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Christina Albrecht
Data is the new Digital - Transformation hört nie auf!
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Gestalter oder Verwalter (33)AI, das WHY und der Data ScientistDer fantastische Artikel HBR von Tom Redman bringt es auf den Punkt!🤖 Data Science existiert schon lange, aber die Misserfolgsquoten von Big-Data- und AI-Projekten sind weiterhin besorgniserregend hoch.🎟️ Trotz des Hypes können Unternehmen noch nicht konkret den Beitrag der Datenwissenschaft zu ihren Gewinnen nachweisen.⁉️ Woran liegt das und wie können wir das in Zeiten in denen AI zum Turnaround für die Wirtschaft ernannt wird ändern?Eine treiben Rolle im Hype spielen Data Scientisten. Deshalb schaut Tom besonders auf ihre Rolle!🧠 Data Scientisten beschäftigen sich gerne mit komplexen Algorithmen und Facts.👨💻 Ein tiefes Verständis für Business Probleme ist bei ihnen oft nicht vorhanden.💓 „Weiche Themen“ wie Vertrauen aufbauen, Dinge auf simple Art und Weise erklären und Geduldig mit Bedenken umgehen werden häufig hinten angestellt oder gar nicht gesehen.Laut Tom sind 4 Dinge zu tun:1. Wertbetrag klären2. Fortschritt messen3. Ende zu Ende Verantwortung von Data Scientisten für ihre Arbeit verlangen4. AI Wissen innerhalb ihrer Abteilungen und im gesamten Unternehmen weitergeben.Wie integriert ihr Data Scientisten ins Unternehmen und wie sichert ihr den Geschäftserfolg der AI Initiativen?Sven Matuschzik Lukas Biermann Beate Braun Dr. Nicole Lehmkuhl Kinda El Maarry, PhD Dr. Franziska Deutschmann Johanna Viktor Karsten Ramm André Bojahr David Goebel Hermann Speiser @Pascal Mai#GestalteroderVerwalter #AI #GenAI #DataScience #E2E #AIGovernance #HBR#PeopleandData
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Amit Gal
Data Science & ML expert | Strategic thinking | Advanced algorithms | Interdisciplinary research | mentoring and attentive leadership
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Many data science projects operate "behind the scenes" of products and services. Sometimes the data scientists operate in a very shielded environment, solving statistical problems whose connection to the real world problem that initiated the project is might be not much more than the name of the variables in the dataset (well, I am exaggerating a bit here).Still, I think that having a "product mindset" role in data science teams is essential. It doesn't necessarily have to be a full time product manager. Sometimes it will be just the team lead that will perform this role, but it must come with a product mindset.Why? Because more often than not I see the "end users" of such statistical models misuse or abuse or totally ignore or don't understand what to do with those predictions or recommendations and other statistical outputs. It is perfectly fine for a decision maker not to understand what confidence interval is, but it would be unprofessional to report it (e.g. as an output from the model). The link between "reporting it" and "understanding it" and "using it" is exactly what product managers do when the design features. They think about the users, their needs and their "mental model". They think about what the software can do, and they they design way to connect them together. to find the fit between the system and the user. Between the need and the solution.It is the same, and even more important when we deal with statistics and decision making. If the outcomes of a statistical model are misunderstood or misused or just not snugly fit to the way the users perform tasks - wrong decisions might be made, making models useless.
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Prof. Dr. Axel Winkelmann
Professor
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Können wir es uns heute noch wirtschaftlich erlauben, nicht jeden Stein im Unternehmen umzudrehen, um bestmöglich effizient im internationalen Wettbewerb zu agieren? Business Process Management hat sich dem Efiizienzgedanken schon immer gestellt, doch die Kosten und der Aufwand für mühevoll erstellte Prozess"tapeten" und dadurch generierte Beraterstunden scheinen heute zu hoch. Datengetriebene Themen wie Hyperautomation, Process und Task Mining bieten neue, flexiblere und effizientere Ansätze. Mit zahlreichen weiteren Fachexperten haben wir daher unsere Erkenntnisse in einem Positionspapier zu "Recent Advances in Data-Driven Business Process Management" zusammengeführt. Danke euch für die guten Diskussionen und interessanten und tiefen Insights aus den einzelnen Forschungsgruppen: Lars Ackermann, ;artin Käppel, Linda Moder, Laura Marcus, Sebastian Dunzer, Markus Hornsteiner, Annina Liessmann, Yorck Zisgen, Philip Empl. Lukas-Valentin Herm, Nicolas Neis, Julian Neuberger, Leo Poss, Myriam Schaschek, Sven Weinzierl, Stefan Jablonski, Agnes Koschmider, Wolfgang Kratsch, Martin Matzner, Stefanie Rinderle-Ma, Maximilian Röglinger und Stefan Schönig.
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Ujjyaini Mitra
Building Deltacube.ai & SETU. DC offers Data Science, AI innovation & Digital Transformation. SETU - Bridging the Gap of Emerging Industry Skill demand in Data Domain
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Data Leadership is not just a position, It's an Attitude that comes with Responsibility. Many of you can achieve it, but do you feel as if something is holding you back? What's holding you back are mostly your self-imposed obstacles. It is not something or someone external to you. 🔶 Self Doubt - I still remember the day I was offered the Team Leader position, and senior management wanted to prepare me for the same, I denied it instantly because I thought I was not made for a leadership role. As an introverted person, I am not sure if could do justice to the role. Thankfully other leaders suggested I walk the path and then decide, the rest is history.🔶 Fear of the learning curve - We all fear the change, and feel comfortable to stay within our cocoons. But success and comfort can not coexist. When I was joining ZEE5 as Head of Data, CEO asked me to consider Market Research under the Data team. But I never touched that domain. I was anxious to put logic as to why it should not be part of the data. He said 'Ujjyaini, it's not rocket science, shikh le na' 🔶 Magical Shortcut - there is no magical shortcut to grow. You have to take the steps, walk the path, fall, get up again and continue to walk. You will be hurt, you will be scared. Make peace with it. 🔶 Procrastination - At times even when we know what we need to do, we keep pushing it back and think that we will start sometime soon. Unfortunately, tomorrow never comes. Either you do it NOW or never.🔶 Rigidity - We all have our baggage and biases that we keep accumulating through our experiences. We end up judging more through those rigid lenses. Unshackle those thoughts, and stay open to picking up something different than you ever did or you were hired for. You never know, you may be the chosen one for the next big role. 🔶 Waiting for the position - I have heard many say 'I am looking out because my company is not promoting me, I deserve better'. Why are you waiting for the company to give you the position for you to play the role? Identify opportunities and proactively start to play the role that you envision. Consider yourself a product, and this proactive role play is your proof of concept. Promotion will follow. 🔶 Inertia - We expect too much from Digitization. But human connections are best made in person, whether it's with your clients, your peers, customers, investors or stakeholders. Go out, show up, build a true human connection, and observe the rewards. DM me, if you are aspiring to grow to a Data Leadership role, and feel you are stuck. I will be happy to coach you. #dataleadership #dataattitude #careeradvice #careergrowth #leadershipjourney #selfimprovement #dataprofessionals #coaching #ai
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Christian Adib
Building the GenAI application layer
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Unsolicited advice to young Data Scientists who want to work in ProductSeek customer-facing roles early in your career. This helps you develop the business sense required to succeedA great model isn’t necessarily one that scores high on your suite of evaluation metrics of choice, it’s a model that helps you maximize profitability, reduce churn, or convert leadsI sometimes see very smart folks jump straight into building excellent models that end up having little business value. Avoid getting hands on keys before you’ve had the time to map things out clearly. Seek feedback where you need it
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Paul Thierbach
Territory Acount Manager || D•A•CH
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Calabrio Introduces Insights - our new AI-powered reporting tool in CalabrioONE! calabrio.com🥁 🥁 🥁 Wir stellen Insights vor - unser neues KI-gestütztes Reporting-Tool in CalabrioONE™!
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Snigdha Jha
Product | Fintech | Data
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Why I Nearly Passed on Being a Data Product Manager — Until the Job Completely Shifted My… link.medium.comWhen I first transitioned from data engineering to product management, I was skeptical about the “Data” Product Manager title 🚩 I worried it would be the same BI/Data Engineering work with a fancier label. But 3.5 years later, I’m glad I took the leap. 💚 In my latest post, I break down what makes a Data PM role truly unique—how it goes beyond just dashboards and insights to deliver real value through strategic planning and stakeholder empowerment. 📊 Whether you're a product manager, data enthusiast, or just curious about the intersection of data and business, this one's for you. 💡 Check out the full article on Medium and if you are a seasoned Data Product manager, please leave in comments the kind of products you have developed or are on your roadmap ⭕ 🍏 #productmanagement #businessintelligence #analytics #data #career #pivot
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SeriesExplorer
7 followers
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Was ist ein repräsentativer Abschnitt meiner Messdaten? Time Series Data Science findet Antworten mit Snippet Localization Algorithmen. Mehr dazu in diesem Artikel: https://lnkd.in/eX9gmux2 #TimeSeries #DataScience #MachineLearning
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Fadle Saad
Managing Director - HP KSA
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New Employee Spotlight: Welcoming Maro Derhovanessians, Our New Business Analyst! I'm thrilled to introduce Maro, who has joined our team as our new Business Analyst. Maro brings a wealth of experience in data analytics, strategic insights, and a keen understanding of how data can drive business success.In today’s fast-paced world, the ability to analyze data effectively is more critical than ever. Business analysis isn't just about numbers; it's about translating data into actionable insights that guide our decision-making and help us navigate the complexities of our industry. Maro will be instrumental in ensuring our strategies are data-driven, allowing us to make informed decisions that support our goals and propel our business forward.I’d also like to touch on the growing importance of AI in our field. AI is revolutionizing how we approach business analysis, enabling us to process vast amounts of data with speed and precision. By harnessing the power of AI tools like Microsoft Copilot, our team is able to uncover deeper insights, enhance operational efficiencies, and stay ahead of the curve in a competitive market.With Maro’s expertise and the advanced tools at our disposal, I am confident that our team will continue to innovate and excel in delivering data-driven strategies that lead to success.Please join me in welcoming Maro to the team! We’re excited to see the impact you'll make. 🚀#HP #BusinessAnalyst #DataDriven #AI #TeamSpotlight #Innovation #Leadership #Microsoft #Copilot
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