets up the app and creates an ER diagram with table structures. 3. The diagram shows one-to-many relationships between the employee table and multiple educational and experience tables. 𝐂𝐮𝐬𝐭𝐨𝐦𝐢𝐳𝐢𝐧𝐠 𝐓𝐚𝐛𝐥𝐞𝐬 𝐚𝐧𝐝 𝐒𝐜𝐡𝐞𝐦𝐚 • 𝐀𝐝𝐝𝐢𝐧𝐠 𝐂𝐨𝐥𝐮𝐦𝐧𝐬: 1. Select a table (e.g., Experience table). 2. Add prompts to include additional columns (e.g., start year, end year). • 𝐄𝐦𝐩𝐥𝐨𝐲𝐞𝐞 𝐓𝐚𝐛𝐥𝐞 𝐂𝐮𝐬𝐭𝐨𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧: 1. Add columns like gender, total experience in months, expected CTC, and actual CTC. 2. Co-Pilot creates the columns with appropriate data types. 𝐄𝐑 𝐃𝐢𝐚𝐠𝐫𝐚𝐦 𝐚𝐧𝐝 𝐌𝐚𝐧𝐮𝐚𝐥 𝐎𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐬 • The ER diagram provides a comprehensive view of the data model. • Options available to delete tables, hide data, add new tables, and import data from Excel, CSV, or SharePoint lists. 𝐂𝐨𝐧𝐜𝐥𝐮𝐬𝐢𝐨𝐧 • The new ER diagram feature with Co-Pilot is a game-changer for creating complex data models. #PowerApps #CoPilot #ERDview #DataModels #ComplexData #PowerPlatform #MicrosoftPowerApps #AppDevelopment #TechInnovation Thank you Dhruvin Shah for the excellent video on working with complex data models using ERD view and Co-Pilot in Power Apps! The new features and step-by-step guidance are beneficial.

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Every. Data Governance. Project. 🎢 →  We start with a shiny budget and big dreams. 💸✨ → Then, the plot thickens... "What do we mean by 'standard' again?" 🤔 → Data lineage? Suddenly, you're drowning in “spaghetti.” 🍝 → Stewardship? ↳ Sounds noble, right? ↳ Until it’s a maze of approvals. 🔄 → don’t get me started on agreeing on data definitions. 😂 → we made it! DG Version 1.0 is out the door. 🎉 let’s connect and share how you survived your DG rollercoaster. What were your lessons learned? Let’s chat in the comments!👇 P.S. Share this post to get more perspectives! ♻️ #DataGovernance #DataLife #DataChallenges #DataWins #LetsConnect

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I really struggle with pithy data storytelling titles and would love advice on how to approach it with this chart. It's a silly, dirty and quick #30DayMapChallenge inspired by Ansgar Wolsing https://lnkd.in/eeMfiPHf I've filtered maps::world.cities for cities with a population of at least 1 million and drawn a circle from each city to its closest partner - that's what the purple area represents https://lnkd.in/e3V8cyqw

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📊 𝙽𝚎𝚠 𝙱𝚕𝚘𝚐 𝚂𝚎𝚛𝚒𝚎𝚜: 𝚅𝚒𝚜𝚞𝚊𝚕𝚒𝚣𝚒𝚗𝚐 𝙳𝚊𝚝𝚊 𝚏𝚛𝚘𝚖 𝙰𝚗𝚊𝚕𝚢𝚝𝚒𝚌𝚊𝚕 𝙼𝚘𝚍𝚎𝚕𝚜 Last week, I kicked off a new blog series on how to visualize data from analytical models and started with why and for whom we do this. At the same time, I ran some polls in Power BI groups. The first question was: ➡️ 𝚆𝚑𝚢 𝚍𝚘 𝚠𝚎 𝚟𝚒𝚜𝚞𝚊𝚕𝚒𝚣𝚎 𝚍𝚊𝚝𝚊 𝚏𝚛𝚘𝚖 𝚊𝚗𝚊𝚕𝚢𝚝𝚒𝚌𝚊𝚕 𝚖𝚘𝚍𝚎𝚕𝚜? Your answers? 🏆 The top reason (with around 60%) was to identify trends and patterns. I was surprised that the developer view (validation or debugging) only got 1%. For me, this is also a key reason to visualize. But as many pointed out, it is important to consider WHO the audience is when we visualize data. That’s the focus of my current posts—whether it’s for developers, business leaders, or stakeholders. Stay tuned for the next posts and poll results! #PowerBI #DataVisualization #Analytics #DataViz

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A great article by Kurt Buhler providing high-level guidelines for creating useful reports/dashboards. Even though the examples used are from #PowerBI, the rule and principles described are universal and applicable to any report/dashboard's designs, regardless of #BI tool's choice. Key takeaways: Your guiding light: What questions are you trying to answer with this data analysis? Simplicity: Select the appropriate visual for the problem question and audience Efficiency: Minimize the time users need to spend on the report/dashboard #analytics #dashboards #reporting

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In today’s blog post, I repost an ungated version of my Business Day article with Pietman Roos in which we discuss the importance of data ethics in the age of big data and AI. https://lnkd.in/dTN86aiR

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This is #howimeasuresummit in the mornings of #measuresummit - have to utilize as many opportunities as possible to get through the list of talks! (What’s not apparent in this picture is Florian Möller’s talk about how to teach - some great takeaways there, pointed out some typical mistakes that I tend to make myself.) (I’ll still need to leverage my all access pass - I won’t get through my list this week for sure.) — #bigquery #digitalmarketing #analytics

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🔗 Deep Dive into the Final Component of the Business Trinity Compass 🔗 We've journeyed through the Business Trinity Theory and the Cycles of Discovery and Innovation, and now it's time to finalize our understanding with the last piece of the puzzle: the Business Trinity Compass. This post integrates these foundational concepts to unlock the full potential of the framework, identifying key areas that underscore core business activities. Get a comprehensive view of how discovery and innovation fit within the zones of the Business Trinity Compass, and see how these insights can lead to more focused and strategic business decisions. We'll cover the final elements that make this tool essential for anyone looking to excel in a business environment, particularly those progressing in seniority who need to master planning and strategic alignment. 👉 Read the full exploration here: https://lnkd.in/eMhbMhzd Stay tuned and subscribe for concise summaries and detailed breakdowns that can transform your approach to business management. #BusinessTrinityCompass #BusinessInnovation #StrategicManagement #LeadershipDevelopment #TheTechniciansMBA #CareerGrowth #BusinessFramework #DiscoveryAndInnovation

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 DATA GOVERNANCE @ WESTNETZ – PART 1 🚀 🆕 #DataGovernance creates resistance? Doesn't have to be. Indeed, all innovation-driven measures generate resistance. As early as 1973, Eberhard Witte identified various barriers in innovation management in his work "Organization for Innovation Decisions". These barriers can of course be minimized in the long term and should be! However, I would like to use data & AI today to further develop the specialist areas of my company in an innovation-driven way. How do I do that? I don't just minimize the barriers, I undermine them. With non-invasive data governance!   What does that mean? Robert S. Seiner described the basic features of non-invasive data governance a long time ago in his fabulous book. The quintessence is essentially this: You focus on formalizing what is already there: the existing responsibilities. At Westnetz, we implement our data governance in the same way. We use the already established process house with our core processes to integrate data responsibility in a meaningful way. We are therefore not building an independent system, but rather expanding established processes. We design processes, IT & data together. Peter Jaschek, Juergen Groenner We have not yet reached our goal and are not yet actively involved in all core processes, but we are working on it.   --------------------------------------------------------------------  Data governance for proactive data quality management, data transparency & competence. Data governance is the incubator of digital transformation.   We are the distribution network operator for data.  #dataexcellence ⚡ Romina Pyplacz geb. Medici Dr. Maria Garbuzova-Schlifter Dominik Lis Dr. Linda Dieckmann Dr. Norman Schumann  

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Those interested in interoperability, including laboratory interoperability should comment through August 23rd on the expanded Data Usability Implementation Guide. The guide focuses on health data exchange across EHR, HIE, Public Health, and laboratories, leveraging published standards to lift everyone up together and help retain vital information in exchanges for downstream users.

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Drowning in Data? Climate change: the information overload is real. But data alone isn't enough for true sustainability leadership. This video cracks the code on: Unveiling the blind spots: Data is key, but what are we missing? Challenging your bubble: Are you hearing all sides of the story? Embracing the uncomfortable: Can you handle the whole truth? Watch to unlock the secrets of navigating the information overload and building a more informed, collaborative path to a sustainable future. #SustainabilityLeadership #CriticalThinking #ClimateChange #Collaboration

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The Gartner® Magic Quadrant™ for Analytics and Business Intelligence Platforms 2024 is finally out. Recognizing Qlik as a leader for 14 years straight! Read up on our Qlik Partner Ambassador Olof Malmström thoughts on the movements below. #GartnerMQ #Qlik #DataAnalytics #BusinessIntelligence

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Gjensidige's #AnalyticSummit is over but being on stage this week is not. Finalizing slides for #PowerHour where we will explore the power of external tools like #TabularEditor and #DAXStudio to optimize #PowerBI semantic models. Thanks Daniel Otykier, Darren Gosbell, Michael Kovalsky for these amazing community tools and BPA rule collection!

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Thanks Sam Knowles for this amazing conversation. Fluency in business is absolutely important for putting data into action. A strong grasp of statistics is also integral for leveraging data. The mixture of business acumen and statistical proficiency empowers organizations to make informed decisions and drive strategic success in a data-driven world. Wrapping it all up into a story is a superpower. Unfortunately, both business and statistics are often overlooked when growing a data team. Those are the pillars of data story telling.

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Protecting sensitive information 🔒 is a top priority in BI. In our latest blog post, Oliver Vetesi explores how Data Masking in #PowerBI ensures data security while enabling powerful analytics 📊. Our first article in this two-part series covers: ✔️ How Power BI handles data through Direct Query, Import Mode, and Direct Lake. ✔️ The impact of source-level data masking on report security. ✔️ Key roles in data workflows: the report builder 🛠️ and the report user 👥. Coming soon in Part 2: We’ll dive deep into native solutions like Object-Level Security (OLS) and Row-Level Security (RLS), as well as creative, non-native approaches for dynamic and secure reporting. Ready to level up your Power BI data security skills? 🚀 Check out the full article here: https://lnkd.in/dE_fJcXd #PowerBI #DataSecurity #BusinessIntelligence

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🚀 Unlock the Power of RAG and Knowledge Graphs for Your Business! 🚀 Tired of drowning in data without getting the answers you need? Want to empower your teams with intelligent, data-driven insights? RAG and Knowledge Graphs are the solution! 🧠 RAG (Retrieval Augmented Generation): How it Works: RAG combines the power of large language models with your company's internal data. It understands natural language queries, searches your knowledge base, and synthesizes relevant information into clear, concise answers. Benefits: -> Instant Expertise: Get answers to complex questions without relying on manual research. -> Data-Driven Decisions: Make informed choices based on accurate, up-to-date information. -> Improved Productivity: Save time and resources by automating knowledge retrieval. 🌐 Knowledge Graphs: How They Work: Knowledge graphs create a structured representation of your company's information, linking concepts, entities, and relationships together. This enables RAG to understand the context of your queries and provide more accurate, relevant responses. Benefits: -> Deeper Insights: Uncover hidden patterns and relationships within your data. -> Enhanced Personalisation: Deliver tailored recommendations and experiences to customers. -> Accelerated Innovation: Identify new opportunities and drive growth by understanding your data landscape. Real-World Applications: 1. Customer Support: Provide instant, accurate answers to customer questions, improving satisfaction and reducing support costs. Decision Intelligence: Empower executives with data-driven insights to make better strategic decisions. 2. Knowledge Management: Create a central repository of knowledge accessible to all employees, fostering collaboration and innovation. 3. Product Development: Analyze customer feedback and market trends to create products that truly meet user needs. Ready to Transform Your Business? RAG and Knowledge Graphs are not just buzzwords; they're powerful tools that can revolutionize how you use data to drive success. Let's connect and discuss how to unleash their potential for your organization! #RAG #KnowledgeGraphs #AI #DataDriven #BusinessTransformation #DigitalTransformation #Innovation #CustomerExperience

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